Today, I want to share a new episode with Moritz Kremb.

Moritz is an AI creator who built a personal OS in Claude Code to manage his emails, create content, and even buy groceries. In this episode, he walks through everything you need to set up your own: folder structure, tools, memory loops, skills, and routines. We also talked about the pros and cons of OpenClaw vs. Claude Code.

Watch now on YouTube, Apple, and Spotify.

Moritz and I talked about:

• (00:00) The honest tradeoffs: OpenClaw vs. Claude Code

• (09:03) The reliability problem that made Moritz switch

• (15:40) The folder structure that runs Moritz's entire OS

• (20:03) The memory loop that makes Claude Code remember everything

• (23:47) CLI vs. MCP vs. API: which to pick and why it matters

• (26:02) Skills walkthrough: automated grocery runs and video uploads

• (29:03) Local vs. remote routines (and when to use each)

• (31:51) The full content pipeline from idea to posted video

• (41:43) Tips to start building your first personal OS

I’m proud to partner with Linear

As teams ship faster with AI agents, the bottleneck shifts from building to deciding what to build.

Linear’s new Agent understands your full workspace context: roadmap, issues, customer requests, and code. Ask it to surface patterns across feedback, scope out a spec, or catch you up on team progress.

Try Linear for Free

Top 10 takeaways I learned from this episode

1. Build your Claude Code personal OS in 4 layers. Moritz runs his email, content pipeline, and grocery shopping through his Claude Code OS. It has 4 layers:

   1. Folder (with memory): A set of files Claude Code reads at the start of every session so it knows who you are, what tools it has, and what it remembers from past chats.

   2. Tools: The APIs, MCPs, and CLIs that let Claude complete tasks like send emails, post to social, search Google Drive, and more.

   3. Skills: Detailed instructions for tasks that Moritz does over and over like “upload my video files” or “refill my grocery cart.”

   4. Routines: Scheduled jobs that run proactively.

Let's walk through how to set up each layer below:

2. Set up your folder structure first. Get this right before setting up tools or skills so that your OS stays organized. Critical files include:

Read more

Today, I want to share a new episode with Ravi Mehta.

Ravi is a top AI instructor and former CPO of Tinder. In our episode, he did a live demo of using his 3-layer context engineering system (functional, visual, data) to build a beautiful music app instead of the usual AI slop. You’ll never prompt AI the same way again after learning about Ravi’s approach.

Watch now on YouTube, Apple, and Spotify.

Ravi and I talked about:

• (00:00) Why most AI prototypes feel like slop

• (01:08) Context engineering, explained from first principles

• (05:12) Layer 1 demo: Functional context

• (09:38) Layer 2 demo: Visual context

• (13:31) Layer 3 demo: Data context

• (15:47) Building a custom MCP server in Claude Code

• (19:54) The full stack prompt: all 3 layers in one shot

• (24:21) Why separating the data layer is the real unlock

• (28:59) Should PMs prototype or just ship to production?

• (33:51) Where PRDs still fit in AI native product development

I’m proud to partner with Wispr Flow

Wispr Flow has quietly become one of the AI tools that I use the most. It lets you dictate into any app on your computer or phone and turns your voice into clean, formatted text automatically.

I save at least 3 hours a week from using it to draft newsletter posts, write specs, and reply on Slack. It’s just so much faster to dictate to AI than to type, and you’ll never go back once you try it. Use code PETERWISPRFLOW to get 6 months free.

Try Wispr Flow for Free

Top 10 takeaways I learned from this episode

1. Apply three layers of context to create polished AI prototypes. Ravi built the same music app in 3 ways to highlight what each context layer adds:

   • Functional context. First, he wrote a spec listing the feature requirements (hero, albums, etc) and got a generic app with placeholders.

   • Visual context. Next, he added a wireframe from Figma to the prompt. This led to better UX and layout but the product was still missing real data.

   • Data context. Finally, he asked AI to generate a JSON with genre, artist, and album names and used a custom MCP server to pull in album cover art from Deezer. This time, AI generated a complete music discovery app.

The best thing about this system is that you can swap the data layer (JSON) at any time to have your app highlight completely different content (e.g., from rock to hip hop albums) without touching the other two layers.

Here’s a detailed prompt that Ravi shared with me to generate all 3 layers in one-shot for any app or idea that you have (just replace the music app details with yours):

Read more

Today, I want to share a new episode with Tibo Louis-Lucas.

Tibo is a solo founder making $1M+ a month (!) after bootstrapping 5 AI products. I got him to walk through his exact playbook for validating ideas fast, acquiring users, and pricing AI products. If you want to bootstrap an AI business from scratch, this interview is a must watch.

Watch now on YouTube, Apple, and Spotify.

Tibo and I talked about:

• (00:00) The right mindset for solo AI founders

• (04:48) Tibo's 5-rule playbook to reach $1M/month

• (09:55) The product pivot that unlocked $600K/month

• (13:08) Why you should charge money right away

• (20:50) The acquisition channel everyone says is dead (it's not)

• (26:58) Running 5 businesses without a real team

• (36:34) How to price your AI product

• (37:20) What's a good churn rate for AI products?

