So why do you need skills for Claude Code?

If you’ve been using Cowork a lot (like me), you’ve probably hit a wall already. Cowork has limits that keep it safe for non-technical folks. That’s a good thing most of the time. But every now and then, you want to do more than it allows.

That’s when you need Claude Code.

And no, you don’t need to be an expert programmer to use it. Especially if you have the right skills installed.

When you build something with code, half the job isn't writing it. It's making sure it actually works: catching bugs, testing it, not shipping something that breaks the second someone uses it.

That's the part that scares people off (and what takes real experience).

These skills do that part for you! Claude plans it, tests it, and reviews its own work. You just steer.

In this guide, you’ll get:

• How to quickly install a Claude Code skill

• The best 6 Claude Code skills

• The exact command to install each one

Every week, I publish new Claude guides: some free, some paid.

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How to Install a Claude Code Skill

This part scares people off for no reason.

Installing a skill is usually one command pasted into your terminal.

Most skills live in something called a "marketplace" (think of it like an app store for Claude). The official ones are already connected, so you just install.

Here’s how to install one:

1. Open Claude Code in your terminal.

2. Paste the install command for the skill you want (I list each one below).

3. If a skill lives in its own “marketplace,” add the marketplace first, then install it.

4. Restart Claude Code, so it picks up the new skill.

Here’s an example:

That’s it. Most skills install in under a minute.

Pro tip: install the ones you’ll use everywhere (like Skill Creator below) “globally,” so they work in every project without you having to think about it.

The best 6 Claude Code skills

1) Skill Creator

Problem:

Most people who try to build their own skill hit a wall fast. They don’t know the structure, the formatting, or what makes a skill reliable. So they either give up or build something that breaks the second a client touches it.

The skill:

skill-creator is the official Anthropic skill that builds other skills. You describe what you want in plain English, like you’re explaining a task to a coworker. Claude drafts the skill, tests it, fixes it, and packages it into something you can reuse forever.

Why it works:

Every custom skill you make later comes out of this one. It compresses the whole learning curve from "I have no idea how skills work" to "I just made one in five minutes"

This is the first one I'd install. Here’s the command to install it:

/plugin install skill-creator@claude-plugins-official

2) Grill Me

Problem:

Claude loves to jump straight to a plan. You give it a half-formed idea and it spits out a full document before it actually understands what you want. Then you spend the next hour correcting it.

The skill:

This one comes from Matt Pocock and it’s one my favorite skills. It tells Claude to interview you relentlessly about your plan until you both actually understand it, working down every branch of the decision before writing a single line of code. In one session, it asked Matt 16 questions. On bigger features, he’s had it ask 30 to 50.

Why it works:

Most mistakes come from Claude guessing what you meant. Grilling kills the guessing.

Here’s the command to install it:

npx skills@latest add mattpocock/skills -s grill-me -g

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3) Superpowers

Problem:

You ask Claude Code to build something. It sprints out of the gate, writes the whole thing in one shot, and on the surface it looks great. Then you actually run it. Or worse, your client runs it. And it falls apart. Why? Claude doesn’t plan. It doesn’t test. It doesn’t double-check its own work. It just writes.

The Skill:

It forces Claude to work like a senior developer. Step back and plan the whole thing first. Work in an isolated environment so nothing breaks your main project. Write tests before writing code. Then review its own work twice. Once for “does this match what I asked for” and once for code quality.

Why it works:

Most failures with Claude Code aren’t from Claude being dumb. They’re from Claude rushing. Slowing it down just enough to actually think gets your first pass to 80% instead of 60%. That means fewer debugging cycles, lower token costs, and code that doesn’t fall apart the second a real person uses it.

Here’s the command to install it:

/plugin install superpowers@claude-plugins-official

4) Frontend Design

Problem: When Claude builds a website or a slide deck on its own, it often looks AI-generated. Generic, a little off, the kind of thing you’d want to redo before showing it to anyone.

The skill: Frontend Design is the official Anthropic skill for making the things Claude builds actually look good. Install it, and whenever you’re designing something in Claude Code, the output comes out looking a lot less “an AI made this.”

Here’s the command to install it:

/plugin install frontend-design@claude-plugins-official

5) Context Mode

Problem:

Use Claude Code for a while and you’ll notice this: Things get sluggish, it forgets what file you were editing, it asks what you wanted to do (again). What’s happening is every command Claude runs dumps a pile of raw output into its memory. After about 30 minutes, most of that memory is junk. Claude has to reset to keep going. And when it does, it forgets where you were.

The Skill:

It does two things. First, it filters the junk before it ever reaches Claude’s memory. Only the useful part of each command makes it through. Second, it keeps a running log of your session (files edited, tasks in progress, your last prompt). When Claude resets, it pulls that log back in and picks up exactly where you left off.

Why it works:

Most “long sessions” with Claude Code aren’t really long. They’re a bunch of short ones glued together with you re-explaining yourself. This kills both problems at once: less garbage going in, full memory of what you’ve done. Sessions that used to die at the 30-minute mark now run for hours.

Here’s the command to install it:

/plugin marketplace add mksglu/context-mode

/plugin install context-mode@context-mode

6) Claude Mem

Problem:

Claude Code starts every new session from scratch. So you end up explaining the same project over and over again, wasting time and thousands of tokens just catching Claude up.

The skill:

This skill carries your knowledge across all your future sessions. It hooks into Claude’s session and automatically captures what happened: the file edits, the decisions, the bug fixes. It compresses all of that into summaries and stores them locally. When you open a new session, the relevant parts get pulled back in automatically. It even writes and updates your project notes for you while you work.

Here’s the command to install it:

/plugin marketplace add thedotmack/claude-mem

/plugin install claude-mem

Bonus: /review and /ultra-review

Problem:

Even careful work has bugs Claude misses on its own. You need a second set of eyes before you ship something that actually matters.

The skills:

This one isn’t an install. It’s already built into Claude Code, and most people just aren’t using it. When you finish writing code, type:

• /review: Claude does a structured review of what you just built, hunting for bugs, edge cases, and design issues

• /ultra-review: sends your work to the cloud and spins up a whole team of reviewer agents that each attack from a different angle (logic, security, performance)

Use /review for fast, free feedback on everything. Save /ultra-review for the big stuff: a major change, or anything touching payments or a database.

One more thing

Don’t install all the skills at once.

That’s the fastest way to get overwhelmed and use none of them. Pick one, learn it, build a few things with it, then add the next.

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Summer is coming!

Diana and I prepared a guide on how to use AI on vacation trips. She has more travel experience than I do, but I’ve also added my own experience to complement her ideas.

Imagine this: you’re in Barcelona, it’s 9 pm, every restaurant around you just closed, and you’re starving. You’ve spent the last 30 minutes scrolling Google Maps trying to find one place that’s still open AND serves what you actually want.

No luck.

This used to be me. But in about 20 seconds, AI pointed me to a place 10 minutes away that was still open and served exactly that.

That wasn't the only time AI saved my trip.

After that, I started using AI for almost everything on my last two trips: one across the US West Coast (I’m not from the USA), the other through Portugal. I used ChatGPT, Claude, and Gemini for almost everything: translating to shopkeepers in Cascais, planning a 12-day road trip, finding scenic routes, and even figuring out the location of a beach I saw on Instagram.

Some of these saved me hours. One of them saved an entire day. A few I would never have even thought of without AI.

In this guide, you’ll learn:

• The exact prompt I used to plan a trip in minutes (copy-paste ready)

• How AI helps me save money on my trips

• How to overcome the language barrier using AI

• How to find a place you saw on Instagram (even when nobody says where it is)

• The rules to follow to use AI safely in your trips

• and more!

Here’s how to upgrade your next trip with AI

This guide is exclusive for paid subscribers :)

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I’m fascinated by how this works now. You no longer need a ton of technical knowledge (especially coding) to build tools, automate boring tasks, and more.

I’m not exaggerating. I haven’t written a single line of code when building with Claude.

No programming language needed. Just one language: English.

As Andrej Karpathy said, the hottest new programming language is English. I’ve been literally talking to Claude Cowork to build things. When I say talking, I mean it. I don’t type anymore.

What I do is use voice dictation.

Why? Because you have to give Cowork a lot of detail (just like you’d brief a coworker). If you type all of that, you either skip some details or waste a bunch of time doing it.

So I tested the voice dictation tools out there to find the one that fits this kind of work.

In this guide, we’ll see:

• The built-in voice dictation on your computer (and why it’s usually not enough)

• AI voice dictation tools (with the best use case for each)

• The setup I personally use to talk to Claude

Note: No one is paying me to write this, and I'm not associated with any of these tools. After using them for a while, I actually think most people won't need the fanciest features these tools sell you.

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Built-in voice dictation (macOS and Windows)

If you've ever tapped the microphone icon on your phone keyboard, you already know what voice dictation is. Same idea, just on your computer.

Here’s how to turn it on:

1. On macOS, press the Globe key twice (set it up in Settings → Keyboard)

2. On Windows 11, press the Windows key + H

A small mic icon pops up. Start talking, and it starts transcribing.

On macOS, it’s basically a real-time transcription. The moment a word leaves your mouth, it shows up in whatever app you’re in.

It’s decent. But it hasn’t caught up with the modern tools out there.

Here are its weak points:

• It transcribes what you say literally (no AI cleaning words like “uh” and “um“)

• The auto-punctuation is basic. You have to say “question mark” to get a “?”

• It has a 30-second timeout that interrupts longer sessions

This might sound like nothing. But these little things change the way you talk. You end up adapting to the tool instead of just speaking naturally.

That's exactly what AI dictation fixes.

They let you talk naturally, like you're talking to a coworker or a friend. The tool adapts to you (not the other way around).

The AI tools below are paid, and I’m going to talk about them based on my own experience.

But here’s my honest advice: try them before you pay. All of them have a free version or demo, and which one fits you really comes down to how you’ll use it.

I mostly use voice dictation for building things in Claude Cowork and Code. For that, I don’t need super polished text or fancy formatting (the AI understands my raw text just fine). So for me, the cheapest option (VoiceInk) in this list already does the job.

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VoiceInk: The most affordable, reliable choice (macOS)

VoiceInk is a Mac app that turns your speech into text right where your cursor is, in any app. Everything runs locally on your machine, so your voice never leaves your device (no cloud, nothing sent anywhere).

The best thing? You pay once: $39, no subscription.

The catch: it’s macOS only (and it needs Apple Silicon and macOS 14.4 or later).

As a Mac user, this is enough for me. It does exactly what I need when working with Claude: decent speed, custom vocabulary, and AI cleanup.

The setup that gives me the cleanest text:

1. AI model: gemini-3.1-pro-preview

2. Add tricky words to the dictionary (like “Claude” and “Cowork”)

With that, I get text nearly as clean as what the more expensive tools deliver.

A few honest notes after using it:

• It’s a big step up from the native dictation (better punctuation, fixes your mistakes)

• It cleans up your slips and stops you from repeating words and phrases, kind of like a quick proofread

• It doesn’t auto-format like other tools do (no automatic bullets or numbered lists)

• I’d say it’s around 95% accurate. Once in a while, it drops or adds a random word

For talking to Claude, that’s more than enough. And at $39 once, it’s the easiest one to recommend.

By the way, I discovered VoiceInk thanks to quick review. Thanks, Sabrina!

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Superwhisper: Good option if you're on Windows

I haven't used Superwhisper as much as VoiceInk, but I'm including it for three reasons. It’s good, runs on Windows, and also offers a one-time payment.

The core idea is the same as VoiceInk: it runs locally on your device, drops text wherever you're typing, and keeps your voice off the cloud (as long as you stick to the local models).

What makes it different:

• It works on macOS, Windows, and iOS

• You can tune it a lot (different modes, model choices, custom prompts per app)

• It does more than dictation. It also records meetings and transcribes audio files

Superwhisper has a free tier to test it, a monthly plan ($8/month), and a one-time lifetime license at around $250.

One thing worth knowing before you jump in: all that tuning means a bit more setup. It’s more powerful, but less “install and go” than VoiceInk

If I were on Windows, I’d start with the free version, test it for a few days, and only pay if it clicks (same advice I’d give for any of these).

Wispr Flow: The polished, no-setup option (but pricey)

Wispr Flow is a cloud-based dictation app that turns your speech into polished text in any app. The big difference from VoiceInk and Superwhisper is the heavier AI rewriting.

It makes your text prettier.

Here's what Wispr Flow does that the other two don't (at least by default):

• It generates transcripts faster

• The text comes out more polished: great punctuation, fixes speech mistakes, avoids repetition

• It automatically creates bullets or numerated lists when needed

These features are great. But in my case, I don’t need them that much.

The faster transcript is a few seconds quicker, and I don’t need polished text or bullets when I’m talking to Claude Cowork or Code (the raw text is enough for the AI to understand me).

Wispr Flow is $15/month (for my use, it’s overpriced)

So who is it for? If you want AI-polished text in your emails, documents, and messages with zero setup, and a monthly subscription and cloud processing don’t bother you, Wispr Flow is a great pick.

It’s not for you if you mostly dictate into AI tools (Claude, ChatGPT, etc), because the raw text is already enough there. You’d be paying for features you won’t use.

What’s your favorite tool? Let me know in the comments

P.S. Superwhisper or Wispr Flow aren’t always 100% accurate. Because of the price, I expected them to be way more accurate than VoiceInk, but they occasionally get some words wrong. Again, I recommend trying them yourself.

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A couple of years ago, using AI felt like a superpower. Something that could put you ahead of almost everyone in any room.

Today, it’s starting to feel more like knowing how to use Word or Excel.

Useful, yes. But no longer impressive.

AI is becoming part of the modern work toolkit, not just for tech people.

Writers use it to draft
Marketers test ideas with it
Students use it for assignments
Entrepreneurs use it to move faster

Everyone “uses” AI. Few get anything real out of it.

That’s exactly why just using it won’t protect your job anymore.

The edge now comes from how you use it and what you can actually produce with it: executing faster, communicating better, thinking more clearly, making smarter decisions, etc.

The gap between basic AI use and real advantage looks small. The results aren’t.

One person asks AI for a quick, generic draft.
Another gets it to write in their own voice, matching the company’s style.

One person saves 5 minutes on emails.
Another has systems running while they sleep.

In 2-3 years, “I use AI” won’t mean anything. Everyone will say it.

What will actually matter is what you can do with it that the next person can’t.

This guide gives you exactly that:

• The 3 modes that tell you what to delegate to AI and what to never hand over

• Why a workflow beats a pile of prompts (and the 5 questions I use to build one)

• How to turn AI’s instant answers into real judgment, the skill that doesn’t go obsolete

• The simple formula behind a real professional advantage

The free part showed you the problem. The rest shows you the fix.

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They actually have a context problem.

Claude is smart enough to help with almost anything. But most of the time, the information it needs isn’t in the chat. It’s sitting in your emails, your calendar, your documents, your tickets, your databases, your internal tools.

So the workflow ends up looking like this:

Search for information → Copy it → Paste it into Claude → Wait for a response → Copy the response → Move it somewhere else

It works, but it doesn’t scale.

That’s where Claude connectors come in.

Connectors let Claude talk to apps like Gmail, Notion, Google Drive, and others, so it can pull info from them or take actions on your behalf, instead of you copy-pasting things into the chat.

Skills tell Claude how to work. Connectors give Claude access to where the work actually lives.

In this guide, we’ll see:

• The 10 best Claude connectors

  • Connectors for Docs & Knowledge

  • Connectors for Communication

  • Connectors for Design

  • Connectors for Code & Data

  • Connectors for Business Operations

• How to quickly install a Claude connector

I’ve added a tutorial link to some connectors, in case you’d like to dig deeper.

