Lenny's Newsletter

Author, Lenny’s Newsletter and Lenny’s Podcast

Self Employed

Investor in 150+ companies including Figma, Linear, Substack, Vanta, Anduril, Whatnot, Webflow, Descript, Levels, Mindbloom, Reforge, Zip, Stytch, Runway, Census, Pachama, and many more: https://www.lennyrachitsky.com/investing

Angel Investor

Airbnb

Led the team responsible for driving consumer supply growth. This included:

* Performance marketing
* Conversion
* Referrals
* Awareness and consideration
* Re-engagement
* Retention
* Core host products

Previously, led three teams driving Instant Book Growth (grew usage from 5% to over 80%), guest booking conversion, and building new tools for hosts (e.g. dashboards, calendar, guest controls, publishing, messaging).

Also supported strategy of the Anti-Discrimination team, and helped on a few side-projects including  work with The Malala Fund.

Product Lead, Supply Growth

Drove growth through improvements to guest booking conversion, host experience (acceptance rate, response rate, more), and Instant Book.

Drove host quality through launching programs such as Superhost, Mentors, Host Dashboard, host quality standards, revamp of reviews system, and more.

Built Airbnb's first host community platform.

Built the first attempt at extending Airbnb beyond the home (now Airbnb Experiences).

Product Lead, Guest Conversion and Host Quality

Localmind

Acquired by Airbnb in 2012.

Localmind was an early location-based consumer app. We leveraged location data from Foursquare, Facebook, and Gowalla to capture location expertise of locals, enabling Localmind users to get real-time answers to questions about places they are thinking about visiting.

https://angel.co/localmind
http://ireport.cnn.com/docs/DOC-574061
https://techcrunch.com/2012/12/13/airbnb-acquires-localmind/

Co-Founder, CEO

Webmetrics/Neustar

Focused on innovations in web performance, cloud, and web operations, looking 2-5 years down the road. Prototype, research, and build. Also included business development with partners.

Engineer, Head of R&D

Managed the entire engineering department of Webmetrics. This included building the team, building the product, and maintaining a 24/7 operations culture. During this period we were acquired by Neustar, and the team grew 10x.

Sr. Manager of Engineering

Webmetrics

Built the core product offering for Webmetrics, a website monitoring and load testing product.

Acquired by NeuStar

Lead Engineer

LA.com

Basic web development for all the LA.com and sister properties (e.g. hawaii.com, texas.com, more)

Web Developer

I write Lenny's Newsletter (the #1 business newsletter on Substack), and host Lenny's Podcast (top ten tech podcast globally). Previously, I spent seven years at Airbnb leading supply growth, conversion, trip quality, and community, and before Airbnb, I was an engineer and a founder (exited to Airbnb).

My biggest takeaways from Ethan Smith on how to win at AEO (i.e. get ChatGPT to recommend your product):

1. Being mentioned most often beats ranking first. In Google, the #1 blue link wins. In ChatGPT, the answer summarizes multiple sources—so appearing in five citations beats ranking #1 in one. Ethan’s strategy: get mentioned on Reddit, YouTube, blogs, and affiliates. Volume of mentions matters more than any single placement.

2. LLM traffic converts 6x better than Google search traffic. Webflow saw this dramatic difference because users who come through AI assistants have built up much more intent through conversation and follow-up questions, making them highly qualified leads.

3. Early-stage startups can win at AEO immediately, unlike with SEO. Traditional SEO requires years of domain authority. But a brand-new Y Combinator company mentioned in a Reddit thread today can show up in ChatGPT tomorrow. The playing field is finally level.

4. The long tail of AEO is 4x bigger than SEO. People ask ChatGPT questions with 25 or more words (vs. 6 in Google). Ethan found gold in queries like “Which meeting transcription tool integrates with Looker via Zapier to BigQuery?”—questions that never existed in search but are perfect for AI. Own these micro-niches.

5. Reddit is proving to be the kingmaker for AI visibility. ChatGPT trusts Reddit because the community polices spam better than any algorithm. Ethan’s exact playbook: make one real account, say who you are and where you work, give genuinely helpful answers. Five good comments can transform your visibility. No automation, no fake accounts—just be helpful.