• (40:16) 9 products failed. The 10th hit $600K/month

I’m proud to partner with Oceans

I recently hired an executive assistant from Oceans to help with podcast post-production and it’s been one of the best decisions I’ve made. My assistant is proactive, picks up new tools fast, and is already using AI to speed up his workflows.

Oceans matches you with top-tier talent for marketing, operations, finance, and executive support, all fully vetted and ready to go. Book a call now via the link below.

Get Started for Free

Top 10 takeaways I learned from this episode

1. Tibo’s 5 rules behind his $1M/month AI portfolio. After launching 5 successful AI products (and many failed ones), Here’s Tibo’s rules to build an AI product that customers want:

   • Charge money from day one. Collect money early so you know if people actually want what you're building.

   • Follow user behavior, not your plan. When people twist your product into something unexpected, build for that instead.

   • Price for quality customers. Charging $50-100/month keeps away high-churn users who cancel fast and flood customer support.

   • Build free tools that rank on Google. Target each tool to a specific search query (e.g., “audio to video”) to win SEO traffic.

   • Launch fast and kill what doesn't work. Accept that most ideas will fail, so move quickly and double down on what sticks.

Let's dive into these rules with real examples 👇

Read more

Today, I want to share a new episode with Ryan Wiggins.

Ryan is the VP of Product at Mercury, my favorite fintech product. We covered three things that are on every AI builder’s mind — how to make your product agent-ready, how to build a Claude Code second brain, and what Mercury’s data reveals about OpenAI and Anthropic’s race for the enterprise.

Watch now on YouTube, Apple, and Spotify.

Ryan and I talked about:

• (00:00) Why APIs and MCPs are the primary interface

• (04:40) How to get your product agent ready

• (07:51) Will MCPs cannibalize your app DAU?

• (10:36) How to decide between MCPs and CLIs

• (13:10) Inside Ryan's Claude Code second brain

• (18:40) Getting AI to coach you after every meeting

• (20:46) Mercury data: Are startups switching to Anthropic?

• (23:05) The product development process will never be the same

P.S. Mercury is offering Behind the Craft readers 1 year of free personal banking. Just click the link to get the discount.

I’m proud to partner with Wispr Flow

For many PMs and tech professionals, communication is the job. Slack replies, stakeholder updates, PRDs, emails — most of us are bottlenecked by typing speed.

Wispr Flow is the tool I use to close that gap. You speak naturally into any app and it outputs clean, ready-to-send text. It genuinely saves me 3 hours per week and works across Mac, Windows, iPhone, and Android. Use code PETERWISPRFLOW for 6 months free.

Try Wispr Flow for Free

Top 10 takeaways I learned from this episode

How Ryan built his Claude Code second brain

1. Ryan built a Claude Code “second brain” trained on 5 years of work history that helped him 2x his productivity as a product leader. He did this in 5 phases:

   1. Create a profile. Have Claude interview you and write a me.md file capturing your role, goals, working style, and growth edges. This is the foundation.

   2. Build the knowledge base. Save your most important docs — specs, retros, performance reviews — in a local folder. Then ask Claude Code to install QMD (Shopify CEO’s vector search tool) so it can reference these docs.

   3. Distill the data. Ask Claude to create summary files using me.md and the knowledge base. For example:

      1. strategic-context.md — what my company/team is trying to do and why

      2. personal-growth.md — patterns in my feedback, coaching themes

   4. Wire up auto-context injection. Create a Claude Code hook that pulls relevant context from the files above into every prompt.

   5. Create the learning loop. Build a /learn skill that updates Claude.md after each session, plus cron jobs for morning briefs and monthly retros.

Ryan uses this to drive team priorities, make decisions, and self-reflect. It’s the most sophisticated personal OS I’ve seen, so I asked Ryan for a full 4,000+ word prompt that you can paste into Claude to set this up for yourself in 5 steps:

I want you to help me build a "Second Brain" — a persistent knowledge system that runs in parallel to my work using Claude Code. We'll do this in 5 phases. Walk me through each one interactively. Don't skip ahead — confirm each phase is working before moving on.

## Phase 1: Interview Me & Create my Profile

Interview me to create a file at ~/Documents/second-brain/me.md that captures:
- Who I am (role, company, responsibilities)
- What I'm optimizing for (goals, priorities, what success looks like)
- My working style (tools I use daily, how I communicate, what frustrates me)
- My growth edges (feedback I've gotten, patterns I want to break)
- What I care about outside work (interests, values — helps with recommendations)

Ask me 5-7 questions conversationally. Don't make me fill out a template. Write the file when you have enough.

## Phase 2: Build the Knowledge Base

Read more

Today, I want to share a new episode with Dylan Field.

Dylan is the co-founder and CEO of Figma. I asked him tough questions on whether AI can learn design taste, whether design systems constrain creativity, and what design’s role is when code is free. Two-thirds of Figma users are now non-designers and it was super interesting to hear Dylan talk about where he’s taking Figma next.

Watch now on YouTube, Apple, and Spotify.

Dylan and I talked about:

• (00:00) Taste, craft, and point of view: the 3 skills AI can’t replace

• (05:33) Can AI agents learn design taste?

• (15:00) What’s Figma’s role when code is free?

• (17:42) What vibe coding gets wrong about design

• (22:17) Two-thirds of Figma users are now non-designers

• (26:47) Do design systems constrain creativity?