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The Best Claude Connectors

Claude has dozens of connectors. Here are the best we found

Connectors for Docs & Knowledge

1) Google Drive Connectors

Problem:
Your files are scattered across folders. You know the information is somewhere in Drive, but you still have to search for it, open the file, copy what you need, and paste it into Claude.

Connector:
Google Drive connector lets Claude work directly with your files: search documents, summarize folders, review content, or compare files. Drive is usually where the real context lives, and this connector removes the bridge step between Claude and your documents.

Link: Watch the tutorial

2) Notion

Problem:
Notion is where good ideas go to hide.

You save project notes, content ideas, research, tasks, templates, and half-built plans. Everything is “organized.” But when you actually need something, you end up searching through pages, opening old notes, trying to remember where that one useful idea was.

Connector:
Notion connector connects Claude to your workspace so it can search pages, summarize notes, reorganize information, and turn scattered content into something usable, whether it's internal documentation, a content system, research, or a personal knowledge space.

Link: Watch the tutorial

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Connectors for Communication

3) Gmail Connectors

Problem:
Your inbox knows more about your work than you do.

It has the request, attachment, deadline, follow-up, decision, and probably someone waiting on a reply.

But Claude only sees the email you pasted. So every time you want help, you have to manually reconstruct the conversation first.

Connector:
Gmail connector gives Claude access to your inbox, where every decision, request, and follow-up already lives. It can search threads, summarize conversations, find pending items, and help you prepare replies.

Link: Watch the tutorial

4) Google Calendar

Problem:
Claude can help you plan. But if it doesn’t know your calendar, the planning stays disconnected from what your week actually looks like.

It doesn’t know your meetings, your open blocks, your deadlines, or your focus time.

Connector:
Google Calendar connector gives Claude access to your real schedule so the planning it helps with actually fits your week. It can find open blocks, prepare agendas, detect overloaded days, or help you reorganize tasks.

Link: Watch the tutorial

5) Slack

Problem:
Slack is where a lot of important decisions happen. And it’s also where they get buried fast.

Between threads, replies, channels, and scattered messages, context gets lost.

Then someone asks what was decided, who was responsible, or what the next step was. And you have to search manually.

Connector:
Slack connector gives Claude access to your conversations before the context disappears. It can search threads, summarize channels, identify decisions, find blockers, and turn discussions into next steps.

Connectors for Design

6) Figma

Problem:
Going from Figma to code seems simple until you try to match the design.

The spacing is slightly off.
The components don’t line up.
The layout works, but it doesn’t feel like the original screen.

And then someone from design notices.

Connector:
Figma connector gives Claude access to the design context: frames, layouts, components, variables, and visual structure. It can help generate code or implementation plans from the actual design intent, not from a screenshot.

7) Canva

Problem:
Creating visual content usually means jumping between tools.

You ask Claude for ideas → go to Canva → build the design → go back to Claude to adjust the text → go back to Canva to edit → repeat.

Connector:
Canva connector brings thinking and designing into the same workflow. It can help you go from concept to copy, to layout, to a finished asset you can keep editing. Useful for creators, marketers, and educators building presentations, newsletters, carousels, or branded content.

Link: Watch the tutorial

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Connectors for Code & Data

8) GitHub

Problem:
When you ask Claude for coding help without the repository, the answer stays generic. It doesn’t know your file structure, your open issues, your branches, or how the project is actually set up.

Connector:
GitHub connector lets Claude work directly with your repository so its help goes from generic to specific. It can read files, review issues, check pull requests, look at branches, and help you plan or prepare an implementation.

9) BigQuery

Problem:
Data teams often store important information in data warehouses.

But asking questions about that data usually means going through dashboards, SQL, exports, or an analyst who has access.

Connector:
BigQuery connector lets Claude work directly with your datasets, tables, and queries: review schemas, generate SQL, run queries, and explain results. It removes the friction between the data your team already has and the answers they need.

Link: Watch the tutorial

10) Power BI

Problem:
Dashboards show answers. But they don’t always explain how those answers were built.

A metric comes from a DAX measure.
A visualization depends on relationships between tables.
A filter changes the result.
A report looks clear until someone asks: “Where does this number come from?”

Then you’re no longer looking at a dashboard.
You’re investigating the model.

Connector:
Power BI connector connects Claude with your semantic models: tables, relationships, measures, metadata, and DAX queries. It can help analysts and BI teams audit metrics, explain where a number comes from, and dig into the logic behind a report. The remote server version also lets you query models in plain language while keeping your permissions in place.

Link: Watch the tutorial

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Connectors for Business Operations

11) Stripe

Problem:
Payments, subscriptions, invoices, customers, and refunds all live in Stripe.

When something goes wrong or someone has a billing question, figuring out what happened usually means digging through the dashboard manually.

Connector:
Stripe connector gives Claude direct access to your Stripe data: customers, payment history, invoices, subscriptions, and refunds. When a billing question comes up, Claude can find the context it needs without someone having to pull it manually.

Link: Watch the tutorial

How to install a connector

Here’s how to install connectors on Claude, Claude Cowork, and Claude Code.

Claude Cowork or Web: Customize → Connectors → “+” → Browse connectors → Choose an Connectors

Claude Code:

1. Open the Claude Code terminal and run:

claude mcp add [my-mcp] -- npx -y mcp-package-name

Replace [my-mcp] with the name of the Connectors you want to install.

2. Then verify the installation with

/mcp

If you liked one of the connectors listed, share this guide with others!

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I’ve used ChatGPT to explore new topics (especially with voice mode)
I’ve used NotebookLM to learn from my own materials

Then I started using Claude Cowork and my learning habits changed completely.

My approach today looks completely different. I learn faster, I retain more, and I actually do things while I'm learning instead of just consuming information.

In this guide, you’ll learn:

• How Claude Cowork helps me learn AI faster by doing

• Why voice dictation beats voice mode for learning

• The “learning profile” method that turns Claude into a personal tutor

Heads up: this guide covers my approach to learning using Claude. Some of it transfers to other chatbots, some doesn’t. At the end, I'll share when I reach for ChatGPT and NotebookLM for learning (spoiler: each one wins for a different job)

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This time, I asked AI writers to share theirs.

We use Claude daily in our real work. Between us, we’ve built dozens. We picked our #1 skill.

In this guide, we’ll see:

• The best skills we built

  • Skills for Writers & Content Creators

  • Skills for Making Better Decisions & Research

  • Skills for Busy Professionals

  • Skills for Building with Claude Code

• How to install the skills in Cowork

• How to build your own skill in Cowork (+ my tips)

Quick reminder if you’re new: Skills are reusable instructions you give Claude, so it follows your way of doing things. For a refresher on the basics, read this guide.

Each skill is credited with a link to its creator at the end. If you find one useful, consider supporting them by subscribing to their newsletter :)

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The Best Claude Skills We Built

There are many skills out there. Here are the best we built

Almost all the skills listed can be used with Claude Cowork. I'll flag the few that don't.

For writers & content creators

1) Instagram post downloader

Problem:
You see a great Instagram post, a carousel of slides, or an image you want to keep. Instagram doesn’t have a download button, so you come up with a workaround: screenshot, swipe, screenshot again, crop each one, rename them, drop them in a folder. By slide six, you’ve lost interest. Screenshots aren’t the real image anyway (they’re a lossy copy)

The Skill:
You hand it an Instagram post URL. It opens the post, figures out whether it’s a single image or a carousel, pulls the actual high-resolution files straight from Instagram’s site, and saves them into a tidy-named folder based on the caption. For carousels, it also stitches every slide into a single PDF so you can scroll through the whole thing in one place.

Why it works:
There are sites that download an Instagram image if you paste a link, but you have to feed them one URL at a time and click download through every slide of a carousel yourself. Do that every day or every week and it turns into a small, stressful chore. This skill skips all of it: you drop in multiple links at once, press enter, and walk away. As a bonus, I’m also sharing a skill for downloading reels using a third-party site.

Download the skills: image & carousels, reels

This skill was created by me (Frank) and from Write, Prompt, Scale

Note: If the skill doesn’t work, add *.cdninstagram.com to domain allowlist: Settings → Capabilities → Domain allowlist → Paste *.cdninstagram.com → Add

2) AEO-Optimization

Problem:

You write a great Substack post. Google might rank it eventually. But ChatGPT, Perplexity, and Claude will never quote it. Why? Because the structure they need to extract answers, short capsules, question headings, no links inside the answer, is the opposite of how most of us write. So the article works for humans scrolling, and disappears the moment someone asks an AI the same question your post answers.

The Skill:

You give it a draft (or a published post). It rewrites your H2s as the actual questions people ask AI (”What is X?”, “How do you Y?”), drops a 50-80 word answer capsule right under each one with zero links inside, and audits the rest, paragraph length, original data signals, named frameworks. You get back an AEO-ready version that’s still your article, just structured so AI can quote it cleanly.

Why it works:

AI engines don’t read articles end-to-end. They scan for extractable, link-free chunks that directly answer a query. Most writers bury the answer in paragraph three and stuff the first two with links. This skill flips that, the answer comes first, clean, in the exact word count AI prefers. You stop competing for Google rankings alone and start being the source AI cites when someone asks.

Link: Download the skill

This skill was created by from LearnAIwithMe

3) Create Thumbnails for Articles (Claude Code)

Problem:

Creating newsletter thumbnails can be time-consuming if you’re generating image candidates one at a time from the Gemini web interface. Gems can eliminate the need to keep attaching images and pasting prompts, but the overall experience feels slow to me. I wanted a way to quickly generate multiple brand-appropriate images with Gemini models from Claude Code where I do most of my work.

The Skill:

You paste in your article copy or a link and ask Claude Code to give you a few thumbnail options. It will suggest compositions informed by your copy and your brand specs, build an image prompt based on your selections, use a script to call Gemini, and evaluate the completed images through its Computer Vision. You can work on other tasks while the images are processed.

Why it works:

It allows Claude to act as an image-generation agent that has access to your brand’s reference images. While I know many people prefer evolving images one step at a time, I find it easier to get three or four candidates all at once. A lot of the time, I get lucky and just pick one. I also find that Claude does a better job with image prompts than I do.

I turned my Skill into a template you can use with Claude Code. It requires a Gemini AI Studio API key and a small script for calling Gemini. You can get the Skill and everything you need to install it on GitHub.

Here’s an image sample.

Link: Download the skill

This skill was created by from Wondering About AI

4) Substack Notes Scraper

Problem:

You write notes on Substack and want to know which ones actually landed — likes, comments, restacks, all of it in one place. Substack doesn’t give you that view. So you end up scrolling your own notes page, copying numbers into a spreadsheet by hand, screenshotting the good ones, and trying to remember which post said what. Do it once and it’s annoying. Do it monthly to track what’s working, and it eats half a morning every time.

The Skill:

You give it three things: the notes URL, the author name, and the period you care about (a month, a date range, whatever). It opens the page, scrolls until it has loaded every note from that window, pulls each one’s date, text, likes, comments, restacks, and link, and hands you back a clean .xlsx with frozen headers, filters, and proper formatting. Ready to sort, filter, or paste into a report.

Why it works:

Substack Notes has no public API, so the only honest way to get the data is from the rendered page. Doing that by hand is exactly the kind of repetitive task that gets skipped. This skill does the scrolling, the filtering (so restacks from other authors don’t pollute your data), and the formatting in one go. You ask once and get a spreadsheet you can actually work with.

Here’s a dataset I generated after running the skill.

Link: Read the guide | Download the skill

This skill was created by me! Consider becoming a paid subscriber for more :)

Subscribe now

5) Notes Humanizer

Problem:

You can spot AI writing from a mile away. Em dashes everywhere, “let’s dive in” openers, rule-of-three lists, every sentence the same length. Asking the model to “sound more natural” just makes a slightly different version of the same generic text. So you end up rewriting it yourself, sentence by sentence.

The Skill:

You paste in any AI-generated text. It runs through the full list of patterns that mark text as machine-written and strips them out. Then it adds the things models don’t do well on their own: opinion, varied rhythm, a specific detail, an aside. You get back text that reads like a person wrote it.

Why it works:

Most “humanize” prompts just tell the model to write less formally. That doesn’t help. The AI patterns are statistical defaults, the most common phrasing the model has seen in its training data from WriteStack.

Link: Download the skill

This skill was created by from TheIndiepreneur

Want to grow on Substack? Orel built WriteStack to make life easier for Substack writers. It handles Notes scheduling, performance analytics, and content generation in one place (quick note: that link’s an affiliate one, so I’ll earn a small commission if you decide to give it a try)

Skills for Making Better Decisions & Research

6) The Sycophancy Skill

Problem:

The default version of Claude wants you to feel right. You bring it a decision, it finds three reasons your instinct is solid, and you leave more confident than when you started. That’s not a thinking partner. That’s a mirror with better grammar. The longer you use it that way, the harder it gets to catch your own blind spots, and the cost doesn’t show up until a decision you can’t take back.

The Skill:

You paste a prompt that flips Claude’s default. Instead of starting with agreement, it starts with the assumption you haven’t tested. It argues the strongest case against your idea before it considers yours. It doesn’t retreat when you push back unless you give it new evidence. It tells you what’s weakest first, not what’s working. And if it can’t find a real flaw, it tells you that too, instead of inventing one to seem thorough.

Why it works:

Most skill prompts tell Claude what to add. This one tells Claude what to stop being by default. The prohibitions do more work than the rules. Without them, Claude follows the framework and then reverts to “great question” energy anyway. The prohibitions shut that off at the source.

Default Claude:

Sycophancy Skill Claude on:

Link: Read the guide

This skill was created by from Leadership in Change

7) Last 30 Days

Problem:

You hear about a new AI tool or trend and want to know what’s actually going on with it. Is it as good as people say? What are the real complaints? Googling it gives you SEO-stuffed “best of” lists and PR fluff from last quarter. The honest takes live on Reddit threads, X, etc. Chasing them across platforms eats your afternoon.

The Skill:

You activate it and name a topic. A tool, a trend, a feature, whatever. It searches Reddit, X, and the web for anything from the past 30 days. Then it hands you back a single report: what people agree on, where they disagree, and the pain points that keep coming up.

Why it works:

Most “research” is just one Google search dressed up. This one looks where the real opinions actually live. And when something shows up on multiple platforms at once, that’s your strongest signal it’s true. You save the afternoon and walk away with a much sharper picture.

Link: Watch the tutorial | Download the skill

8) Notebook LM Connector

Problem:

Notebook LM is one of the best AI tools out there, but it doesn’t talk to your other tools. So every time you want a new mindmap, audio overview, or slide deck, you’re back inside Notebook LM clicking the same buttons. There are open-source workarounds, but most of them need Claude Code and the terminal (not exactly beginner-friendly).

The Skill:

You install it inside Claude (no coding, no terminal). Then you just tell Claude what to do: “create a notebook, add these links as sources, generate a mindmap.” Claude goes into NotebookLM and does it for you. It runs through the Claude Chrome extension.

Why it works:

Notebook LM has the outputs (audio overviews, slide decks, infographics, mindmaps). Claude has the automation. Connect the two and you get NotebookLM on autopilot.

Link: Watch the tutorial | Download the skill

Subscribe now

Skills for Busy Professionals

9) Email tasks

Problem:

A lot of us (at least I am) are drowning in emails. Newsletters, news, etc. I wanted to have something that I can launch from my phone in Claude and that will help me save time and only read the emails that matter.

The Skill:

This skill is connected to my Gmail (connector). I type /emails-tasks and it reads my inbox for the last 8 hours (or whatever window I want to be set). It throws out everything that doesn’t need me, things like receipts, notifications, etc. Then, it surfaces only what requires a reply or a decision. For each one: who it’s from, what they actually need, how urgent it is, and a one-line opener if there’s a need for one.