6. YouTube videos for “boring” B2B terms are a gold mine for AEO. Nobody makes videos about “AI-powered payment processing APIs”—which is exactly why you should. While everyone fights over “best CRM software,” the high-value, zero-competition long tail is wide open in video.

7. Your help center is now a growth channel. All those “Does your product do X?” questions flooding ChatGPT can be answered by help-center pages. Move them from subdomain to subdirectory, cross-link aggressively, and cover every feature question. Ethan calls this the most underutilized opportunity in AEO.

8. January 2025 was the inflection point in AEO growth. That’s when ChatGPT made answers more clickable (maps, shopping cards, citations) and adoption exploded. Webflow went from near zero to 8% of signups from AI. This channel is accelerating faster than any Ethan’s seen in 18 years.

9. The AEO playbook: (1) Find questions from competitor paid search data, (2) set up answer tracking, (3) see who’s showing up as citations, (4) create landing pages answering all follow-up questions, (5) get mentioned offsite via Reddit/YouTube/affiliates, (6) run controlled experiments, (7) build a dedicated team. This exact process is driving real results at scale.

Lenny Rachitsky

Deeply researched product, growth, and career advice

Everyone should be using Claude Code more

PMs, marketers, designers, founders, parents. Everyone.

The trick is to forget that it’s called Claude Code and instead think of it as Claude Local or Claude Agent. It’s essentially a super-intelligent AI running locally, able to do stuff directly on your computer—from organizing your files and folders to brainstorming domain names, summarizing customer calls, to enhancing image quality, creating Linear tickets, and so much more.

Here are 50 creative ways non-technical people are using Claude Code in their work and life, to inspire your own thinking. This list includes my own favorite use cases, and the best examples y’all shared with me:

1. Finding high-quality leads, from Jeff Lindquist
“I literally just typed: look at what I’m building and identify the top 5 companies in my area that would be good for a pilot for this. Then I go to LinkedIn and message them. If it’s not clear, I do this in the source directory of the code of my app so the first thing it does is figure out what it is that I’m building.”

2. Figuring out why your computer is running slow, from Anthony Roux
“I sometimes use Claude Code for system diagnostics when my Mac slows down. I use it to check load averages, memory pressure, disk space, stuck processes, and swap activity, then it dives deeper to find what’s actually causing issues. It can calculate cache sizes, check Docker usage, find Time Machine snapshots eating space, etc."

3. Noticing when you’re avoiding conflict, from Dan Shipper
“I download all of my meeting recordings, put them in a folder, and ask Claude Code to tell me all of the times I’ve subtly avoided conflict.”

4. Clearing space on my computer
Prompt: “How can I clear some storage on my computer?” I then discuss my options.

5. Brainstorming domain names, from Ben Aiad
“Just describe your project, and it’ll suggest creative options across multiple TLDs (.com, .io, .dev, etc.) while verifying what’s actually available to register.”

6. Improving the image quality of screenshots
Prompt: “Improve the image quality of [filename]”. I used this many times for the screenshots in this post.

7. Downloading YouTube videos
Prompt: “Download this YouTube video: [URL]”. Then I ignored all the warnings 🤫

8. Downloading all of the images embedded inside a Google Doc
Prompt: “Download all of the images in high-res from this Google Doc: [URL]”. This paired well with item #2.

9. Cleaning up messy invoice files, from Martin Merschroth
“I use Claude Code to sort my invoices for taxes. It reads each file in a messy folder, renames it to ‘YYYY-MM-DD Vendor - Invoice - ProductOrService.pdf’, and moves it into the right folder.”

Here's the whole collection (bookmark it for later), including a quick 3-step guide to installing Claude Code so you can try this stuff at home: https://lnkd.in/g_wqdx36

Open article: Everyone should be using Claude Code more by lennysnewsletter.com

Everyone should be using Claude Code more

Trend I'm following: evals quickly becoming a must-have skill for product builders (and AI companies).