• (29:13) The one trait Dylan hires for over AI fluency

• (32:01) Why Dylan thinks design is the new code

• (36:32) Dylan’s personal AI workflow for writing and ideation

I’m proud to partner with Linear

As teams ship faster with AI agents, the bottleneck shifts from building to deciding what to build.

Linear’s new Agent understands your full workspace context: roadmap, issues, customer requests, and code. Ask it to surface patterns across feedback, scope out a spec, or catch you up on team progress.

Try Linear for Free

Top 10 takeaways I learned from this episode

1. Taste, craft, and point of view are three different things. Here’s how Dylan defines each:

   • Taste is knowing what’s good and being able to articulate why. It’s navigating possibilities with clear preferences.

   • Craft is “pushing past where others might push” at every level, from the macro structure down to the smallest detail.

   • Point of view is the insight that you see, expressed through what you build. Dylan’s test: “If everyone agrees with your POV, you probably don’t have one.”

2. AI gets you to average fast and your job is to push beyond that. “The first thing AI gives you is generic by definition because it’s the average of everything it’s seen.” You need to apply your taste and judgment to iterate with AI toward something only you could have made.

Read more

Today, I want to share a new episode with OpenAI’s Codex team.

Alex is the product lead for Codex and Romain runs developer experience. They gave me a rare look at how their team operates including how they build products with Codex and ship without traditional specs or roadmaps. Alex also has some spicy takes on the future of PM and what he looks for when hiring (it’s not resumes!).

Watch now on YouTube, Apple, and Spotify.

We talked about:

• (00:00) Live demo: Building a game in seconds with Codex Spark

• (04:29) "For specs, we write like 10 bullets and that's it"

• (08:09) "Our designers now write more code than eng 6 months ago"

• (15:30) "We plan short and long term, never medium term"

• (22:11) How Alex actually spends his day as Codex’s product lead

• (32:06) The traditional career ladder no longer makes sense

• (39:20) What the Codex team looks for when hiring (it's not your resume)

I’m proud to partner with Linear

As AI agents like Codex become part of your company’s daily workflow, having visibility into what they’re doing is critical.

With Linear, you can delegate issues to Codex directly by simply tagging @Codex in an issue. You can also use the new Linear plugin inside Codex to ensure that your issues and project updates stay synced in real time.

Try Linear for Free

Top 10 takeaways I learned from this episode

How the Codex team ships products

1. The team designed the Codex app to let you delegate to multiple AI agents. The team knew that multi-agent delegation was the future, but felt that having 18 terminals wasn’t the right UX. So they started prototyping apps early before shipping on a beautifully simple agent management interface.

2. Plan near-term or long-term, never medium-term. Alex got this advice from an OpenAI researcher: “Plan concrete milestones up to 8 weeks out and have a long-term vision of where models are heading.” Medium-term roadmaps (e.g., 6-12 months) are awkward and always changing because AI coding is evolving so fast.

Read more

Today, I want to share a new episode with Jenny Wen.

Jenny is Cowork’s design lead. She gave me a rare inside look at how Anthropic operates — including how she uses Cowork to design and build products and the real story behind how Cowork was built. Anthropic is shipping new features every day and it was fascinating to see how they do it.

Watch now on YouTube, Apple, and Spotify.

Jenny and I talked about:

• (00:00) How design work has changed at Anthropic

• (04:30) "My secret is that I actually use Cowork for most things now"

• (05:19) Cowork demo: From messy user feedback into product insights

• (14:41) "Every Monday Cowork gives me 3 vetted product ideas"

• (23:09) The real story behind Cowork's development (10 days?)

• (27:18) Exclusive look: Cowork prototypes that didn't ship

• (34:01) How product planning works at Anthropic

• (38:10) "If you feel like the ground is shifting, it's because it is."

I’m proud to partner with Replit

Replit’s new Agent 4 is the best way for teams to collaborate with AI agents.

1. Creating multiple design variations on an infinite canvas (see above).

2. Building using parallel agents using a kanban-style task board.

3. Deploying to production in one click.

Get 3 months free to Replit by using my code PYANG26 at checkout.

Get Replit for 3 Months Free

Top 10 takeaways I learned from this episode

Jenny shared a lot of great insights so I’ve organized the takeaways into two sections:

1. How Jenny uses Cowork at Anthropic

2. How the Cowork team designs and ships products

How Jenny uses Cowork at Anthropic

1. Set up Cowork to deliver a product priorities deck every week. Jenny demoed using Cowork to summarize user feedback from customer calls and social posts. She then asked Cowork to use that feedback to create a product priorities deck. Finally, she scheduled a workflow to share an updated deck in Slack every Monday for her team to review.

Here’s a 1,500+ character Cowork prompt that I created to do all of the above in one-shot. Please make sure to replace [folder] with your local folder where you’ve pasted user feedback files and replace [product name] with your product name:

Read more

Today, I want to share a new episode with Felix Lee.

Felix has taught 1000s of designers how to code with Claude Code and Figma MCP. I got him to show me how he converts a Figma design into a working website and converts a website back into editable layers in Figma. A designer who can ship is one of the most valuable hires in tech today — learn how by watching this episode.

Watch now on YouTube, Apple, and Spotify.