Why it works:

Claude sorts the emails perfectly now. The best part about this skill - I can launch it straight from Dispatch from my phone. So now I am just seeing the most important emails and if I need to take any action or not.

Link: Download the skill

This skill was created by from Prosper

10) Morning intelligence

Problem:

You want to stay on top of news that matters to your work. Cowork Scheduled Tasks and Claude Code Routines now run recurring tasks on a schedule. The bottleneck is the prompt. A good one has to capture who you are, what you track, what to exclude, your sources, your geography, your format. Writing it from scratch is hard. Tuning it every time your focus shifts is harder.

The Skill:

A 15-question interview that captures your role, focus, story-type mix, exclusions, freshness, and format. It clusters your answers into pillars and writes a master prompt ready to paste into a Cowork Scheduled Task or Claude Code Routine. When priorities shift, run it again for a fresh prompt.

Why it works:

Design once, run forever. Drop the prompt into Cowork (Scheduled Tasks → New Task, requires Pro/Max with the desktop open) or Claude Code (Routines → New routine → Remote runs in the cloud without your laptop on). Either path turns a one-time prompt into a brief that arrives on its own.
Pro tip: Run the interview with Opus.

Link: Download the skill

This skill was created by from Cash&Cache

For building with Claude Code

These are skills I found on the Nate Herk YouTube channel. They’re highly recommended for Claude Code users.

11) Context Mode

Problem:

Use Claude Code for a while and you’ll notice this: Things get sluggish, it forgets what file you were editing, it asks what you wanted to do (again). What’s happening is every command Claude runs dumps a pile of raw output into its memory. After about 30 minutes, most of that memory is junk. Claude has to reset to keep going. And when it does, it forgets where you were.

The Skill:

It does two things. First, it filters the junk before it ever reaches Claude’s memory. Only the useful part of each command makes it through. Second, it keeps a running log of your session (files edited, tasks in progress, your last prompt). When Claude resets, it pulls that log back in and picks up exactly where you left off.

Why it works:

Most “long sessions” with Claude Code aren’t really long. They’re a bunch of short ones glued together with you re-explaining yourself. This kills both problems at once: less garbage going in, full memory of what you’ve done. Sessions that used to die at the 30-minute mark now run for hours.

Link: Watch the tutorial (installation steps in the description)

12) Superpowers

Problem:

You ask Claude Code to build something. It sprints out of the gate, writes the whole thing in one shot, and on the surface it looks great. Then you actually run it. Or worse, your client runs it. And it falls apart. Why? Claude doesn’t plan. It doesn’t test. It doesn’t double-check its own work. It just writes.

The Skill:

It forces Claude to work like a senior developer. Step back and plan the whole thing first. Work in an isolated environment so nothing breaks your main project. Write tests before writing code. Then review its own work twice. Once for “does this match what I asked for” and once for code quality.

Why it works:

Most failures with Claude Code aren’t from Claude being dumb. They’re from Claude rushing. Slowing it down just enough to actually think gets your first pass to 80% instead of 60%. That means fewer debugging cycles, lower token costs, and code that doesn’t fall apart the second a real person uses it.

Link: Watch the tutorial (installation steps in the description)

Bonus: has a Claude Code skill that reviews your configuration against the latest Claude Code documentation and recommends improvements. Check it out here.

How to install the skills in Cowork

Follow the steps below when you want to add one skill to Claude (.zip or skill.md file)

Customize → Skills → “+” → Create skill → Upload a skill → Upload your .zip or skill.md file

How to build your own skill in Cowork

On paper, creating a skill is as simple as describing to Claude what skill you want to build.

<your instructions in plain English>

When creating a skill, you should get a skill.md or zip file at the end of the response.

You can either download it and then upload the file using the steps above, or click on “save skill“ (for the latest Cowork versions)

In real-world projects, building a Claude skill takes a lot of trial and error.

Here’s how I decide when to turn a task into a skill and the steps I follow to build skills for my projects.

When to create a skill

• Look for tasks you do repeatedly and are time-consuming (those are your best skill candidates)

• Tasks that follow a clear, repeatable step pattern are even better candidates

• One-off tasks aren’t worth skillifying. The value comes from reuse.

How to build a Claude skill

1. Start the task in Claude Cowork as you normally would, and ask Claude to do it end-to-end.

2. If your task is complex, break it into the smallest meaningful parts and test each one independently with Claude.

3. For each part, set a goal (output, action, etc) and describe it to Claude in plain English

4. After some back-and-forth, Claude will get your task right. At that moment, type something like this: “based on everything we learned in this session, create a skill called XYZ“

5. Save the skill and test it in a new chat. If it doesn’t work as expected, just tell Claude to fix the issue and reupload the skill

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What’s your favorite skill? Let me know in the comments.

If you found this guide useful, share it with others!

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One group is saving 5 minutes on emails.
Others are running systems that work while they sleep.

The good news? You can climb faster than you think.

Last year, I wrote about how to go from AI beginner to pro. Here’s the updated framework for 2026:

• Stage 1: The AI beginner

• Stage 2: The prompt crafter (where most people are)

• Stage 3: The AI literate

• Stage 4: The workflow builder

• Stage 5: The system builder

What stage are you at? I’ll leave links to resources for each stage.

Subscribe now

Stage 1: The AI beginner

This is where everyone starts.

You have a ChatGPT, Gemini, or Claude account. You use it like a fancier Google. You ask one-off questions, maybe write a quick email, generate images, and that’s it.

It’s useful, but it doesn’t feel like a superpower yet (we’ll get there).

The first move at this stage is picking your tools.

AI tools split into two categories:

• General-purpose tools: Tools that can handle multiple tasks (text, image, etc.)

• Task-specific tools: Tools designed for one specific task

For absolute beginners, there isn’t a big difference between ChatGPT, Gemini, and Claude. Still, here are some things to keep in mind:

• ChatGPT: It has a rich feature set (voice/video mode, image generation, etc.)

• Gemini: Similar to ChatGPT + integration with Google products (Docs, Sheets, etc.)

• Claude: Excels at writing, automation, and building tools/apps (no image/video generation)

If you’re a beginner, stick to one for a few weeks to learn how it thinks.

For task-specific tools, follow these steps:

1. Identify your needs

2. Find what tools can cover those needs

3. Compare them and learn to use the winner

My current stack: Claude, Cowork, and Claude Code for serious work, NotebookLM for learning, and ChatGPT for voice mode

Your stack doesn’t have to look like mine. Build your own based on what you actually do.

📚 The best AI tools

📚 ChatGPT vs Claude vs Gemini

Note: If you plan to level up to the final stage of this list, the best choice right now is probably Claude because it includes Cowork and Claude Code in its subscription.

Stage 2: The prompt crafter

When it comes to AI chatbots, how you ask is as important as what you ask.

At this level, you should know this basic prompt structure:

• Instruction: what you want

• Context: background the AI needs to know

• Constraints: length, tone, format

• Example: when possible, show what “good” looks like

Or this more robust prompt formula shared by Anthropic:

You’ll rarely need to use all the elements of the formula, but it’s good to know they exist.

At this level, you also know a few prompt-improvement tricks. For example, when you finally land on a great answer after a long back-and-forth, you ask the AI to write the prompt that would have gotten you there on the first try.

📚 Prompt Formula

📚 Prompt Principles

Who needs to go beyond stage 2?

Stage 2 was enough in 2023.

Things have changed a lot in 2026. There’s nothing wrong with being in stage 1 or 2 if you’re a casual user who proofreads emails, generates images once in a while, etc.

However, if you want to master AI, you need more.

That’s what we’ll cover in the next stages:

• Stage 3: Develop AI literacy & use it as a thinking partner

• Stage 4: Build AI workflows for the work you keep doing

• Stage 5: Build AI systems that run while you sleep

Stages 3, 4, and 5 aren’t for casual AI users, but for professionals, builders, and business leaders who want to turn AI into a real competitive advantage.

If you’re in that group, keep reading 👇

Paid-members only :) Each stage comes with resources to help you get there

Subscribe now

Read more

Ask → Read → Copy → Rebuild somewhere else

That workflow made sense when Claude was just a text generator. But it’s starting to fall short.

Claude can now create three types of outputs:

1. Charts: Helps you explore data, ideas, or processes visually, right inside the chat.

2. Artifact: Builds something you can actually use (a tool, page, dashboard, etc).

3. Live artifact: An artifact that connects to external data sources and refreshes with real-time data every time it's opened.

Each one shows up in a different place: Charts stay in the chat, Artifacts open in a separate panel, and Live Artifacts live inside Claude Cowork.

In this guide, you’ll learn how to make the most out of them.

Consider becoming a paid subscriber to get full access to my Claude course, workflows, video courses and more 👇

Subscribe now

1) Charts & widgets

Charts and widgets are useful when you need to see data, ideas, or processes clearly. You don’t need an external tool. Just ask Claude to turn the information into a visualization.

Quick steps:

1. Open Claude

2. Go to Settings → Capabilities → Visuals → Turn on Inline visualizations

3. Here's a base prompt you can start from:

Create an interactive chart from this data.

Make it explorable, not just static.

Include:
- hover details
- highlighted insights
- clear labels
- a short explanation of what the chart shows

If useful, add filters or toggles so I can compare different views.

Let's look at some examples.

Example 1: Newsletter funnel

Create an interactive funnel chart from this data.

Data:
- Impressions: 50,000
- Profile visits: 8,000
- Clicks: 2,400
- Subscribers: 620

Make it explorable, not just static.

Include:
- hover details for each stage
- conversion rate between stages
- total drop-off between stages
- a highlighted insight for the biggest drop-off
- clear labels
- a short explanation of what the chart shows

Example 2: Content performance chart

Create an interactive chart from this data.

Data:
- LinkedIn post: 18,000 views, 760 clicks, 120 subscribers
- Substack article: 7,500 views, 980 clicks, 210 subscribers
- X thread: 12,000 views, 430 clicks, 80 subscribers
- YouTube short: 25,000 views, 510 clicks, 95 subscribers
- Carousel: 9,800 views, 690 clicks, 150 subscribers

Make it explorable, not just static.

Include:
- hover details for each content format
- highlighted insights for the best format by metric
- clear labels
- a short explanation of what the chart shows
- toggles to compare views, clicks, and subscribers

The toggle is what makes it interactive. Without it, you get a static image you can only look at.

Example 3: Claude tools map

Create an interactive visual comparison between:

- Claude Chat
- Projects
- Artifacts
- Cowork
- Claude Code

Show when each one should be used.

Make it interactive.

Include:
- clickable cards for each tool
- best use case
- example prompt
- difficulty level
- when not to use it

Asking for clickable cards is what makes it interactive. Without that, Claude might give you a flat comparison table.

Example 4: Workflow bottleneck chart

Create an interactive chart from this workflow data.

Data:
- Ideas: 40
- Outlines: 18
- Drafts: 9
- Edited articles: 5
- Published articles: 3

Make it explorable, not just static.

Include:
- hover details for each stage
- conversion rate between stages
- drop-off between stages
- highlighted insight for the biggest bottleneck
- clear labels
- a short explanation of what the chart shows
- a recommendation for what to improve first

Example 5: Article process diagram

Create an interactive process diagram that explains how an article moves from idea to published post.

Stages:
- idea
- research
- outline
- draft
- editing
- visuals
- publishing

Make each stage clickable.

For each stage, show:
- goal
- main task
- common mistake
- useful Claude prompt

The key phrase is "Make each stage clickable." Without it, Claude might give you a flat diagram with no interaction.

2) Artifacts

An artifact helps you build something. It shows up in a separate panel.

Quick steps:

1. Open Claude

2. Go to Settings → Capabilities → Visuals → Turn on Artifacts and AI-powered artifacts

3. Here's a base prompt you can start from:

Build an interactive [tool/dashboard/page/calculator] for [use case].

It should include [elements].

Make it clean, simple, and easy to use.

Build this as an interactive artifact.
Make it usable, not just explanatory.

Example 1: Content pipeline dashboard

Build an interactive dashboard for a content pipeline.

Use this sample data:
- 12 ideas
- 5 outlines
- 3 drafts
- 2 articles in review
- 4 scheduled posts
- 18 published posts

It should include:
- summary cards
- filters by platform, status, and priority
- a table view
- a simple progress overview
- next action for each item

Make it clean, simple, and easy to use.

Build this as an interactive Artifact.
Make it usable, not just explanatory.

Example 2: Article effort calculator

Build an interactive calculator for estimating article production effort.

Use this case:
- Article type: long-form guide
- Research time: 3 hours
- Writing time: 4 hours
- Editing time: 2 hours
- Visuals: 3 visuals
- Publishing format: Substack + LinkedIn repurpose

It should include:
- editable inputs
- total estimated hours
- difficulty level
- recommendation
- warning if the workload is too high for one day

Make it clean, simple, and easy to use.

Build this as an interactive Artifact.
Make it usable, not just explanatory.

Example 3: Interactive learning guide

Build an interactive guide based on this article:

[PASTE ARTICLE LINK]

It should include:
- main idea
- step-by-step workflow
- visual map
- copy-ready prompts
- examples
- common mistakes
- checklist
- suggested next action

Make it clean, simple, and easy to use.

Build this as an interactive Artifact.
Make it usable, not just explanatory.

"Make it usable, not just explanatory" is the phrase that does the heavy lifting. Without it, Claude might just summarize the article.

Example 4: AI tools comparison dashboard

Build an interactive comparison dashboard for AI tools.

Compare:
- Claude Chat
- Claude Projects
- Artifacts
- Cowork
- Claude Code

It should include:
- best use case
- difficulty level
- example prompt
- when not to use it
- recommended user type
- decision filter by goal

Use some understated emoticons, as well as the company logo and all the branding elements.

Make it clean, simple, and easy to use.

Build this as an interactive Artifact.
Make it usable, not just explanatory.

Subscribe now

3) Live Artifacts

A live artifact is useful when you need a dashboard, tracker, or workspace you can return to. Claude builds it once, and then you keep reviewing, updating, and reusing it inside Claude Cowork.

Quick steps:

1. Open Claude Desktop → Cowork

2. Select “Live artifacts“

3. Create or open an Artifact

4. Here's a base prompt you can start from:

Create a live [tracker/monitor/dashboard/workspace] inside Claude Cowork.

Use this context:
- [source 1]
- [source 2]
- [source 3]

It should track:
- [field 1]
- [field 2]
- [field 3]
- [field 4]

Make it useful from the first version.

Include sample data, current entries, or imported items when possible.

Show what changed.
Show what needs attention.
Highlight blockers, opportunities, or next actions.

Example 1: Live content operating system

Create a live AI video radar inside Claude Cowork.

Goal:
Track recent YouTube videos about AI, Claude, Claude Code, AI productivity, and workflow automation.

Use official or authorized sources when possible, such as:
- YouTube Data API
- channel RSS feeds
- exported CSV files
- manually pasted video links

Track:
- video title
- channel
- publish date
- views
- likes
- comment count
- duration
- topic category
- why it matters
- possible article angle
- possible LinkedIn post idea
- possible X post idea
- next action

Start with these search topics:
- Claude Code
- Claude Artifacts
- Claude Cowork
- AI productivity
- AI agents
- prompt engineering

Make it easy to refresh weekly.

Highlight:
- videos growing fast
- repeated topics across channels
- content gaps I could write about
- videos worth watching first

To make it work better: Ask for authorized sources: the YouTube Data API, exported CSV files, or manually pasted links. Direct scraping is less stable and might break.

Example 2: Live content ecosystem monitor

Create a live content ecosystem monitor inside Claude Cowork.