It's the first new hard skill in a long time that PMs/engineers/founders have had to learn to be successful. The last one was maybe SQL, and Excel?

Evals have been one of the most common themes in my podcast conversations, when I ask guests what skills people need to develop to be successful with the rise of AI.

Also:
- Garry Tan: "Evals are emerging as the real moat for AI startups."
- Kevin Weil: "Writing evals is going to become a core skill for product managers."
- Mike Krieger: "Writing evals is probably the most important thing right now."
- Sarah Guo: "Evals = your new marketing."
- Greg Brockman: "Evals are surprisingly often all you need."
- Brendan Foody (CEO of arguably the fastest growing company in history, quote below)

More to come.

My biggest takeaways from my chat with Julie Zhuo:

1. Most management skills transfer directly to working well with AI. And we're all becoming managers—of AI. Management is fundamentally about achieving outcomes with resources: “You have a North Star, you have a vision, and you’re trying to figure out how to use the resources that you have to get that thing done.” With AI, the principles remain the same—you need clear goals, an understanding of your tools’ strengths, and effective processes.

2. Every strength is also a weakness. Julie shares how her thoughtfulness (strength) was connected to her slowness to speak up in meetings (weakness). “What you realize is these are two sides of the same coin.” Rather than trying to eliminate weaknesses, understand how they relate to your strengths and learn when each serves you best.

3. “Diagnose with data, treat with design.” Data helps identify problems and opportunities, but it won’t tell you what to build. “Data is not a tool that’s going to tell you what you should build or what the solution is ... it can tell you if you have a problem and where that problem or opportunity might be, but you still need to go back and undergo a very creative process.”

4. AI makes emotional regulation skills more important, not less. When asked what she teaches her children, knowing AI will be part of their future, Julie focuses on emotional regulation: “We’re still human. We still have the same hardware that humans have had for thousands of years, and that’s not changing even as the tools and the environment around us change.”

5. Understanding yourself is the foundation of managing others well. Julie wanted this to be chapter 1 of her book (the publishers pushed it to chapter 5). “I really do fundamentally believe this, because all of us have things that we’re strong at and things that we’re weak at.” She introduces the concept of “dimensionality”—viewing yourself across infinite dimensions rather than as wholly good or bad.

6. New managers need to have a POV of their own. Julie emphasizes that middle managers can’t just pass down orders: “If you don’t really believe in what you’re doing and you’re just kind of parroting the thing that got passed through the organization, it’s very hard for you to then help other people see what that magic is.” 

7. The rate of change is accelerating, requiring managers to be “sturdy while flexible.” Julie uses the metaphor of a willow tree—sturdy but with flexible branches that bend in storms. “I think today management is really about this idea ... and that is a very hard thing to pull off.”

8. The danger of AI is making life too comfortable. Julie worries that AI might make it too easy to avoid challenges: “You can shortcut relationships ... you can shortcut hard feelings because now you can just watch TikTok instead of actually dealing with the very difficult emotion.” She teaches her children to still seek challenges despite having powerful tools.

My top takeaways from Google's head of search Robby Stein:

1. The next year of AI products will establish user habits for many years. People are building their new habits right now, like how quickly everyone started relying on ChatGPT. This creates incredible urgency because whoever captures these habits now will have a lasting advantage. Google recognized they couldn’t let users develop the habit of going elsewhere for AI-powered answers. This is the critical window for establishing how people will search and find information for the next decade.

2. Choose clarity over cleverness. Using standard icons and familiar patterns gives you enormous leverage. Creating a custom camera icon that looks “mostly like AI” confuses users. Simple naming matters too—changing “Favorites” to “Close Friends” dramatically increased how many people users added to their lists. When users instantly understand what something does, you get much more adoption.

3. Great products require relentless dissatisfaction with the status quo. Successful product leaders constantly question why things work the way they do, down to tiny frustrations most people accept. One example: a sticker that tears a fruit’s peel when removed. This mindset of noticing and refusing to tolerate small annoyances drives breakthrough improvements.