Felix and I talked about:

• (00:00) 3 products Felix designed and built in Claude Code

• (06:36) Building a 3D animated world map in one-shot

• (07:50) Felix's app that analyzes how good your landing page is

• (13:17) Demo: Figma design to working website in 15 min

• (23:07) Demo: FigJam flowchart to a working game

• (31:30) A UX reviewer skill for design feedback

• (40:19) How to export code back to Figma as editable designs

• (45:10) Why most designers aren't adapting fast enough

I’m proud to partner with Replit

Replit’s Agent 4 is the best way for teams to work with AI agents. You can use it to:

1. Explore design variations on an infinite canvas

2. Build using multiple AI agents at once using a task board.

3. Generate beautiful slide decks, animations and more in one shot.

Try Agent 4 for 3 months free by using my code PYANG26 at checkout.

Get Replit for 3 Months Free

Top 10 takeaways I learned from this episode

1. If you use Figma, Figma MCP is the best way to go from design to code:

   1. Install. In your terminal, run “claude mcp add --transport http figma https://mcp.figma.com/mcp”

   2. Authenticate. Open Claude Code, type “/mcp” and then select Figma. It’ll open your browser for you to authenticate the MCP with your Figma account.

   3. Copy a Figma frame. Now go to one of your Figma designs and right click any frame or layer. Select “Copy link to selection” and then paste the link into Claude Code with the prompt: “Build this design.” It’s as simple as that.

2. Convert code back into editable Figma layers to explore more design variations. Here’s how to do this step by step after setting up Figma MCP:

Read more

Today, I want to share a new episode with Geoff Charles.

Geoff is the CPO of Ramp and runs one of the most AI-native orgs I’ve seen. He showed me an amazing Claude Code PM skill that his team uses to go from idea to product and shared live demos of Ramp’s internal AI agents for customer research, data analysis, and more. Geoff also shared 5 tactics Ramp followed to go from barely anyone using AI to non-engineers shipping production code.

Watch now on YouTube, Apple, and Spotify.

Geoff and I talked about:

• (00:00) "If you're not using Claude Code, you're probably underperforming"

• (04:45) Voice of customer agent (demo): 8 days of research in 8 minutes

• (07:57) Analyst agent (demo): Get insights and pull data using English

• (13:08) The best Claude Code PM skill I've ever seen

• (15:20) "50% of Ramp's code is written by AI. It'll probably be 80% soon."

• (16:38) Inspect agent (demo): Building a production feature in 5 min

• (28:21) The two directions the PM role is splitting into

• (34:05) Ramp's L0-L3 framework for getting every employee to build with AI

• (36:36) The AI interview question Ramp asks every candidate

• (39:15) "Management is probably dead...be the best builder in the world."

I’m proud to partner with Granola

Meeting notes are the most useful context for AI in any company. With Granola MCP, you can now access this context from Claude, ChatGPT, and any AI app:

1. Ask Cursor to create tickets for bugs discussed in standup

2. Have Claude update your Linear board directly from a planning meeting

3. Get ChatGPT to draft a follow-up from a sales call and push it to your CRM

I honestly couldn’t work without Granola, and the MCP just makes it more useful.

Try Granola Today

Top 10 takeaways I learned from this episode

1. Ramp’s product shaping Claude Code skill is one of the best PM skills I’ve seen. This skill turns Claude into a product thinking partner that pushes back on your ideas, runs parallel research, and outputs a clean spec. It works in 3 phases:

   1. Phase 1: Frame the problem. Claude pushes the PM with 7 questions including "What's the job to be done?", "Why now?", and "If we build this, what does it unlock?" If you can't defend your answers, Claude pushes back.

   2. Phase 2: Research. Claude launches 6-10 parallel agents to scan competitors, Gong calls, Zendesk tickets, and the codebase simultaneously. Each agent writes a markdown file that Claude then synthesizes into key patterns.

   3. Phase 3: Shape the spec. Claude converges on a design through conversation. The final spec is a 2-min read with context, design principles, requirements grounded in evidence, alternatives considered, and open questions.

I’ve updated the skill to remove Ramp-specific info so that any person or company can adopt it. Just copy and paste the 5,000+ character skill in the section below directly into Claude to set it up.

Read more

Today, I want to share a new episode with Tom Krcha.

Tom is the CEO of Pencil, one of the most insane AI design apps I’ve seen. Watching 6 AI agents design a beautiful app in real-time will genuinely blow your mind. Tom showed me how it all works under the hood (a simple JSON file?!) and how you can use Pencil to design right where you code in Cursor, Claude Code, and more.

Watch now on YouTube, Apple, and Spotify.

Tom and I talked about:

• ((00:00) Watch 6 AI agents design an app together

• (03:09) Demo: Designing a travel app with an AI agent swarm

• (08:20) Redesigning screens in different styles on the fly

• (13:20) The Pencil extension that turns Cursor into a design tool

• (15:07) One prompt to go from visual design to React website

• (19:00) Using design systems to keep your AI output consistent

• (22:02) From side project to 100K users in 8 weeks

• (27:44) Why vibe coding reminds Tom of the Flash era

• (30:05) Humanizing AI with cursors, craft, and personality

This episode is brought to you by… Linear

Linear lets AI agents help you in every step of your product development process — from reading customer conversations and auto-creating issues, to de-duping them against the backlog and routing them to the right team.