Use these sources as context:
- Substack: [PASTE SUBSTACK LINK]
- X profile: [PASTE X LINK]
- Medium: [PASTE MEDIUM LINK]
- LinkedIn: [PASTE LINKEDIN LINK]

Track:
- platform
- content title or post idea
- topic
- format
- target audience
- reusable example
- reusable prompt
- repurposing opportunity
- suggested next action
- status

Organize the workspace into:
- published content
- ideas to repurpose
- examples worth reusing
- prompts worth saving
- next content actions

Make it useful from the first version.

If Claude cannot access a source directly, create the structure and ask me to paste examples or exports.

Example 3: Live Skills Library and Skill Router

Create a live Skills Library and Skill Router inside Claude Cowork.

Before building, check whether you can access the Skills available in this Cowork Project.

If you can access them:

- show me the Skills you found
- group them by source or plugin
- ask me to confirm before building

If you cannot access them:
- ask me to paste or upload the Skills list

Do not use Gmail.
Do not use email.
Do not use Calendar.
Do not use external connectors.
Do not create an inbox dashboard.
Do not switch the use case.

After I confirm, build the Live Artifact with two modes:

Mode 1: Skills Library
Track:
- Skill name
- Source/plugin
- Category
- Main purpose
- When to use it
- Required inputs
- Expected output
- Example prompt
- Related workflows
- Last updated
- Status
- Improvement ideas

Mode 2: Skill Router
The user describes a task.
Then recommend:
- best Skill
- alternative Skill if relevant
- why it fits
- what input I should provide
- copy-ready prompt
- missing context needed

Also include:
- search
- filters by category, source/plugin, and status
- a section for duplicated or overlapping Skills
- a section for Skills missing examples
- a section for Skills that should become templates

For Last updated, use “Unknown” if there is no metadata.
For Status, use:
- Active by default
- Needs review if the Skill has weak instructions, missing examples, unclear inputs, or overlaps with another Skill

The library with filters and the Skill Router are what make this actually useful. Without them, you'd just have a list of Skills with no way to know which one to use and what input to provide.

Subscribe now

Click here to get my FREE Claude course (20+ lessons)

Most AI tools chat. Cowork acts.

You point Cowork at your inbox or your files, give it a clear job, and it goes and does it: scans, extracts, saves the result, etc.

No copy-paste. No tab juggling.

But that "give it a clear job" part is where most people lose.

They open Cowork, type something vague, and get back a half-baked answer and stop there.

That's the mistake. Cowork is built for iteration. You have to co-work with it: feedback, tweak, repeat — until the output is exactly what you need. Then you ask Cowork to rewrite your original prompt so the workflow runs cleanly next time.

That’s what Ilia and I did.

We automated boring, repetitive tasks with Cowork. After a lot of trial and error, we landed on 7 prompts that many of you will find useful.

In this guide, you’ll get prompts to automate:

1. Freelance Invoice Tracker

2. Vendor Comparison Table

3. Travel Itinerary Builder

4. Meeting Transcript → Action Items

5. Subscription Tracker

6. Job Application Tracker

7. Organize Downloads Folder

This guide was written in collaboration with Ilia Karelin.

Ilia writes Prosper, a newsletter focused on practical AI workflows, systems, and frameworks for professionals who want to use AI more thoughtfully.

Prosper

Every week, practical AI workflows, prompts, and guides you can put to use the same day - no matter your technical background.

By Ilia Karelin

How to Use These Prompts

• Step 1: Copy the prompt

• Step 2: Open Claude Cowork

• Step 3: Paste and run

• Step 4: Grant permissions when asked

That’s it. No configuration. No learning curve.

Each prompt is designed to work out of the box. Customize the [BRACKETS] for your situation.

Note: You can schedule any of the tasks below to run automatically. Check the guide below to learn how:

📚 Claude scheduled tasks

P.S. For more collabs like this, consider becoming a paid subscriber 👇

Subscribe now

1. Freelance Invoice Tracker

You invoiced someone. You forgot when. You’re not sure if they paid. This prompt scans your inbox and local files and builds a full payment status tracker in one run.

What it does:

- Scans Gmail and local folders for every invoice sent

- Flags unpaid and overdue invoices

- Calculates total outstanding at the top

- Saves a tracker you can reference any time

The prompt:

Scan my emails and local files to track all freelance invoices and payment status.

GMAIL FILTER:

- Search for emails containing: invoice, payment, due, overdue, receipt
- Date range: [Last 30 days / Last 90 days / This year]

LOCAL FOLDER TO SCAN (optional):

- [path to invoices folder, e.g., ~/Documents/Invoices]
- File types: .pdf, .docx, .xlsx, .csv

FOR EACH INVOICE FOUND, EXTRACT:

- Client name
- Invoice number (if available)
- Amount
- Date sent
- Due date (if mentioned)
- Payment status: Paid / Unpaid / Overdue / Unknown

BUILD A TRACKER TABLE:

- All invoices sorted by due date (oldest first)
- Status: OVERDUE / DUE SOON / PAID
- Total outstanding amount at the top
- Total paid this period

SUMMARY AT THE TOP:

- Total invoiced: $[X]
- Total paid: $[X]
- Total outstanding: $[X]
- Number of overdue invoices

OUTPUT: Save as [invoices-tracker-YYYY-MM].md in [YOUR FOLDER PATH]

Pro tip: Run this at the start of every month. The overdue column tells you exactly who to follow up with before chasing anything manually.

Want this as a live artifact instead? Replace the last line of the prompt with:

OUTPUT: Build this as a live artifact. 
Every time it’s reopened, re-scan Gmail and the local folder and refresh all numbers. 
Do not cache the previous state.

And this is what you can get:

The difference: the file version is a snapshot you have to re-run. The live artifact stays connected to Gmail, so every time you open it, it re-scans your inbox and updates totals and statuses automatically. New invoice sent, payment received, due date passed, it reflects all of it without touching the prompt again. And if you want to refresh mid-session, hit the Reload button in the top right corner of the artifact, it re-scans Gmail on demand and updates everything instantly.

2. Vendor Comparison Table

You’re evaluating tools. You have 10 tabs open. You still haven’t decided. This prompt researches every option and produces a structured comparison table with a clear recommendation.

What it does:

- Researches each vendor’s pricing, features, and limitations

- Pulls user sentiment from G2, Capterra, and Reddit

- Builds a scored comparison table

- Gives a direct recommendation for your use case

The prompt:

I’m evaluating tools/services and need a structured comparison to make a decision.

VENDORS TO COMPARE:

1. [Vendor 1]
2. [Vendor 2]
3. [Vendor 3]

WHAT I’M TRYING TO DO:

[Describe your use case in one sentence]

MY BUDGET: [Monthly or annual budget range]

TEAM SIZE: [Just me / Small team 2-10 / Medium team 10-50]

FOR EACH VENDOR, RESEARCH AND FILL IN:

## Pricing

- Free tier: yes/no, what’s included
- Paid plans: price per seat or flat rate
- Annual vs monthly discount
- Hidden costs (storage limits, API calls, add-ons)

## Core Features

- Does it handle [YOUR PRIMARY USE CASE]?
- Top 3 things it does well
- Top 2 limitations

## Integrations

- Connects to [YOUR KEY TOOLS]?
- Native vs. Zapier/Make required

## User Sentiment

- X / Capterra / Reddit consensus
- Most common complaint
- Most common praise

BUILD A COMPARISON TABLE:

- Rows: each vendor
- Columns: pricing, core fit, integrations, support, overall score (1-10)

RECOMMENDATION:

- Best overall for my use case
- Best budget option
- One to avoid and why

OUTPUT: Save as [topic]-vendor-comparison.md in [YOUR FOLDER PATH]

Here’s the end result:

And then it gave the best options for your and which one to avoid as well:

Pro tip: Add “MY CURRENT TOOL: [name]” to the prompt if you’re switching. Cowork will include a migration difficulty rating for each alternative.

3. Travel Itinerary Builder

Your trip confirmations are scattered across 12 emails. This prompt finds all of them and assembles a single chronological itinerary with every confirmation number, address, and time in one place.

What it does:

- Scans Gmail for flight, hotel, and booking confirmation emails

- Extracts times, addresses, and confirmation numbers

- Builds a day-by-day itinerary in order

- Flags gaps and anything missing a confirmation number

The prompt:

Scan my inbox for all travel-related emails and build a complete trip itinerary.

GMAIL FILTER:

- Search for: flight confirmation, hotel booking, reservation, booking confirmation, check-in, itinerary
- Date range: emails from [TODAY] to [TRIP END DATE]
- Focus on trip to: [DESTINATION]

FOR EACH TRAVEL ELEMENT FOUND, EXTRACT:

FLIGHTS:

- Airline and flight number
- Departure: airport, terminal, date, time
- Arrival: airport, terminal, date, time
- Booking reference and seat number

ACCOMMODATION:

- Hotel/Airbnb name and address
- Check-in and check-out date and time
- Confirmation number
- Any notes (parking, early check-in, etc.)

OTHER BOOKINGS:

- Car rentals, trains, tours, restaurants
- Date, time, confirmation number, address

BUILD THE ITINERARY:

- Organized chronologically by day
- Each day: date as header, all events in time order
- Each event: time | what | address | confirmation number
- Flag any gaps (e.g., arriving at 11pm but hotel check-in closes at 10pm)
- Flag anything missing a confirmation number

SUMMARY AT THE TOP:

- Trip dates
- Destination(s)
- Total flights / nights / bookings

OUTPUT: Save as [destination]-[dates]-itinerary.md in [YOUR FOLDER PATH]

Here’s the end result:

Pro tip: Run this 48 hours before departure, not the morning of. The gap-flagging is where it earns its keep, a missed check-in window is easy to fix with two days to spare.

4. Meeting Transcript → Action Items

The call ended. Everyone said “I’ll follow up.” Nobody followed up. This prompt reads any transcript or notes file and returns every decision, action item, and open question, plus a ready-to-send follow-up email.

What it does:

- Reads any transcript or meeting notes file from a local folder

- Extracts decisions made, action items with owners, and open questions

- Writes a follow-up email ready to send with zero edits

- Flags anything assigned to no one

The prompt:

I have a meeting transcript or notes file. Extract everything actionable and structured.

FOLDER TO SEARCH: [Downloads / Desktop / specify path]

FILE NAME (or partial match): [e.g., “meeting”, “call”, date, or topic]

FILE TYPE: [.txt / .pdf / .docx / .md / .vtt]

MEETING CONTEXT:

- Meeting type: [Team standup / Client call / Strategy session / 1:1 / Other]
- Attendees (if known): [Names or roles]
- Date of meeting: [DATE]

ONCE YOU FIND THE FILE, EXTRACT:

## 1. Decisions Made

- Every decision that was reached (not discussed — decided)
- Format: Decision | Owner | Effective date

## 2. Action Items

- Every task, commitment, or next step mentioned
- Format: Task | Owner | Deadline | Priority (High/Medium/Low)
- Flag as [UNASSIGNED] if no owner named
- Flag as [NO DATE] if no deadline mentioned

## 3. Open Questions

- Everything raised but not resolved
- Format: Question | Who raised it | Who should answer it

## 4. Key Discussion Points

- 3-5 bullet summary of what was actually discussed

## 5. Follow-Up Email Draft

Subject line included. Ready to send. Covers:

- Decisions made
- Action items with owners and deadlines
- Open questions with responsible parties

OUTPUT: Save as [meeting-topic]-[date]-actions.md in the same folder as the source file.

Pro tip: Works on Zoom transcripts, Otter exports, Google Meet notes, or even a rough .txt you typed during the call. Format doesn’t matter, the structure comes from the prompt.

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5. Subscription tracker

Every month, we sign up for a new service: a gym membership, a streaming platform, or a Substack subscription to make the most out of AI … like this one :)

The subscriptions pile up, and after a while, it gets really hard to keep track of them all. We end up paying for things we don’t even use anymore.

For example, I had a €5/month Glovo Premium subscription for free delivery. When I started cooking at home, I forgot to cancel it — and only realized seven months later when I checked my bank statements. The skill below fixes this problem.

What this skill does:

• You create a folder and save all your bank statements inside it. Create a folder for each bank and make sure the files have the month of the statement.

• Run the prompt below. Claude builds a dashboard of your active subscriptions, sorted by category, with a card for each one showing the name, average amount, frequency, and which account it’s charged to.

• It also generates a spreadsheet in the same folder with three tables:

  • Active subscriptions — amount, currency, frequency, and account.

  • Cancelled subscriptions.

  • Monthly savings — how much you saved by cancelling the unused ones.

# Subscription tracker

Read all bank statements in my folder (any format — CSV, XLS, XLSX, PDF). Identify every recurring subscription or membership by finding charges that repeat across 2+ months with a consistent amount or merchant name.

## What to include

- Subscriptions (software, streaming, SaaS)
- Memberships (gym, coworking, clubs)
- Insurance, telecom, donations
- Any other fixed recurring charge

## What to exclude

- One-off purchases
- Groceries, dining, retail shopping
- Bank fees and currency conversion charges

## Output 1 — Visual dashboard (inline widget)

- Total number of subscriptions found
- Estimated monthly cost grouped by currency
- A card for each subscription showing: name, average amount, frequency, and which account it’s charged to
- Organized by category (software/streaming, services/utilities, etc.)

## Output 2 — Spreadsheet (.xlsx) saved to my folder

- **Active subscriptions** sheet with columns: Subscription, Amount, Currency, Frequency, Account
- Totals per currency using Excel formulas
- **Canceled subscriptions** section with a Status column (leave empty if none confirmed)
- Monthly savings row for canceled items

Pro tip: Use Task Scheduler to run this at the end of every month, so you always start the new month with a clear picture of where your money’s going.

The dashboard looks like this:

and the report looks like this:

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6. Job Application Tracker

You’ve applied to 20 places. You can’t remember which ones responded. This prompt scans your inbox and builds a live dashboard of every application, sorted by how long you’ve been waiting.

What it does:

- Scans Gmail for application confirmations, interview requests, and rejections

- Assigns a status to every application

- Sorts by days since last update so nothing falls through the cracks

- Flags applications with no response after 14 days

The prompt:

Scan my inbox and build a live tracker of every job application I’ve submitted.

GMAIL FILTER:

- Search for: application received, thank you for applying, interview, next steps, unfortunately, offer
- Date range: [Last 30 days / Last 3 months / specify]

FOR EACH APPLICATION FOUND, EXTRACT:

- Company name
- Role title
- Date applied
- Current status: Applied / Acknowledged / Interview Scheduled / Interviewing / Rejected / Offer / Withdrawn
- Last email date
- Next step (if mentioned)
- Recruiter contact name (if any)

BUILD A LIVE DASHBOARD:

- One row per application
- Columns: Company | Role | Date Applied | Status | Days Since Last Update | Next Step
- Sort by: Days Since Last Update (longest first)
- Status colors: green = active/interviewing, amber = applied/waiting, red = rejected, blue = offer

SUMMARY AT TOP:

- Total applications
- Active (not rejected or withdrawn)
- Awaiting response >14 days — flag these
- Interviews scheduled
- Offers

OUTPUT: Live artifact. Every time it’s reopened, re-scan Gmail and refresh all statuses. 
Do not cache the previous state.

Pro tip: The “awaiting response >14 days” flag tells you exactly where to send a follow-up. Most people let those go cold without realizing it.

The end result looks awesome:

Same live behavior as the Invoice Tracker, reopening re-scans Gmail automatically, Reload button refreshes on demand.

7. Organize Downloads Folder

Every day, we download spreadsheets, images, PDFs, and all kinds of other files straight into our Downloads folder. We don’t have time to sort them into proper folders later, so as the days go by, Downloads turns into a mess. Once an important file lands in there, it basically disappears — finding it again is a pain, especially when you’re in a rush.

What this skill does:

• Creates separate folders for audio, documents, PDFs, images, videos, and datasets.

• Every time you run it, it moves each file into the right folder.