You can also tag the Linear agent directly in Slack to assign bugs and small features to other agents like Cursor and Codex.

Try Linear Now for Free

Top 10 takeaways I learned from this episode

1. Pencil lets up to 6 AI agents design together on a visual canvas using .pen files (which are just JSON). Here’s how to set up Pencil on each channel:

   1. App: Download from pencil.dev (Mac, Windows, Linux) — it’s free.

   2. Cursor: Install “Pencil” extension from the Extensions store.

   3. Claude Code: Open Pencil, run claude, type /mcp to verify connection.

2. Build your first design with swarm mode. After downloading Pencil, add your AI model (Claude 4.6 works best), turn on swarm mode, and prompt “Design an app to do X.” Then sit back and watch the magic.

Read more

Today, I want to share a new episode with Carl Vellotti.

Carl has gone deeper on Claude Code than any product leader that I know. He showed me exactly how to connect Claude Code to Google Workspace, Slack, Reddit, and Linear to get work done without opening any of these other apps. Watch as he demos how to prep for meetings, update tickets, and post Slack updates all from the terminal.

Watch now on YouTube, Apple, and Spotify.

Carl and I talked about:

• (00:00) Why you should connect Claude Code to your favorite apps

• (02:01) Google Workspace: Using Claude to prep for meetings

• (09:35) Linear: Creating tickets from PRDs

• (13:16) Slack: Sharing status updates from terminal

• (20:04) Reddit: Monitoring subreddit discussions

• (21:47) The daily-standup command that pulls from multiple tools

• (25:08) The folder setup Carl uses for his Claude Code OS

• (33:36) The consult-the-council skill that works with multiple AI agents

• (35:50) How to get Claude Code to generate system design diagrams

I’m proud to partner with Granola

Granola’s recipes feature pairs expert-crafted prompts with your meeting context to give you insights into your work.

One of my favorite recipes is Matt Mochary’s coaching recipe. It gives me feedback based on how I actually showed up in conversations that week.

Try Granola for Free

Top 10 takeaways I learned from this episode

1. Keep your Claude Code personal OS organized with this structure. Carl's setup gives Claude clear places to find and store everything:

   • /context - Company info, product docs, quarterly goals.

   • /projects - One sub-folder per initiative with PRDs, research, and more.

   • /templates - Reusable formats for PRDs, Slack updates, meeting notes.

   • /tools - Image generation (via Nano Banana) and other capabilities.

   • /workflows - Multi-step processes like content writing or research.

   • /_temp - Drafts and one-off docs that are temporary.

You can copy Carl's personal OS setup by visiting the GitHub link below. Simply paste the link into Claude Code and ask it to clone the repo to get the folder structure:

Read more

Today, I want to share a new episode with my friend, Nat Eliason.

Nat gave his OpenClaw bot, Felix, $1,000 to build its own business 3 weeks ago. Since then, it has made $14,718 by launching its own website, info product, and X account. Nat walked through exactly how he set up his OpenClaw bot to run its own business — from the 3-layer memory system, to multi-threaded chats, to security best practices.

Watch now on YouTube, Apple, and Spotify.

Nat and I talked about:

• (00:00) Meet Felix: The OpenClaw bot building its own business

• (03:49) “I’m going to sleep. Build a product that makes money.”

• (08:03) How to set up multiple OpenClaw chats to build 5 projects at once

• (11:06) How Felix is able to ignore prompt injections on X/Twitter

• (14:42) The wild story of how Felix ended up with $100K+ in crypto

• (17:24) The 3-layer memory system that makes it all work

• (22:14) Heartbeat, cron jobs, and delegating to Codex

• (26:41) Ask this question to make your OpenClaw bot more capable

• (32:14) Recap: how to set up your own bot to build a business

I’m proud to partner with Replit

Replit now makes beautiful videos for product launches, fundraise announcements, and explainers from simple text prompts. To try it out:

1. Go to Replit and select the “App” tab

2. Ask for “an animated video about…”, or use the dropdown selector under the prompt box & select “Animation”

It’s as simple as that. Try Replit Animation now for free via the link below.

Try Replit for Free

Top 10 takeaways I learned from this episode

1. Set up a 3-layer memory system for OpenClaw first. This is the single biggest unlock. From Nat: “Get the memory structure in first because then your conversations from day one will be useful.” Here’s what Felix uses:

   1. Layer 1: Knowledge graph. A ~/life/ folder using the PARA system (projects, areas, resources, archives). Stores durable facts about people and projects with summary files for quick lookups.

   2. Layer 2: Daily notes. dated markdown file for each day logging what happened. Your bot writes to this during conversations, then extracts important stuff into Layer 1 during nightly consolidation.

   3. Layer 3: Tacit knowledge. Facts about you like your communication preferences, workflow habits, hard rules, and lessons learned from past mistakes. This is what makes your bot feel like it actually knows you.

To set up all of the above, just copy and paste the 6,500+ character prompt in the section below into your OpenClaw bot. One of the most annoying parts about OpenClaw is it tends to forget things and I’ve found that Nat’s prompt significantly improves the bot’s memory.

Read more

Today, I want to share a new episode with Eno Reyes.

Eno is the co-founder of Factory and the most AI-native founder I know. He gave me a live demo of how he builds apps with AI agents, but what really blew my mind was his AI skill that writes PRDs, prioritizes features, and makes AI think like a senior PM on your team. Watch the interview to see him walk through it and I’ve also pasted the full skill below for paid subscribers to copy.

Watch now on YouTube, Apple, and Spotify.

Eno and I talked about:

• (00:00) What makes Droid different from other AI agents

• (03:46) Live demo: Building a speed reading app from meeting notes

• (08:11) The difference between spec mode and plan mode

• (12:04) How real engineers use AI agents vs vibe coders

• (16:33) Skills vs MCPs vs hooks: When to use each one

• (19:02) Eno's PM skill that completely blew my mind

• (22:46) Why Factory hires product engineers vs. PMs

• (27:09) How a 40-person team competes with Cursor and Anthropic

I’m proud to partner with…Linear

As coding agents take on more engineering work, a lot happens invisibly. Someone can go from a bug report in Slack to a shipped fix without creating any record of what happened. That’s fine for speed, but coordination gets harder as you scale.

Linear integrates directly with tools like Cursor and Codex so anyone can see what an agent is working on and who assigned the task. Product teams at OpenAI, Ramp, and Block all use Linear to collaborate with AI agents.

Try Linear Today

Top 10 takeaways I learned from this episode

1. Eno’s PM skill agent is genuinely the most impressive I’ve seen. It covers:

   1. Product principles and positioning. The agent reads Factory’s core beliefs about how they build product and how they position themselves in the market.

   2. The 11-star experience. The skill links to Factory’s description of its most compelling 11-star user experience borrowed from Airbnb’s Brian Chesky.

   3. PRD template and review rubric. The skill not only edits PRDs using Factory’s template but also scores each PRD and flags critical gaps.

   4. Prioritization framework. The skill can prioritize and trade-off features.

   5. Language guidance. The skill includes guidance on clear and concise copy.

Here’s the full 700 word PM skill for you to copy and paste into your favorite AI project or coding app. Just save it as a md file and replcae the links with your own:

Read more

Today, I want to share a new episode with Kieran Klaassen.

Kieran my favorite Claude Code power user and teacher. In our interview, he walked through his Compound Engineering system that makes Claude Code better every time you use it. This same system has been embraced by the Claude Code team and others. Kieran is like Morpheus introducing me to the matrix, so don’t miss this episode 🙂

Watch now on YouTube, Apple, and Spotify.

Kieran and I talked about:

• (00:00) The compound engineering loop: Plan, work, assess, compound

• (03:40) Live demo: The /workflows command to plan your app

• (13:25) How to use Claude Skills as just-in-time context

• (25:27) Why you should always ask Claude to ask you questions first

• (30:00) Live demo: Using Playwright MCP as your AI QA team

• (35:03) Code reviews by AI agents playing security, architect, and more

• (40:33) The LFG command: one prompt to go from 0 to production

• (46:39) Slash commands vs sub-agents vs skills — when to use each

I’m proud to partner with Granola

Meeting notes are the most useful context for AI in any company. With Granola MCP, you can now access this context from Claude, ChatGPT, and any AI app:

1. Ask Cursor to create tickets for bugs discussed in standup

2. Have Claude update your Linear board directly from a planning meeting

3. Get ChatGPT to draft a follow-up from a sales call and push it to your CRM

I honestly couldn’t work without Granola and the MCP just makes it more useful.

Try Granola Today

Top 10 takeaways I learned from this episode

1. Kieran’s compound engineering system makes Claude Code smarter every time you use it. Here's the 4-step loop:

   1. Plan. Sub-agents research your codebase, best practices, and framework versions in parallel before any code is written.

   2. Work. Claude asks clarifying questions first, then builds the feature and writes tests from the plan.

   3. Assess. Review agents check security, architecture, and code quality, then triage findings by priority.

   4. Compound. Capture learnings into docs that Claude reads next time. Simplest version: “add this to claude.md.”

The best part: Kieran packaged this entire system into a free Claude Code plugin with slash commands for each step. Install it here and try it yourself:

Read more

Today, I want to share a new episode with Peter Steinberger.

Peter is the creator of OpenClaw (formerly Molt - the name keeps changing 😅), the hottest AI right now with 2M visitors in a week. In our interview, Peter shared is personal favorite use cases including using Claw to check in to flights, control his home, and more. We also talked about his hot takes such as no plan mode or MCPs.

Watch now on YouTube, Apple, and Spotify.

Peter and I talked about:

• (00:00) “It’s like having a new weird friend that lives on your computer”

• (03:52) “It sent me a voice message but I never set that up”

• (15:06) “It watched my security camera all night and found this”

• (16:15) Using OpenClaw to check in flights, change lights, and adjust his bed

• (19:42) Why 80% of your phone apps will disappear

• (22:51) The agentic trap: Why fancy AI workflows produce slop

• (29:42) Peter’s AI coding hot takes: No plan mode, MCPs suck, and more

• (36:56) The way to learn AI is to play

I’m proud to partner with…Granola

If you’re in back-to-back meetings, you know how much work it is to take notes live and clean them up afterwards. That’s why I love Granola, the best AI meeting notes app in the market.