• The prompt has built-in constraints, so it will never create extra folders or delete anything in your Downloads folder.

Organize loose files in the user's selected folder (their Downloads directory) into the appropriate subfolders based on file type. 

The target folders are:

- **Audio** — move all audio files here (`.mp3`, `.m4a`, `.wav`, `.flac`, `.aac`, `.ogg`, `.wma`, `.aiff`)
- **Docs** — move all docs here (`.docx`, `.txt`, `.md`, `.rtf`, `.odt`, `.doc`)
- **PDFs** — move all `.pdf` files here
- **Images** — move all image files here (`.png`, `.jpeg`, `.jpg`, `.gif`, `.webp`, `.svg`, `.bmp`, `.tiff`, `.heic`)
- **Videos** — move all video files here (`.mp4`, `.mov`, `.avi`, `.mkv`, `.webm`)
- **Datasets** — move all data files here (`.csv`, `.tsv`, `.json`, `.parquet`, `.xlsx`, `.xls`)

## Steps

1. List all loose files (not directories) in the root of the Downloads folder.
2. For each file, check its extension and move it to the matching folder above.
3. After moving, list what was moved to each folder and note any files that were left untouched.

## Constraints

- Do **NOT** create any new folders. Only use the existing folders listed above.
- Do **NOT** move, rename, or touch any existing subfolders or their contents.
- Do **NOT** move files whose extensions don't match any of the categories above.
- Never delete any files.
- Never create new directories.
- Only operate on the root level of the Downloads folder.

Pro tip: Use Task Scheduler to run this prompt automatically at a set time each day, so your Downloads folder gets organized without you lifting a finger. I personally schedule mine to run every two days at 9 p.m., and Downloads stays tidy on its own. A couple of times a week I pop into the sorted folders and delete anything I don’t need, so they don’t balloon in size either.

Did you find one of the prompts useful? Share it with others :)

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Hi!

Today, is sharing with us the Sycophancy Skill, a Claude Cowork setup that forces Claude to disagree with you constructively before it agrees. Highly recommended for leaders and professionals who want to use Claude as a thinking partner without the frequent “you’re right“ responses.

Joel Salinas is a Fractional Chief AI Officer for small and mid-sized businesses and nonprofits, working on AI strategy, hands-on builds, and change management. He writes Leadership in Change, a newsletter for mission-driven leaders navigating the AI era, and offers 1:1 coaching for individual leaders.

I have 25+ Claude skills. Just in writing each article for Leadership in Change, I probably use 8 of them every time.

So when I see writers in this space talking about prompts you can paste into a chat to make Claude a “thinking partner,” I get it. The prompts work. The rhythm wrote about in this post recently, beginning, middle, end, is genuinely useful. I’ve used versions of it.

But there’s a layer above prompts that almost nobody is talking about, and it changes everything once you cross over. Most people use Claude skills to make Claude faster. The real shift is using skills to make Claude honest.

In this guide, you’ll learn:

• Why you need the Sycophancy Skill

• How to build this skill (copy-and-paste prompt included)

• Four before-and-after examples that show the skill in action

• A 5-step method to build any skill that fits how you actually work

Click here to get my FREE Claude course (20+ lessons)

Subscribe now

Why you need the Sycophancy Skill

Here’s the problem that genuinely frightens me… when you ask AI something, the default training behavior is to be helpful, agreeable, and confidence-boosting. That sounds fine until you remember what kind of professional that personality describes: the doctor who agrees with your self-diagnosis. You walk in already convinced of what’s wrong, you describe it, the doctor nods, writes the prescription you came in expecting, and you leave feeling validated. You’re still sick. You just feel better about it.

A doctor is not good if he or she just agrees with what you already think you have, before testing.

This is the version of “thinking partner” most leaders are getting. Sharper questions, better-framed prompts, more thoughtful counterpoints, all of it still operating inside a default that wants to make you feel right. I’ve made the case before that this is the deeper version of outsourcing your thinking, and the leaders most at risk are the ones who got value from AI fast and stopped questioning the wins.

This isn’t theoretical for me. The first few times I asked Claude something about a stat or an AI development I half-remembered, it confirmed what I had in my head. Confidently. Cleanly. I almost moved on. The only reason I caught it was that I went to verify one of those answers manually, and Claude wasn’t just wrong, it was wrong in a way that fit my framing so neatly it never tripped my filter. The model was confidently confirming what I’d already half-decided was true, and the only fix was to go look outside the chat. That’s when I started building skills to break the reflex.

Honestly, this is the most under-discussed danger in the entire AI thinking-partner conversation, and it’s especially dangerous for leaders.

Here’s the cascade I see in the leaders I work with as a fractional Chief AI Officer:

The leader who gets the most value from AI isn’t the one who finds the smartest model. It’s the one who builds in friction on purpose, and the difference between those two leaders compounds fast.

Leadership in Change

Don’t just read about AI, lead it. Get the weekly playbook for leaders who want to supercharge their expertise and multiply their impact.

By Joel Salinas

📚 If you’re completely new to Claude skills, read this guide

How to build the Sycophancy Skill

So I built one, and you can too!

Simply:

Open Claude Desktop

Start a new chat on Cowork

Paste the Prompt below… and that’s it!

You should see it begin working:

And after a couple of minutes, your skill is ready. Click SAVE SKILL.

Ready?

Use the following information to create my newest Claude Skill...
# Sycophancy Skill

You are my critical thinking partner. Your default mode is constructive disagreement.

## Behavior rules

1. Before agreeing with anything I say, identify at least one
   assumption underneath it that I have not tested. State the
   assumption plainly.

2. When I propose a decision, idea, plan, or interpretation, your
   first response is to argue the strongest opposing case. Do not
   soften it. Do not append "but you might be right." Make me
   defend my position.

3. If I push back on your counterargument, do not retreat because
   I objected. Retreat only if I produce new evidence, new
   reasoning, or a constraint I had not mentioned. Saying "fair
   point" without new information is not enough.

4. When I share work to review, identify what is weakest first,
   not what is strongest. Strengths are easier to find on my own.
   Weaknesses are why I am asking.

5. If I am clearly emotionally invested in an answer, name that
   explicitly and ask whether the emotion is signal or noise.

6. If you cannot find a real flaw, say so directly: "I have looked
   for the weakness and I cannot find one." Do not invent a flaw
   to perform thoroughness.

7. End every substantive exchange with one question I should sit
   with before I act, not a summary.

## Tone rules

- Direct, not aggressive
- Specific, not abstract
- One disagreement at a time, not a list
- Cite my own words when challenging me

## What you do not do

- Open with praise before disagreeing
- Use "great question," "interesting point," or any opener that
  reads as flattery
- Hedge with "I could be wrong but"
- Add a closing reassurance like "your instinct is good"

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Before and After the Sycophancy Skill

Here’s what that looks like in practice. Four questions, before and after the skill is on.

Question 1: Should I raise my coaching prices by 20%?

Default Claude:

Sycophancy Skill Claude on:

Default Claude opens with agreement (”You probably should”) and then asks for more information to help you think it through. The Sycophancy Skill doesn’t acknowledge the question at all. It goes straight to the thing you haven’t proven: what’s your evidence the market will bear 20% more, not your hope, your evidence.

Question 2: I’m thinking about cutting our lowest-performing program to free up resources for the one that’s working. Does that make sense?

Default Claude:

Sycophancy Skill Claude on:

Default Claude starts with agreement (”Yes, it usually does”) before adding nuance. Sycophancy Skill ignores whether cutting makes sense and goes straight to the assumption you haven’t tested: is the winning program actually resource-constrained, or does cutting just feel decisive? It reframes the question before answering it.

Question 3: I’m considering promoting my best individual contributor to team lead. She’s excellent at her work. Thoughts?

Default Claude

Sycophancy Skill Claude on:

Default Claude opens with validation (”the fact that you’re thinking carefully about it is a good sign”) and then educates you. Sycophancy Skill opens with a challenge (”being excellent at the work is the worst reason to promote someone”) and then interrogates your assumption. One makes you feel like a thoughtful leader. The other makes you prove you are one.

Same model. Same question. The skill changes which version of Claude shows up.

Two things to notice about how this is built.

First, the “What you do not do” section is doing more work than the rules. Rules tell Claude what to add. Prohibitions tell Claude what to stop being by default. Without the prohibitions, the model will follow the rules and then revert to “great question” energy on top of them, and you end up with a Claude that disagrees politely and then agrees anyway.

Second, rule #6 matters more than it looks. Without it, a skill that demands disagreement will start inventing flaws to seem rigorous. You don’t want a Claude that pushes back theatrically. You want a Claude that pushes back when there’s a real flaw and tells you the truth when there isn’t.

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How to build any skill that fits how you actually work

The Sycophancy Skill is one example. The same method builds any skill that holds context across chats. Here’s the 5-step version.

Step 1: Write the role in one sentence. “You are my critical thinking partner.” “You are my brand strategist for [business].” “You are my book recommender who knows the authors I admire.” If you can’t write the role in one sentence, the skill is too broad.

Step 2: Write the behavior rules. What does this skill do every time? Use imperatives. Number them. Aim for 4 to 7. Fewer than 4 and the skill won’t have personality. More than 7 and the model will start dropping rules.

Step 3: Write the tone rules. How should it sound? Direct, warm, terse, formal, conversational. Two or three lines is enough.

Step 4: Write the prohibitions. This is the step most people skip, and it’s the difference between a skill that works and a skill that drifts. List 3 to 5 things the skill does not do. Default model behaviors you specifically want to disable.

Step 5: Test it with a question you already know the answer to. (Try: “Is my latest project a good idea?” If Claude lists three reasons it’s great before naming a single risk, your prohibitions are too soft.) Tighten it and run it again.

That’s the whole method. The Sycophancy Skill is one application of it. Your version, for whatever you do, is 30 minutes of work and saves you that much every week from then on.

📚 I wrote about my five favorite skills in this piece

The point

A thinking partner that always agrees with you isn’t a partner at all. It’s a stenographer with a friendlier tone, and the longer you use one, the harder it gets to tell the difference between agreement and validation. The leaders who get the most out of AI in the next two years aren’t going to be the ones with the biggest tool stack. They’re going to be the ones who deliberately built friction into the stack, because frictionless agreement is the most expensive feedback you can get, and you don’t notice the cost until it shows up in a decision you can’t take back.

If you can’t remember the last time Claude told you you were wrong, you’re using it wrong. Build the skill. Run it on the next decision that matters. See what comes back.

Don’t forget to subscribe to Leadership in Change, a newsletter for mission-driven leaders navigating the AI era, and offers 1:1 coaching for individual leaders.

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Did you know?

• 33% of interviewers make a decision in the first 90 seconds.

• Around 50% of candidates use AI to prepare their applications.

• The other 50% are walking in at a disadvantage.

Most people sit down in an interview without knowing how they’ll be evaluated. That’s a big problem.

Today we’ll fix that. This guide is split into two parts:

• Part 1: How to use Claude to decode any job description, map it to your experience, and answer common questions without rambling

• Part 2: How to build a clean, ATS-friendly resume in Overleaf without fighting Word's formatting (Claude does the heavy lifting)

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Part 1: Prep for the Interview with Claude

Read more

Click here to get my FREE Claude course (20+ lessons)

Most people use NotebookLM and Claude Cowork separately.

NotebookLM to do research or get answers grounded in their documents. Cowork for building a report, infographic, dashboard, and apps without coding.

Connect them, and you get something unique. Tools built on your own data. The research layer and the build layer finally talk to each other.

Nobody does this. Everyone should.

In this guide, you’ll learn:

• How to connect NotebookLM to Claude Cowork

• Use Case 1: Turn spreadsheets into infographics your CEO will read

• Use Case 2: Build a personal language tutor app before your next trip abroad

• Use Case 3: Spy on competitor content and extract what’s working

This guide was written in collaboration with .

Gencay writes LearnAIWithMe, a newsletter focused on practical AI tutorials for people who’d rather replace than be replaced by AI.

LearnAIWithMe

If you want to build with AI, not just learn how to prompt, this is the right place.

By Gencay

What does connecting NotebookLM and Claude Cowork solve?

Two things.

One. Your data becomes the source of truth.

NotebookLM grounds every answer in the sources you upload. Every claim traces back to a citation you can click.

Cowork normally runs on training data. Useful, but can be generic. Connect it to NotebookLM and Cowork now reasons from your sources. Your internal docs or your research.

Two. Static knowledge becomes a working tool.

NotebookLM alone stays “ask and read.” You open it, type a question, read the answer, and close the tab.

Cowork turns that same knowledge into an app you operate. An artifact or infographic creator. Something you use every week, not a tab you forget.

Build once. Run forever.

How to connect NotebookLM and Claude Cowork

There is no official connector.

What works is this repo: github.com/teng-lin/notebooklm-py.

Unofficial, but powerful.

Step 1: Install NotebookLM-py

Run this prompt in Cowork:

Install this skill :https://github.com/teng-lin/notebooklm-py
I want to use it via CLI

Let it work. The progress bar shows up in the top right.

Step 2: Turn it into a Skill

Next prompt:

I want to drive this on Claude Cowork because I’ll turn it into a skill and do whatever is needed.

Cowork starts building.

Watch the progress bar on the top right, walk through the checklist.

Step 3: Auth

Cowork cannot log into Google from the sandbox.

You log in on your Mac and hand the session back.

Open your terminal.

New to the terminal?

The terminal is a simple text window where you type commands instead of clicking buttons. Do not panic, you only need it once for this setup.

On Mac: Press Cmd + Space, type Terminal, hit Enter.

On Windows: Press the Windows key, type PowerShell, hit Enter.

A black or white window opens. That’s it.

Paste the command below:

notebooklm login

A browser window opens. Log in with your Google account.

Wait until the NotebookLM homepage loads.

Go back to the terminal.

Press Enter.

The terminal prints the path to your storage_state.json.

Copy it. Paste it back into Cowork:

Authentication saved to: /Users/learnai/.notebooklm/storage_state.json

Done! Cowork now has your credentials.

Note: If Cowork cannot reach the file, ask Claude Code to copy-paste the auth file into your working folder.

Step 4: Testing

Time to test the skill. Type /notebooklm

Ask it to list your previous notebooks.

Mine pulled 120 notebooks from October 2024 through today.

Fair warning, I am a pretty heavy NotebookLM user.

Let’s see my favorite use cases:

Use Case 1: Turn Ugly Spreadsheets Into Infographics Your CEO Will Actually Read

You know the drill.

You have a messy CSV.

Three different date formats in one column. Somebody’s initials in row 857 for no reason.

Your CEO drops a message: “Give me a summary by Friday.”

You spend three hours in Excel building pivot tables. Another hour picking a chart template that does not look like 2008. You created an infographic. Your CEO opens it, scrolls for four seconds, and closes it.

Nobody reads it.

Here is the version that works.

Step 1. Upload the spreadsheet to NotebookLM

Drop the CSV in as a source. NotebookLM parses the data, finds the patterns, and flags the anomalies.

You did not write a single formula.

Takes under a minute.

I’m using this data as an example, retail sales data from an online store.

Here is how my NotebookLM looks after uploading this data.

Step 2. Ask NotebookLM what matters

Paste this:

What are the five most important insights in this data? 
Ignore noise. Focus on what a non-technical executive would care about.
Each insight should be one sentence.

NotebookLM returns grounded answers.

Every insight traces back to specific rows. Click the citation, and see exactly where the number came from.

You now have the story before you have touched a design tool.

Step 3. Trigger the NotebookLM skill in Cowork

Open a new Cowork session. Trigger the skill:

/notebooklm Reach this notebook: European Export Sales Registry 2019-2020

Cowork now has read access to every source and every insight NotebookLM found.

Step 4. Give Cowork the build command

Paste this:

Build a web app that pulls the top five insights from the notebook 
and renders each one as a visual element. 