It captures everything automatically, lets me add my own notes inline, and formats takeaways exactly how I want them. No annoying bot joins your calls either.

Try Granola Now

Top 10 takeaways I learned from this episode

1. Peter’s AI workflow rejects most popular “best practices”:

   1. Default to Codex for coding (not Opus). Codex handles big codebases better with fewer mistakes and less handholding. Opus is great for personality.

   2. No plan mode. From Peter: “Plan mode was a hack for older models. I just write ‘let’s discuss’ and have a conversation.”

   3. No MCPs. “Most MCPs should be CLIs. The agent will try the CLI, get the help menu, and from now on we’re good.”

Read more

Today, I want to share a new episode with Logan Kilpatrick.

Logan is the Product Lead for Google AI Studio. I got him to give me an inside look at how he uses AI Studio to build AI Studio (very meta) and how his team ships at startup speed inside Google. I’ve been using AI Studio non-stop for prototyping and it has genuinely made my PM job more fun, so don’t miss this tutorial.

Watch now on YouTube, Apple, and Spotify.

Logan and I talked about:

• (00:00) Tour of Google AI Studio's Build mode

• (06:29) Live demo: Building a social media content generator

• (09:31) How Logan uses AI Studio to build AI Studio

• (11:34) Cloning the AI Studio UI in 68 seconds

• (12:58) Getting AI to show you 5-6 design options in one UI

• (17:20) Live demo: Building a restaurant finder with Google Maps

• (21:12) Using annotate mode to give visual feedback

• (34:09) "There's one mode and the mode is we ship fast"

• (36:00) What Logan looks for when hiring PMs

This episode is brought to you by…Box

Getting structured data out of contracts, invoices, and scanned documents usually means time-consuming manual work but Box Extract uses agentic AI to transform how businesses analyze their data.

Powered by leading AI models from Google, Anthropic, and OpenAI, Box Extract pulls out critical information and saves it in Box, making it easier than ever for enterprises to quickly access actionable insights. No custom model training required.

Learn More about Box Extract

Top 10 takeaways I learned from this episode

1. Clone existing UIs instead of prompting from scratch. Logan’s go-to workflow is screenshotting his existing AI Studio interface, pasting it into AI Studio, and saying “clone this UI exactly.” He then prototypes new features on top of this template.

2. Explore multiple UI options in a single view. Instead of building separate prototypes, he asks the AI to add a button that toggles between design variations in one UI. Simply prompt AI Studio: “Add a widget so I can click through these styles: [describe 3-5 different styles].”

Read more

Today, I want to share a new episode with Sumeet Marwaha.

Sumeet is the Head of Data at Brex and came personally recommended by the Claude Code team. In our episode, he showed me how to use Claude Code to build an AI data analyst that can answer questions and deliver insights without any SQL queries. If you’re tired of analyzing data manually, then this interview is a must-watch.

Watch now on YouTube, Apple, and Spotify.

Sumeet and I talked about:

• (00:00) How to make Claude Code your data analyst

• (03:04) Analyzing data with AI: Monitor → Explore → Craft → Impact

• (10:23) Live demo: Building a startup funding MCP with 3 queries

• (21:10) Context management: Why your data agent gets confused

• (26:04) How to connect Claude to Slack and Drive for context

• (35:00) Demo: Predicting which AI startups will get Series B funding

• (41:32) Brex stats on which AI coding tools are actually winning

This episode is brought to you by…Glue

Team chat hasn't changed in years—it's still mostly a place to talk about work, then you switch tabs to actually do it.

Glue is the first multiplayer MCP client that lets your chat connect directly to tools like Linear, Sentry, Notion, and Vercel. Teams can log issues, update projects, or check analytics without leaving the conversation. Glue puts context-aware AI at the core of your team’s workflow, making every chat thread more useful.‌

Try Glue Now for Free

‍‍‍‌‍‌Top 10 takeaways I learned from this episode

1. Set up Claude Code to augment every step of data analysis:

   1. Monitor: Run your queries automatically and flag changes.

   2. Explore: When metrics look off, pull context from Slack, Linear, and code.

   3. Craft: Help you tell a good story by running investigations and filling gaps.

   4. Impact: Size potential impact by reviewing past experiments and code.

2. The #1 mistake: Blowing up the context window. A query that returns 10,000+ rows can fill your context in one step. To avoid this, add instructions telling Claude to manage tokens, use skills to enforce limits like “limit 50 on joins,” and add 2-3 minute timeouts that trigger query rewrites.

Read more

Today, I want to share a new episode with my friends Tal and Aman.

Tal and Aman are experienced AI PMs so I put all of us on the spot to share our favorite AI product workflows — from writing strategy docs to prototyping with Google AI Studio to building a personal OS with Claude Code. Watch this episode if you want to see 5 real no-BS AI product workflows in 50 minutes.

Watch now on YouTube, Apple, and Spotify.

We talked about:

• (00:00) Our best AI workflows for product work

• (01:13) Demo 1: Writing strategy docs with Claude Projects

• (10:21) Demo 2: Prototyping a new feature with Google AI Studio

• (17:10) Demo 3: Building an AI thinking partner with Obsidian + Cursor

• (24:06) Demo 4: Managing tasks with Linear MCP

• (29:01) Demo 5: Building a personal OS with Claude Code and skills

• (40:06) Context engineering 101 from Aman

• (48:54) Summary and how you can start today

I’ll also share Aman’s personal OS GitHub repo for you to clone at the end of this post.

This episode is brought to you by…Korey

The biggest slowdown in product development isn’t your code. It’s your process. Specs, tickets, updates, and keeping everyone in sync can all take time away from actual development.

Korey is an AI agent that handles the busywork of product development. Korey turns rough notes into dev-ready specs, breaks work into tasks, and can even hand things off to coding agents like Cursor or Devin with full context intact. Teams using Korey report 48% time saved on spec creation and scoping.

Try Korey AI for Free

Top 10 takeaways I learned from this episode

My AI workflows: Co-creating strategy and prototyping in Google AI Studio

1. Prototype before you write the PRD. You can now build a prototype and test with real users in less time than it takes to create a PRD or design. I demoed exactly how to do this by prototyping a new feature for Google AI Studio. “Build a prototype first and test with users, then make the PRD once you have direction.”

2. Work with AI to create your product plan. Create an AI project and upload your strategy template and reference materials. Then ask AI to draft your document and iterate on it together. Keep your document to one page and add a TLDR paragraph at the top so readers won’t use AI to summarize it.

Read more

Today, I want to share a new episode with Teresa Torres.

Teresa is a well-known product coach and author who runs her entire life and business using two Claude Code terminals and a note taking app. It was genuinely mind blowing to watch her demo using Claude Code to manage her to do list, delegate her research, write content, and much more.

Watch now on YouTube, Apple, and Spotify.

Teresa and I talked about:

• (00:00) Why Teresa uses Claude Code to run her life

• (03:00) Live demo: The "today" command that builds Teresa's daily to do list

• (07:00) Working with Claude Code to brainstorm tasks and ideas

• (14:00) Live demo: Writing a blog post together using plan mode

• (21:00) How Claude does SEO keyword research for blog posts

• (26:00) Why Teresa still writes every word herself (but 10x faster)

• (30:00) Pro tips to manage context so Claude doesn't "get dumber"

• (36:00) The 3-layer context system: global, project, and reference files

• (44:00) 3 tips to get started with Claude Code without feeling overwhelmed

This episode is brought to you by…Bolt

The bottleneck to create great AI apps isn’t the UI, it’s the backend. Databases, auth, and hosting are still a pain to set up. Bolt v2 bundles all of that directly into the browser using their WebContainers tech. It also supports Claude Code in a web UX that’s more approachable than a command line tool. Try using Bolt to accelerate your product development loops today.

Try Bolt for free or use the code PETERYANG to get 25% off the team plan (for the first month and new users only). Code expires on January 31.

Get 25% Off Bolt's Team Plan Now

Top 10 takeaways I learned from this episode

1. Claude Code is only as good as what it knows about you. “Every morning, I type ‘/today’ into Claude Code and watch it generate my to-do list.” This works because Teresa built a system of context files that tell Claude about her business, preferences, and workflows.

2. Give Claude 3 layers of context — global, project-specific, and reference files. Teresa’s global Claude.md holds universal preferences like “always plan before acting” and how she likes to get feedback. She also has project folders like “tasks” and “writing” that each have their own Claude.md (e.g., her preferred writing style). Finally, she has reference files that hold business details (e.g., her business, products, and team) that Claude can decide to pull in when relevant.

Read more

Today, I want to share a new episode with Yana Welinder.

Yana is Head of AI at Amplitude and a good friend. We had some real talk about how to stay scrappy inside a big company, including how to avoid decision by committee and endless internal debates. Yana also demoed her favorite AI workflows to triage her emails and aggregate customer feedback. I think you’ll love our banter 😅

Watch now on YouTube, Apple, and Spotify.

Yana and I talked about:

• (00:00) “By the time you’ve debated 2 ideas, I’ve already shipped 10”

• (03:21) Think “how would I run this company?” not “what’s my job?”

• (05:22) Why we banned decisions by committee

• (08:25) Cross-functional now means doing the work, not coordinating it

• (11:22) Why frustrated users can become your biggest advocates

• (15:19) Live demo: Using ChatGPT Atlas to triage emails

• (24:38) AI is still terrible at prompting (and what you can do about it)

• (28:48) Live demo: Combining qualitative feedback with quantitative data

• (37:38) Why AI analytics is lagging (and what needs to change)

🔥 Join my private Slack community with 750+ other AI builders

We’ve set up channels to share AI workflows, discuss industry news, rant about PM life, and (most importantly) post memes. I’ll share more raw tips like the one above as well. Come hang out with us during the holidays 🙂

Upgrade to Get Instant Access

Top 10 takeaways I learned from this episode

1. “By the time you’re done debating 2 ideas, I’ve already executed on 10.” Amplitude’s CEO banned decisions by committee so everyone can ship faster. Every project has a clear DRI (directly responsible individual) who takes inputs from others but owns their decision and outcome.

2. Frustrated users can be your best advocates if you fix their issues fast. “The reaction of a user who had initial frustration, reported it, and you fixed it within 15 minutes is going to be so much better than the user who was just happy the first time.” Speed is what leads to polish.

Read more