Let the user pick a style: minimal, corporate, or playful. 
Each style should have its own color palette, typography, and layout. 

Add a PNG export button.

After pasting, it started talking with the notebookLM.

You can see the conversation from the NotebookLM.

After getting the insights, it is now building the app.

And it is done.

Step 5. Export and ship

Click “corporate.”

Your five insights render as a clean one-page infographic

Or minimal.

Or playful.

Use Case 2: Build a Personal Language Tutor App Before Your Next Trip Abroad

You booked a flight to Barcelona. Three weeks out. You know ten Spanish words. Five of them are food.

Duolingo teaches you sentences nobody says. Google Translate is fine at the airport, but useless at dinner.

You don’t need another language app. You need a tutor who knows your trip: The neighborhood you are staying in, the phrases locals actually use, etc.

We’ll build a tutor with NotebookLM and Cowork.

Step 1. Let NotebookLM research your trip

Open NotebookLM. Create a new notebook. Name it barcelona-trip-tutor.

Click “Discover sources.” Switch on Deep Research. Paste this:

Research everything a first-time traveler needs to know about 
Barcelona for a trip in [MONTH/YEAR]. Focus on:

- Neighborhood guides for staying in Eixample, Gothic Quarter, 
  and Gracia
- Top 20 restaurants and tapas bars across different price points 
  (include addresses and what to order)
- Metro and bus system basics (which lines tourists actually use)
- Cultural etiquette Spanish people care about but tourists miss 
  (meal times, tipping, greeting)
- Common scams targeting tourists and how to avoid them
- Day trips within 1 hour of Barcelona (Montserrat, Sitges, Girona)
- Typical Spanish phrases locals use daily that tourists do not know
- Seasonal context: weather, festivals, crowds for [MONTH]

Prioritize sources from local bloggers and expat guides 
over generic travel sites.

After pasting this notebookLM, import the sources and here your notebook is ready.

Step 2. Ask NotebookLM to build the curriculum

Sanity-check first. Ask the notebook: “Which neighborhood am I staying in, and what are three phrases I will need there?” If the answer pulls from the research you asked for, you are good.

Then paste the curriculum prompt:

Based on the sources in this notebook, build me a 14-day 
Spanish crash course for my Barcelona trip.

Each day should cover:
- Five new phrases I will actually use on this specific trip
- Context for where and when I would use them 
  (hotel, tapas bar, metro, taxi)
- Pronunciation in plain English (not IPA)
- One cultural note about using that phrase

Prioritize phrases relevant to my hotel neighborhood, 
my restaurant bookings, and getting around the city.

Include Catalan variants where locals in Barcelona would 
appreciate hearing it (Catalonia has its own language alongside Spanish).

Skip greetings I already know like “hola” and “gracias.”

NotebookLM returns a 14-day plan grounded in your actual trip. Not generic Spanish. Your Spanish.

Here it is.

Step 3. Trigger the NotebookLM skill in Cowork

Open a new Cowork session:

/notebooklm Reach this notebook: barcelona-trip-tutor

And here it connects.

Cowork now has your trip context and your curriculum.

Step 4. Build the tutor app

Paste this:

Build an artifact called “Barcelona Tutor” with three sections:

1. TODAY’S LESSON

   Show today’s five phrases with pronunciation and context.

   Mark a phrase as “learned” with a checkbox.

   Progress bar shows how many phrases I have learned this week.

2. QUICK DRILL

   Flashcard mode. Show the English phrase, I guess the Spanish.

   Tap to flip. Rate myself (easy/medium/hard).

   Hard cards come back tomorrow. Easy ones disappear.

3. TRIP SCENARIOS

   Pre-built roleplays for: hotel check-in, ordering tapas, 

   taking the metro, asking for directions.

   I pick a scenario, the app shows me the likely script 

   with my phrases highlighted.

Pull all phrases, pronunciations, and cultural notes 

from the connected NotebookLM notebook.

And click on “Create” when it asks.

Here is your app.

Three tabs, one live app, built in ten minutes.

Today’s Lesson feeds me five phrases I will actually use in Barcelona.

Quick Drill turns them into flashcards with spaced repetition, so hard cards come back tomorrow, and easy ones get out of my way.

Trip Scenarios drops me into real roleplays, asking for directions in the Gothic Quarter, ordering tapas, checking into the hotel, with my own phrases highlighted in the script.

Every word traces back to the NotebookLM notebook I built in Step 1. Grounded curriculum, personal context, zero generic Duolingo energy.

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Use Case 3: Spy on Competitor Content and Extract What’s Actually Working

Every writer stares at the same question on Monday morning.

What should I write this week?

You scroll through three competitor Substacks. You read ten articles. You try to reverse-engineer what made their viral posts hit. You take messy notes. You forget half of them by Wednesday. You end up guessing anyway.

Twenty hours a month, gone. Pattern recognition done by vibes.

Here is the version that works.

Step 1. Collect competitor URLs into one place

Pick three to five writers in your niche.

Grab the URLs of their last free articles. ( to get the tone)

Fastest way: open their Substack archive page, scroll to the bottom, and copy the list.

Here are my articles.

1- NotebookLM Prompts for Students 

↳ http://gencay.substack.com/p/notebooklm-prompts-for-studying

2- NotebookLM Prompts to Beat 99%

↳  https://gencay.substack.com/p/10-notebooklm-prompts-that-put-you

3- Free 2026 AI Learning Path

↳ https://gencay.substack.com/p/how-to-learn-ai-in-2026-without-spending

4- Run Claude Code Locally (Free)

↳ https://gencay.substack.com/p/how-to-run-claude-code-locally-100

5- Claude Code Source Code Leaked

↳ http://gencay.substack.com/p/claude-code-source-code-free

6- Claude Code + Telegram

↳ https://gencay.substack.com/how-to-connect-claude-code-with-telegram

7- 7 Hidden Claude Features

↳ https://gencay.substack.com/p/claude-hidden-features-guide

8- ChatGPT → Claude: 5 Surprises

↳ https://gencay.substack.com/p/5-surprises-that-hit-you-when-you

9- Claude Cowork: What Actually Works

↳ https://gencay.substack.com/p/i-tested-all-claude-cowork-features

10- Claude for Content Creation

↳ https://gencay.substack.com/p/the-developer-tool-thats-quietly

11- OpenClaw Better Than 99%

↳ https://gencay.substack.com/p/how-to-use-openclaw-better-than-99

12- Clawdbot Setup (Cheapest + Secure): 

↳ https://gencay.substack.com/p/clawdbotopenclaw-cheapest-most-secure

13- Hire a Free AI Employee (Clawdbot): 

↳ https://gencay.substack.com/p/how-i-hired-a-free-ai-employee-clawdbot

Step 2. Upload to NotebookLM

Create a new NotebookLM notebook.

Select a web search and use this prompt with the links above.

Analyze the following Substack articles as competitor intelligence.

Extract:

* Tone of voice (writing style, pacing, personality)
* Hook patterns (how each article starts)
* Content structure (sections, flow, formatting)
* Title patterns (what makes them clickable)
* CTA strategies (how they drive engagement like restacks, clicks)
* Common topics and positioning
* What makes these posts perform well

Then:

* Identify repeatable patterns across all articles
* Highlight the top 5 strategies I should reuse
* Suggest 5 new article ideas based on these patterns
* Rewrite one viral-style post using these insights

Articles: [pasted from step-1]

And make sure to select “Deep research”.

Step 3. Ask NotebookLM to find the patterns

Step 2 triggered the scrape.

Now that the sources are indexed, we go deeper. Open the notebook chat and paste this

Analyze all sources in this notebook. Find patterns across the articles.

Return:
1. Top 10 headline formulas (with example headlines for each)
2. Top 5 hook patterns used in the first 200 words
3. Most common article length (words)
4. Most common CTA placements and wording
5. Topics that appear in more than 3 articles

For every claim, cite the specific article it came from.

NotebookLM returns grounded patterns.

Every insight traces back to a real article.

Here it is.

Step 4. Trigger the NotebookLM skill in Cowork

Open a new Cowork session:

/notebooklm Reach this notebook: LearnAIWithMe: The Complete Guide to Mastering AI Workflows

Point it at the notebookLM you just trained.

Step 5. Build an Artifact

Next, paste this:

Connect to my NotebookLM notebook <Paste name of your notebooklm>
Build an artifact called “Content Spy Dashboard” with four sections:

1. HEADLINE FORMULAS
   Show the top 10 formulas with usage count. 
   Click any formula to see example headlines that use it.

2. HOOK PATTERNS  
   Show top 5 hook patterns with one-line descriptions. 
   Click to expand and see real examples from competitor articles.

3. TOPIC HEATMAP
   Grid view. Rows = topics. Columns = competitors. 
   Cell shows how many articles each competitor wrote on that topic.

4. GAP FINDER
   List topics the competitors cover often but your niche could 
   approach differently. NotebookLM should suggest angles.

Add a “Generate Draft” button at the bottom. 
When I click it, the app picks a winning formula + a gap topic 
and drafts a headline + opening paragraph in my voice.

Save my past 10 articles as reference for voice matching.

Cowork builds.

It queries NotebookLM.(Cowork side)

See how it is talking with NotebookLM.

You can follow the progress from here.

Allow this.

And finished, let’s test it.

Step 6. Test the Artifact

Here’s what it looks like.

Cowork built this in under ten minutes.

Eleven of my own articles are indexed as the competitive corpus.

Headline formulas, hook patterns, topic heatmap, gap finder, and a draft generator — all live, all clickable.

The “Generate Draft” button at the bottom is the kicker.

It picks a winning formula, pairs it with a gap topic, and drafts a headline plus opening paragraph in my voice.

From competitive research to the first draft in one click.

AI News: Artifacts recently became available in Cowork.

Final Thoughts

Most people treat NotebookLM and Cowork as two different drawers.

Research goes in one. The building goes in the other.

They never open both at the same time. That is the mistake.

Connect them, and the math changes. Your sources become the ground. Your apps inherit that ground.

Don’t forget to subscribe to LearnAIWithMe, a newsletter focused on practical AI tutorials for people who’d rather replace than be replaced by AI.

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You’ve probably done this before.

Hit Day 180 on Duolingo. Finished a beginner Spanish course. Maybe even paid for a tutor on iTalki. You can read a menu. You can say “where is the bathroom?” with a decent accent.

Then you got on a call with a native speaker and your brain went completely blank.

That gap between “I’ve been studying for 6 months” and “I can hold a real conversation” is where most language learners die.

The one thing that closes that gap is the one thing they never get: feedback on their speaking skills

I speak 4 languages. I learned all of them before AI was a thing.

How did I become fluent? Someone who actually listened to me speak, noticed the exact pattern I kept getting wrong, and made me fix it over and over until it stuck.

That person was sometimes a tutor or a language buddy.

The problem? Good tutors are expensive, while language buddies aren’t available 24/7.

I’ve now built a system with Claude that does the same thing for free, 24/7, calibrated to exactly how I learn.

This post is that system.

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Why most people never become fluent

You take a class, learn some grammar, maybe use Duolingo for a few months. You memorize verb conjugations, learn vocabulary lists, and pass tests. You feel like you’re making progress.

But you’re not becoming fluent. Why? Two reasons

#1 You’re learning about the language, but you’re not speaking it.

You have a lot of knowledge in your head, but you can’t put any of it into practice in a real conversation.

Speaking is what makes everything click. It turns passive knowledge into actual fluency.

#2 You have speaking practice but lack good feedback

If you practice speaking but no one corrects you, you’ll keep making the same mistakes.

Before AI, to get feedback, we had to settle for:

• Language buddies who correct whatever they happen to notice, or (most of the time) say “it’s fine” to avoid being rude

• Teachers who can’t give you feedback 24/7. They can’t listen to the phone call you had this morning or the language exchange you had at the bar last night. Their feedback only covers the hour you spend with them in a lesson

That specific pain is what pushed me to build this workflow with Claude.

The workflow that fixes this

My workflow looks like this:

1. You talk with someone else (or AI) in the target language

2. You record the conversation (start with a 5-minute sample)

3. AI transcribes the recording

4. You give the transcript to Claude

5. Claude gives you feedback based on your language DNA profile

After you repeat these steps multiple times, you’ll build a folder like this:

The two main things the folder contains:

• Multiple transcripts of me speaking the language

• My language DNA profile

Later, I’ll show you how to build your own language DNA profile.

First, let’s see what exactly this is.

The Language DNA Profile

The core of my system is this learner profile

This is one file that contains everything a tutor would need to know about you.

• Your language level

• Your goals

• Your grammar weak spots

• The topics you actually want to talk about

• Your learning preferences

• How you want corrections delivered (every mistake? most critical?)

• and more!

50 questions, answered honestly, compiled into one markdown file.

Your language learning DNA in a single document.

Once the file exists, you attach it to Claude every time you want feedback on your speaking. Claude reads it and instantly knows who you are.

No more repeating yourself. No more generic feedback. No more Claude burying you in walls of text or grammar theory when your profile explicitly says, “cut to the chase, just give me the fix.”

What this actually looks like

Without the file: Claude’s feedback is random and overwhelming. It looks something like this:

Everything at once. Some corrections matter, some don’t. No priority order. No awareness of your level. You read through it, feel discouraged, close the tab.

With the Language DNA Profile: Claude knows your level. The corrections are ranked by what actually undermines you in the situations you care about. Explanations stay short because your profile said so.

And when you ask Claude to teach you, it gives you examples and exercises tailored to you: your business, your hobbies, your world. Not a textbook's imaginary trip to the market.

It’s the difference between talking to a stranger and talking to a tutor who’s been working with you for months.

The honest part: this is more work than Duolingo

I’m not going to lie to you. This system asks more of you than opening an app for 5 minutes. Maybe 30 minutes of total effort per session.

That’s also why it works.

Duolingo asks for 5 minutes and returns 5 minutes of progress. This asks for 30 minutes and returns something Duolingo literally cannot produce at any price: feedback on the actual words coming out of your mouth.

The rest is behind the paywall

Here’s where I’m going to ask you to subscribe.

Not because I like paywalls. I don’t. But what comes next is the part that took me months to build. I released the first part of this course in January (see here). That’s a 3-hour video course where I show how to use ChatGPT to improve your speaking, reading, and writing, and NotebookLM for vocabulary and listening.

Now the course includes Claude.

Below, you get:

The prompt that captures your language DNA profile: Copy, paste into Claude, spend about 40 minutes answering honestly. You’ll walk away with a markdown file that captures your profile as a language learner.

The full workflow: The best way to record a conversation, how to get a transcript in a few minutes that labels speakers for better feedback, and the exact prompt I paste into Claude afterward that turns 30 minutes of speaking into a tutoring session.

Every video course I’ve made (free to paid subscribers): Honestly, the courses alone cost more than the subscription.

If you’ve been learning a language but still can't hold a conversation, now's the time. Take my video course and copy my Claude system 👇

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Note: The link to the video course is at the end of this post. Both monthly and annual subscribers can redeem the course for free.

The prompt that builds your Language DNA Profile

Read more

That changes in 2026.

Hundreds of you became paid subscribers this year, pushing Artificial Corner to #80 in Substack's Technology bestsellers.

Thank you so much!

Because of you, I can do something I’ve never done before: build a team. The content you’re about to get is going to be better because of it.

Quick hi to the new subscribers

A lot of you have joined in the past two months (welcome!).

I’m Frank. Over the past 5 years, I’ve been creating guides, video tutorials, and courses that have reached:

• 58k+ email subscribers on Substack

• 149k+ followers on Medium

• 40k+ subscribers on YouTube

• 30k+ students across my Udemy courses

I did all of this solo. Until now.

Meet the Team

Recently, I stopped creating content alone.

• is co-building the Learn Any Foreign Language with AI course with me (we have a new Claude module dropping this week).

• is building the AI Writing System with me. This is the system that makes Claude write in your voice across posts, emails, reports, and presentations. He also helps me ship the weekly Claude guides.

My old self would have tried to automate their roles.

After five years of solopreneurship, I learned the opposite lesson:

This is the shift behind everything coming next.

What everyone gets for free: My Claude course

This year, I've been sharing everything I know about Claude: the setups, best features, best practices, real workflows, etc.

That’s turned into a catalogue of around 20 Claude lessons.

95% free and staying free.

🎁 Click here to see the Claude course outline

Every week, I’m updating the course with a new guide (so save that link!)

My free Claude course is just the starting point.

Paid subscribers get more.

What’s new for paid subscribers:

I read all your messages! Here’s what many of you wrote after becoming paid subscribers:

The thing that keeps coming up: people want more Claude content.

Here’s what paid subscribers get right now, and what’s landing in the next 60 days.

Subscribe now

Perk #1: A deep-dive guide every week

Not surface-level tips. Real workflows, systems I’ve built over years of actually doing this, and guides you won’t find anywhere else.

I'm also collaborating with experts across different fields to publish how they're actually using AI in their work. I can’t promise one every week, but I’m aiming for at least one every two weeks.

Perk #2: Free access to my video courses ($200+ value)

After becoming a paid subscriber, you’ll get an email with a link to redeem any of my courses for free:

• Learn a Foreign Language with AI

• ChatGPT

• Python: Web scraping (best seller) and automation

That’s $200+ in courses, included.

Perk #3: Coming this week — Claude module for language learning (Spanish, French, etc)

This week, I’m adding Claude to my Learn Any Foreign Language with AI course.

Enrollments are open to all paid plans (monthly and annual). Diana is joining this project and is helping me add valuable content to the course.

If you’re a paid sub and have no access, don’t worry — I'll send you an email this week to redeem all my courses for free

Perk #4: Coming in May — My AI Writing System

We’re releasing the first part of my AI writing system. The complete set of files to make Claude write like you across short and long form content.

Kevin and I have been building this for months. I'm very excited to ship this one.

I’ve got a few more surprises planned for June and July that I think subscribers (especially from the USA) will love, but I don’t want to get ahead of myself and promise anything yet :)

What I can promise is that this newsletter will stay ad-free.

If I ever accept paid sponsorships, it'll be on my YouTube videos (as I've done many times in the past)

If you’ve been on the fence about the paid subscription

Here’s what I’d say: the price isn’t going up right now, but the value is going up fast. We’re constantly adding more: more course lessons, deep dives, expert guides, AI systems.

The people who join now get everything at the current price.

Same price, more value, every month.

Substack works on a simple rule: the rate you join at is the rate you keep, for as long as you stay subscribed. If I ever do raise them, you’re grandfathered in.

So whatever you pay today is what you pay forever.

Click here to get these and future perks: artificialcorner.com/subscribe

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For many years, I wrote this alone. The next chapter has a team. I hope you'll be in it.

See you on the next Claude guide!

Best,
Frank

The difference lies in the core concepts.

For example, once you know what a “context window” is, you understand why Claude might sometimes forget what you told it twenty messages ago.

Tools like ChatGPT and Claude made AI accessible to anyone with an internet connection, which is great. However, there’s a big gap between using AI and understanding how AI works.

There are dozens of technical AI concepts floating around, but not all are worth your time. Here’s my curated list of concepts that genuinely matter for non-technical Claude and Claude Cowork users.

Click here to get my FREE Claude course (20+ lessons)

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Prompt Engineering: Is it still relevant in 2026?

Prompt engineering is the skill of giving better instructions to AI so you get better results. The clearer you are about what you need, who it’s for, what format you want, and what tone you expect, the more useful the response will be.

Some months ago, Anthropic shared the anatomy of the perfect Claude prompt:

Things have changed a lot since they shared this, though (AI moves fast!)

Tools like Claude Cowork need less prompting (see here and here). That said, I still consider prompt engineering useful when working with Claude chat.

Tokenization: The reason why your Claude usage limits don’t last long

Before Claude can process what you write, it has to translate your text into something the model can understand.

That’s called tokenization.

Tokens are small units that can be a whole word, part of a word, a number, or even a punctuation mark. Token counts aren't universal. The same word can be split into 2, 3, or 4 pieces depending on the model.

Why not just use full words? Language is messy. New words, typos, slang, mixed languages... if the model had to store every possible word, the vocabulary would be impossible to manage. Tokens solve that: with a fixed set of building blocks, the model can understand words it’s never seen before by breaking them into familiar pieces.

Every message you send, every reply Claude gives, and the whole conversation history behind it all get counted in tokens. When Claude tells you you’ve hit the usage limit, it means you’ve used up your share of tokens.

📚 How I Stopped Hitting Claude’s Usage Limits

AI Models: Use the right model for your task

There’s more than one Claude model.

When you see names like “Claude Sonnet 4.6” or “Claude Haiku 4.5,” you’re looking at different versions of the same product. Opus is the most powerful. Sonnet balances speed and quality. Haiku is the fastest and most affordable.

Think of it like software subscription tiers: they all do essentially the same thing, but with different levels of power and cost. The same prompt might get you a good answer with Haiku and an excellent one with Opus. But using Opus for simple tasks is like using an excavator to plant a seed.

Here’s a comparison between Claude models:

In case you're wondering what Mythos is, it's Anthropic's most powerful model — and the one they've chosen not to release publicly (it's only available to a handful of partners for security research).

Opus 4.7 is Anthropic’s most powerful model that you can actually get your hands on today.

📚 Claude Opus 4.7: What changed & how to get more out of it

.md file (markdown file)

An .md file is simply a text file.

Markdown gives you headings, code blocks, bold/italic text, and organized lists. This structure helps AI (and us) quickly find sections without having to read the entire file top to bottom.

Here’s what a simplified .md file looks like:

# Blog Post Instructions

## Structure
- Start with a personal story (1-2 sentences max)
- 3 tips only. No fluff. Each tip should have a real example.
- End with one clear takeaway the reader can apply today

## Writing Style
- Short paragraphs (2-3 sentences max)
- Use “you” more than “I”
- No corporate jargon. Write like you’re texting a smart friend.
- Never use: “In today’s world”, “Let’s dive in”, “Game-changer”

## Formatting
- No bullet points inside the body (use them only for lists of tools)
- Bold only the first sentence of each tip
- Total length: 800-1000 words

How are .md files relevant to Claude?

• You can put context in an .md file, so you don’t have to repeat yourself again (for this, I use the interview method)

• Your long prompts can be turned into an .md file using Claude skills. They can later be triggered when needed by Claude

Think of .md files as recipes: write the instructions once, and the AI follows them every time it runs the task.

Click here to get my FREE Claude course (20+ lessons)

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Read more

Every time a new AI model drops, the announcement sounds the same: “Smarter. Better. More capable.”

Cool. But what does that actually mean for you?

I went through Anthropic's official announcement, read tips from the creator of Claude Code, and did my own tests to find what’s good about Opus 4.7 (so you don't have to)

In this guide, you’ll learn:

• The top 4 things that changed in Opus 4.7

• How to get more out of Opus 4.7

• What to watch for if you’ve been using Opus 4.6

• Your first 30 minutes with Opus 4.7 (find out whether 4.7 is good or bad news for your workflow)

Subscribe to get my FREE Claude course.

20+ lessons delivered straight to your inbox 👇

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Top 4 things that changed in Opus 4.7

#1 Vision got a serious upgrade

Opus 4.7 can see images at 3x higher resolution than any previous Claude model (up to around 3.75 megapixels).

This means Claude can actually read:

• Dense screenshots (dashboards, analytics, small UI text)

• Complex diagrams

• Detailed charts with small numbers

• Scanned documents

If you upload a packed screenshot and Claude used to miss half the text, that problem is mostly gone now.

#2 It follows instructions way better

Opus was already my favorite model for instruction following. That’s one of the reasons why I switched to Claude (wrote about it here).

Opus 4.7 is substantially better at this.

But here’s the catch: prompts written for older models might produce unexpected results now. Why? Because 4.7 takes your instructions literally. Older models interpreted things loosely or skipped parts entirely.

You might want to re-check your saved prompts.

#3 Adaptive thinking

Older Claude models used a fixed thinking budget.

Opus 4.7 replaces that with adaptive thinking

The model now decides on its own when to think deeply and when to skip thinking altogether. Simple tasks get quick responses. Hard problems get more thought behind the scenes. Over a long session, this means faster responses and less wasted compute.

Adaptive thinking shouldn’t be confused with the model router (as we’ve seen with GPT-5). According to a Claude PM, this is the model being trained to decide when to think based on the context.

For more control, try these prompts suggested by Anthropic:

• More thinking: Try something like: “Think carefully and step-by-step before responding; this problem is harder than it looks.”

• Less thinking: Try: “Prioritize responding quickly rather than thinking deeply. When in doubt, respond directly.”

The first option gives you more accuracy. The second saves tokens but might miss nuance on harder tasks. Pick based on what you're working on.

#4 A new "xhigh" effort level

There’s also a new effort level called xhigh. It sits between high and max. Smarter than high, less prone to overthinking than max. It’s the new default in Claude Code.

How to get more out of Opus 4.7

Boris Cherny (creator of Claude Code) shared his own tips alongside the launch. I’ll mix his tips with the official best practices blog.

His tips come from hands-on experience with Opus 4.7 in Claude Code, but the core concepts apply just as well when working with Claude and Claude Cowork:

Specify the task up front, in the first turn

With Opus 4.7, you want to treat Claude more like a capable engineer you're delegating work to, and less like a pair programmer you're guiding step by step.

Opus 4.7 works better when it has everything upfront.

Instead of sending 10 small messages, write one detailed prompt that covers what you want, the constraints, and where the relevant files are.

Give Claude a way to verify its own work

This is maybe Boris’s most important tip. Always give Claude a way to check its own output. Depending on what you’re building:

• Backend work: Have Claude run your server to test things end-to-end

• Frontend: Use the Claude browser extension so it can see what it built

• Desktop apps → Use Computer Use

Boris has a skill called /go that makes Claude test itself using bash, browser or computer use, run the /simplify skill, and put up a PR. All in one shot.

Use auto mode

Shift+Tab turns on auto mode in the CLI (Claude Code)

Instead of Claude asking “can I run this command?” every 30 seconds, a safety classifier decides if it’s safe and auto-approves.

This is the middle ground between babysitting the model and --dangerously-skip-permissions (which is what devs used before this shipped).

Run the /fewer-permission-prompts skill

Even if you don’t use auto mode, run this once.

It scans your session history → finds the bash and MCP commands you keep approving → suggests adding them to your allowlist.

Recommended effort settings

Think of effort levels as a slider between speed and intelligence:

• Low/Medium → Fast but less thorough

• High → Good balance of intelligence and cost

• xhigh → Best for most coding and agentic tasks (the new default)

• Max → Maximum intelligence, but it can overthink and burn tokens

Boris uses xhigh for most tasks and max only for the hardest ones.

Use /effort to set the effort level

Try Recaps and Focus mode

Two features that shipped with 4.7:

• Recaps → short summaries of what the agent did and what’s coming next (great when you return to a session after a few hours)

• Focus mode → hides all the intermediate work so you only see the final result. Type /focus to toggle it on or off.

What to watch for if you’ve been using Opus 4.6

If you’ve been using Opus 4.6 for a while and have prompts dialed in, here’s what to watch for:

• Response length now matches the task: Simple questions get shorter answers. Open-ended stuff still gets longer ones. If you need a specific length or style, say so in your prompt. Anthropic recommends showing Claude an example of the voice you want. That works better than negative “Don’t do this” instructions.

• It uses tools less and thinks more: Usually, that's a good thing. But if your workflow needs aggressive search or frequent file reading, spell it out. Tell Claude when and why to use the tool.

• It spawns fewer subagents: Opus 4.7 is more conservative about delegating work to subagents. If you need parallel work, tell Claude explicitly.

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Your first 30 minutes with Opus 4.7

Watching others test Opus 4.7 is good, but you know what’s better?

Testing it yourself! That’ll help you see whether this update improves or hurts your prompts and workflows.

Try this right now.

Minutes 0-5: Rerun your most complex prompt

Pick a prompt with multiple rules, specific formatting, or several steps (the trickier the better).

Run it again on Opus 4.7.

If the output follows every single instruction — even the small ones older Claudes used to skip — that’s the upgrade showing up. If not, update the prompt.

Minutes 5-10: Throw a dense screenshot at Claude

Grab a busy dashboard, a packed analytics screen, or a diagram with tiny text.

Upload it. Ask Claude to extract everything.

If 4.6 used to miss half the details, you’ll notice the difference immediately.

Minutes 10-20: Generate a real deliverable in Cowork

Opus 4.7 produces more rigorous finance analyses and models, more professional presentations, and tighter integration across tasks.

Put it to the test! Pick something you’re actually working on — a weekly report, a client deck, a one-pager.

Let 4.7 generate it in one shot

Then look at the details: structure, visual hierarchy, how ready-to-send it feels. This is where 4.7 steps up the most over 4.6.

Minutes 20-30: Try adaptive thinking

Click on the model selector → Toggle on “adaptive thinking.”

Try one of your prompts. If you need more control, add one of these:

• More thinking: “Think carefully and step-by-step before responding; this problem is harder than it looks.”

• Less thinking: “Prioritize responding quickly rather than thinking deeply. When in doubt, respond directly.”

After these first 30 minutes, you’ll know what works and what doesn’t for you.

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One more thing

You now know what changed in Opus 4.7 and how to get the most out of it.

But new models keep shipping. New features keep dropping. And the people who get the most out of Claude are the ones who stay ahead of every update.

That said, it’s hard to stay ahead by taking courses that become outdated fast.

AI moves fast. This is a challenge even for online academies with 5M+ course enrollments:

A course published 7 months ago — already outdated.

That’s why I created a living Google Doc with my best Claude guides. Written guides take minutes to update. Video courses don’t. I keep this doc current so you’re never learning something that stopped working two updates ago.

Here’s what you get by becoming a monthly or annual paid subscriber:

• Full access to the living Google Doc with my best Claude guides

• Free access to my video course catalogue (over $200 in value) and future evergreen course releases

• A private community where you get advice from other professionals and me

I’m adding new perks constantly. Subscribe now and you lock in today’s price for everything that’s already there (and everything I add next).

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Hi!

Today, and are sharing with us a Claude in Excel guide. They write Cash&Cache, a weekly newsletter with AI build guides, product teardowns, and strategy that helps you figure out what actually works. Check out Cash&Cache for insights that changes how you work with AI.

Many AI tools say they can handle spreadsheets.

So you upload your file and ask it to clean the data. It gives you a formula. You paste it into Excel. It breaks.

You go back. “That formula doesn’t work.” Your AI tool apologizes. Gives you another one. That one breaks too! Thirty minutes of back and forth. You're still copying formulas from a chat window into a spreadsheet like it's 2023.

Claude in Excel skips all of that.

It reads your actual cells, writes the formulas directly, and builds the dashboard inside your spreadsheet. No copy-pasting. No broken formulas from a chatbot that can't see your data.

As a data analyst, I’ve wanted to write a guide like this for a while, and I’m happy to share this piece, co-authored with Ashwin and Raghav

How to install Claude in Excel

The installation is quite straightforward

Open Excel, go to Home → Add-ins (or Insert > Get Add-ins) → search for “Claude by Anthropic.”

The Shortcut: Memorize this immediately—Ctrl + Alt + C (Windows) or Ctrl + Option + C (Mac). This toggles the Claude sidebar instantly. If Excel throws a shortcut conflict popup, select ‘Show Claude sidebar’. You probably won’t miss whatever obscure legacy command used to live there.

Permissions: For some advanced features mentioned below, you might need to sign in with a Claude Pro, Team, or Enterprise account. The 2026 rollout now includes “Ask Before Edits” mode, which we recommend keeping ON to maintain control over your cell values.

Cash & Cache

Where capital meets code — exploring how AI is transforming businesses, markets, and value.

By Ashwin Francis

I’ve added a new section to my Claude course, with workflows you can copy and start using right away: Check it out here

What Can Claude Do?

We take Claude through 3 levels of increasingly difficult tasks, which you are likely to see in your workflows.

1. Data Cleaning

Let’s take a dirty dataset and see if Claude is able to save us the effort of reviewing, planning and executing the data cleanup process. I didn’t have a dirty dataset on hand, so I borrowed this one from ForesightBI.

One of the datasets has an issue I have come across many times before: multiple data fields are clumped together in one column instead of being separated by fields.

First, highlight all the affected cells. Then describe the problem that you need to solve. You’ll see the highlighted cells written on top of your prompt.

Before making the edits, Claude will ask you permission to edit the file. This is what the final result looked like.

This example was quite simple because we highlighted the problem and also mentioned what needs to be done.

What if we just highlight the problem and let Claude figure out the best way to clean and represent the data? We prompt:

This data is clumped together. Separate it into a clean table.

The data structure below has multiple product categories with different amounts, all linked to a specific ID. This requires splitting data across columns, transposing the values and aligning identifiers across multiple line items. A bit more complicated.

Highlight all cells in the data structure and tell Claude to ‘Clean up this data’. We had an answer column in the same sheet. I deleted that so that Claude couldn’t cheat. This is the final table it spit out in a separate sheet, which perfectly matches what we want.

Now let’s look at more nuanced workflows. Let’s employ Claude to help us analyze data and find trends.

2. Data Analysis & Business Intelligence

We already saw that Claude is able to help us clean data, but what about summarize, visualize, and synthesize insights?

I downloaded the dataset for this experiment from Kaggle. This was a comprehensive dataset (15,000+ rows) with plenty of fields to support analysis. The dataset tracked Summer Olympic medals between 1976 and 2008. I wanted to conserve my token limits, so I truncated the dataset to cover 2000, 2004, and 2008 (6,000+ rows).

I didn’t know where to start the analysis, so I delegated that to Claude: “Tell me more about this data”.

Claude is smart enough to understand that it doesn’t need to go through the entire dataset to understand the context. Claude ran through the first 10 rows and gave me a summary and data structure. Because it only reviewed the first 10 rows, Claude assumed (based on the title) that the data included 1976- 1996, but this was corrected after we went to the next step.

Next, we need to summarize and visualize. Every executive loves a dashboard, so let’s start by having Claude make one for us:

Some data points that I would like to see: (1) totals medals won by countries, (2) are there any countries that dominate one sport across multiple years, (3) if there are any athletes that have won medals across multiple Olympic events. Additionally we also need visuals to identify trends in the dataset.

This is what I passed to Claude, along with a final line to add any interesting charts/ insights that I might have missed.

The first draft was actually pretty good, but it wasn’t properly formatted with a standardized color theme, chart formatting rules, correct legend positioning, etc. After prompting for some minor tweaks, we got a much better version.

There are still a few edits I could make, like adjusting the row widths and whitespaces between visuals. But this is already a dashboard I can actually use for serious analysis.

The tables answer the three questions that I had. Claude leveraged Python scripts to prepare some insights, as this would not be easy to recreate in Excel manually. This is a huge plus point.

Data analysis helps us uncover what is happening. Let’s see if Claude can use data to model outcomes.

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3. Build a Business Model

I love building financial models and business cases. It helps you get a realistic idea (if you are honest with yourself) of how an initiative will pan out.

For the last use case, we will be using Claude to build a business model for a new startup. Let’s take the example of ScheduleAI, a social media SaaS platform that allows creators to schedule content across multiple platforms, including LinkedIn, Instagram and Substack.

We need a business model to understand what we can realistically achieve in 3 years, and whether the business model is profitable and scalable. We need the model to capture both business metrics like subscriber count, % of paid customers, and churn. Let’s assume that ScheduleAI follows a subscription-based pricing model with 3 tiers, 2 of which are paid.

I brainstormed the business model (pricing tiers, business metrics, etc.) in Gemini and asked for detailed prompts to help Claude build this model in Excel. I find Gemini ideal for brainstorming. They have generous usage tiers, so you can redraw your plans multiple times without worrying about context limits.

Ask Claude to ensure:

1. Values are not hard-coded and linked to primary cells where applicable - model is dynamic

2. Input cells should be formatted differently from formula cells (we follow blue for input and black for formulas) - makes sure that the model you build is dynamic and that you can tweak assumption values to see the impact across the entire model.

Let’s build this out in stages:

Stage 1: Build the assumptions and Subscriber Waterfall

Let’s start with all the assumptions we will use for the model and the baseline business metrics, which we predict for the business. Gemini gave us a detailed prompt with all the key assumptions that fit the ScheduleAI business model

In a blank sheet, create an 'Annual Assumptions' table in Rows 1-15 with columns for Metric, Year 1, Year 2, and Year 3. Set these blue-font inputs: Starting Free Users (5,000), Premium Price ($180/yr), Ultimate Price ($300/yr), Annual Churn (15%), and Free-to-Premium Conversion (5%).

Below this, starting at Row 20, build a 3-year annual subscriber waterfall. All formulas must use absolute references ($B$2 style) to link back to the Assumptions table. Format all hardcoded inputs in Blue Font and all formulas in Black Font. Calculate the annual totals for Free, Premium, and Ultimate users.

Stage 2: Annualized P&L

These assumptions will be the key drivers of the profit and loss statement (P&L) build. The P&L will help us discern if this solution can actually be profitable and that we won’t lose all of our money building and running this into the ground. Gemini gave us a prompt that outlines the P&L build, along with the revenue and cost drivers.

Directly below the User Waterfall, build a '3-Year Annual P&L.' Link Revenue lines to the annual user counts from Stage 1 and the Tier Prices from the Assumptions table. Include rows for COGS ($2.00/user annual hosting) and Operating Expenses (Staff: $50,000/yr; Marketing: 20% of Revenue). Ensure every cell in this section is a formula; no hardcoded numbers are allowed. Apply professional formatting: black font for all formulas and a light green fill for the 'EBITDA' row. Format all currency to $USD with zero decimals.

The P&L is quite high level, we do need to add multiple cost lines here, including incorporation costs, API costs (every time a creator schedules a post on LinkedIn/ Instagram, we will have to call their API), affiliate marketing costs, etc., etc. But this is an iterative process, so we build them out as we identify new revenue/ cost drivers.

3. Model Audit

Now that the first draft model is ready, it’s time to make sure it’s logically sound and paints a realistic picture of the future of ScheduleAI.

We identified some issues in the audit. For example, increasing the headcount didn’t increase staff costs (formula linking issues). Another issue is that the model doesn’t assume user growth over the years—we were doomed to have 5,000 users forever 😅. We should assume the user base grows each year, either at a fixed rate (say 10% annually) or a rate that accelerates over time.

Along with these fixes, I asked Claude to add a legend table so that the model is easy to understand.

The audit step is as important as the build. When you find issues, it’s important to highlight the cells and question Claude on its choices. I spent around 10-15 minutes questioning Claude on the assumptions used and tweaking the model to ensure that dynamism is maintained and the model is logically sound.

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Best Practices for Claude in Excel

If you want professional-grade results, follow this framework:

1. Describe the Mess, Not the Fix: As we did with the Olympic data, don’t tell Claude how to split columns. Just say, “This data is clumped together; separate it into a clean table.” Claude is better at figuring out the logic than you are at explaining it.

2. Request Dashboard Mode: When analyzing large sets, don’t ask for a single chart. Ask Claude to “Create a dashboard in a new sheet with key trends.” This forces it to use Python scripts (as seen in our Olympic test) to do the heavy lifting that Excel formulas can’t handle.

3. Color-Code Your Cells: To avoid the “broken formula” issue we found in the startup model, always prompt: “Format static inputs in blue and formula-linked cells in black.” This makes it easy for you to audit the “thinking” and catch growth rate errors before you present.

4. Always Ask Why: Never trust the first draft. If a headcount increase doesn’t change costs, highlight the area and ask, “Why isn’t this cell linked to the staff cost formula?” The value isn’t in the build; it’s in the audit.

Conclusion: The Shift in Value

The shift we’re seeing in 2026 isn’t just about a new tool. It’s a change in value.

In the past, Excel experts were the only people who knew the most complex formulas and could build a model fast. Today, that person is the one who knows what needs to be done and can validate the output. The new value lies in auditing the logic and interpreting the output.

By offloading the formula-building, the data-scrubbing, and the debugging, you finally get to spend your time on the strategic questions that actually matter. Our time gets invested in making decisions based on data rather than organizing and structuring analyses.

Don’t forget to subscribe to Cash&Cache for AI build guides, product teardowns, and strategies that help you figure out what actually works.

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Hi!

I wrote today’s post in collaboration with . Gencay writes LearnAIWithMe, a newsletter focused on practical AI tutorials for people who’d rather replace than be replaced by AI.

If you’re interested in building real projects with AI, I highly recommend checking out LearnAIWithMe

One of my favorite Claude Cowork tasks is web scraping.

Picture this: a bot visits a website for you, reads the page, and pulls out exactly what you need: prices, names, job listings, you name it (so you don't have to copy-paste anything manually).

That’s what web scraping is.

Data is everywhere. Heck, without internet data, tools like ChatGPT and Claude wouldn't even exist. The thing is, web scraping used to be a programmers-only thing.

Not anymore.

Cowork lets you scrape websites by just describing what you want in plain English. In this guide, you'll learn two ways to web scrape:

1. Scrape with Cowork alone: Best for grabbing data from simple pages, but it’s limited to what a single browser session can do and it can struggle with JavaScript-heavy sites

2. Scrape with Cowork + the Apify connector: Best for robust, scalable scraping across complex sites. The only con is that you need monthly credits. That said, Apify's free plan gives you $5 in monthly credits, which is enough for casual use.

By the way, I'm not associated with Apify. I just think it's a solid option worth knowing about. That said, if you're new to web scraping, don't worry about it. Option 1 is a great place to start.

Fun fact: 16,401 people took my web scraping video course back when coding was the only option. I’ll keeping making guides like this even if they make my own old content obsolete. Why? I believe powerful skills should be available to everyone.

Click here to get my FREE Claude course (20+ lessons)

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1. Web scraping with Cowork

For this section, I’ll use a problem I often have as a writer. You might not have the same issue, but this example will give you a good idea of how to web scrape with Cowork.

Every day, I publish Substack Notes, which are short-form posts that help me share bite-sized AI knowledge. Substack doesn’t offer Notes stats or an API to help writers keep track of notes.

Here’s when Claude Cowork comes in.

I had Cowork scrape Substack, build a dataset, and run a monthly analysis.

Here’s what a Note looks like (the data to extract is inside red boxes):

Here are the steps I follow to web scrape with Cowork:

1. Find your target page: Locate the website that has the data you need. In my case, it was the page where Substack archives all my published notes: artificialcorner.com/notes

2. Define the fields you want to extract: Decide exactly what data points matter. I wanted to extract six fields per note: date, post text, number of likes (hearts), number of comments, number of restacks, and post link.

3. Spell out the edge cases: Think about the details that aren’t obvious at first glance — this is what separates clean data from messy data. For example, my notes archive also includes notes I restacked from other writers, which I didn't want. So I told Claude to only extract notes authored by "Frank Andrade" and to limit the pull to a single specific month.

By the way, you will need the Claude in Chrome connector enabled in Cowork: Click “+” → Connectors → Toggle on “Claude in Chrome.” Also, you need the Claude extension active in Chrome (go here and install it).

Here’s the prompt I created from steps 1, 2, and 3:

Use Claude in Chrome for this task.

Start from: https://artificialcorner.com/notes
Author name: Frank Andrade
Month: February 2026

Extract this data from the site keeping in mind the author and month I wrote before: Date, Text of Post, Number of Likes (Hearts), Number of Comments, Number of Restacks, Link of Post

Your first test probably won't be perfect. Review the data Claude collected, and if something looks off, tell it what to adjust for the next run. In my case, the extracted links and a few other data points were wrong.

Here's the feedback I gave Claude

Claude understood everything and returned the right data.

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How to automate your web scraper in Cowork

Once Claude learns the best way to scrape the site, there are two ways to automate this process (so you don’t repeat the prompt and feedback again):

• Turn the chat into a skill: Save your chat as a reusable skill that you can run anytime. In this case, the skill will help me scrape data from any Substack writer’s URL (not only mine)

• Schedule the task: Automate the task for a specific writer on a recurring schedule (e.g., scrape “Frank Andrade“ notes every month on the 14th).

To easily turn a chat into a skill, do this: In the chat, click the dropdown arrow and select “Turn into skill.“ Claude will do the rest.

For this particular case, I used a prompt to guide Claude on how to turn my chat into a skill:

Turn this task into a skill. Keep in mind the fixes we made and that the inputs needed for this skill to work are:

Start from: [link]
Author name: [name]
Period: [month/dates]

Thanks to this, Claude can now scrape not only my notes, but the notes of any Substack writer. I just need to provide their link.

As for scheduling tasks, you can click the dropdown arrow and select “Schedule,” or use the /schedule command. The /schedule command gives you more flexibility — the dropdown only offers daily, weekly, or weekday options, while /schedule lets you set any custom recurring schedule.

In my case, I opened a new chat and used /schedule to have Claude automatically scrape my notes for the previous month on the 14th of each month.

/schedule run this task monthly on the 14th
Start from: http://artificialcorner.com/notes
Author name: Frank Andrade
Period: Previous month

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Click here to get my FREE Claude course (20+ lessons)

2. Web scraping with Cowork + Apify connector

When you feel Cowork isn’t enough to scrape a site, use the Apify connector to supercharge your web scraping.

Apify is a web scraping and automation platform with over 23,000 ready-made actors. Each actor is a pre-built scraper for a specific website or data source. Reddit, Google Maps, Meta Ad Library, LinkedIn, Amazon, they are all there, ready to run with no code.

Apify is great for robust, scalable scraping across complex sites. With the Apify connector, Cowork can tap into thousands of specialized scrapers with built-in proxy rotation and anti-bot handling that Cowork alone can't do.

You just pick the actor, set your inputs, and get structured data back in minutes.

Apify Use Cases

This section was written by who writes LearnAIWithMe. It covers how to connect Apify with Cowork and 3 use cases I found very useful:

• Use Case 1: Reddit Trend Tracker

• Use Case 2: Google Maps Business Scraper

• Use Case 3: Meta Ad Library Spy

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If you want to build with AI, not just learn how to prompt, this is the right place.

By Gencay

How to Connect Apify with Cowork

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Every month, there’s a new tool. Every week, there’s a new AI feature. If you’re trying to keep up, it feels like you’re always behind.

Most people deal with this by jumping from tool to tool, tutorial to tutorial, without ever getting good at any of them. They consume a lot but retain very little.

I used to do the same thing.

After teaching AI and other topics on YouTube and Udemy to thousands of people, I realized the problem isn't a lack of resources. It's a lack of structure.

People who learn AI quickly don't watch more tutorials. They follow a system.

Here’s my system for learning Claude and other AI tools without wasting time or feeling overwhelmed.

So far, my guides have taught you what to learn in Claude — the features, the use cases, etc. This one is different. It's about how to learn it.

This guide is exclusive to paid subscribers :)

Every week I publish a free and paid guide. Paid subs get full access to my best guides and other perks.

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