4. When users hack your product, they’re showing you what to build. Instagram users created multiple fake accounts to share privately with different groups—this workaround signaled an unmet need that eventually became Close Friends. Similarly, Google saw people typing “AI” at the end of searches to trigger AI responses, revealing demand for AI Mode. Pay attention to these signals.

5. Understand the job people hire your product to do, not just what features they ask for. Instagram’s Close Friends wasn’t about creating lists—it was about feeling connection through DMs. Understanding this emotional job helped the team realize users needed 20 to 30 people on their list, not 2 or 3, to ensure someone would respond. Study the exact moment someone first decides to use your product—that’s where the most critical insights live.

6. Small usability details make copied features feel native. Instagram Stories succeeded not just by copying Snapchat’s format but by adding key differences: letting users upload from their camera roll, adding a pause button, and using different creative tools. When adding major new features to mature products, give them their own distinct space rather than modifying what already exists.

7. The “lean startup” mentality can backfire—some breakthroughs need substantial resources. Keeping teams too small for too long can actually slow progress. Instagram’s Close Friends took two years partly because the team stayed too lean. While lean teams work well for early validation, products that require technical breakthroughs need enough resources to build real momentum and get good enough.

From managing people to managing AI with Julie Zhuo

In a very special episode, my first-ever podcast guest returns (3 years and over 30M downloads later!) to explain why everyone's about to become a manager—of AI. Spoiler: The skills that make you a great manager also make you great at using AI.

In our conversation, we discuss:
🔸 The three core manager skills that translate directly to working with AI tools
🔸 Why her startup has zero PMs
🔸 How her team at Sundial uses AI to learn new skills 10x faster
🔸 The “diagnose with data, treat with design” framework for balancing instinct and data
🔸 How to give feedback that actually lands—including Julie’s exact script for difficult conversations
🔸 What Julie’s teaching her kids about an AI future (hint: it’s not coding or STEM)

Listen now 👇
• YouTube: https://lnkd.in/gmHYUfwX
• Spotify: https://lnkd.in/gjRSa4bd
• Apple: https://lnkd.in/gVRYW6hc

Thank you to our wonderful sponsors for supporting the podcast: 
🏆 Mercury—The art of simplified finances: https://mercury.com/
🏆 DX—The developer intelligence platform designed by leading researchers: http://getdx.com/lenny
🏆 PostHog—How developers build successful products: https://posthog.com/lenny

In a rare interview, the growth 🐐 behind Duolingo, Grammarly, and Chess.com shares everything he's learned about growing consumer products.

Albert Cheng and I discuss: 
🔸 What good retention looks like for a consumer subscription app in 2025
🔸 How showing premium features to free users doubled Grammarly’s upgrades to paid plans
🔸 How to use the explore-exploit framework to find new growth opportunities
🔸 Why “reverse trials” work better than time-based trials
🔸  The three pillars of successful gamification: core loop, metagame, and profile

Listen now 👇
• YouTube: https://lnkd.in/gyd4S_iC
• Spotify: https://lnkd.in/gfS3-5_J
• Apple: https://lnkd.in/gG6DbQne

Thank you to our wonderful sponsors for supporting the podcast: 
🏆 Vanta — Automate compliance. Simplify security: https://vanta.com/lenny
🏆 Atlassian Jira Product Discovery — Confidence to build the right thing: https://lnkd.in/g6N-tMTy
🏆 Miro — A collaborative visual platform where your best work comes to life: https://miro.com/lenny

Hamel H. and Shreya Shankar's online course—AI Evals for Engineers & PMs—is the #1 highest-grossing course on Maven, and consistently brings in large groups from all of the major AI labs.

This is because they teach something crucial: how to build evaluations that actually improve your product, not just generate vanity dashboards.

Over the past two years, Hamel and Shreya have played a major role in shifting evals from being an obscure, mysterious subject to one of the most necessary skills for AI product builders.

After training more than 2,000 PMs and engineers, and leaders at over 500 companies, they’re now sharing their complete playbook—the same methodology taught at OpenAI, Anthropic, and other leading labs. 

You’ll learn how to leverage error analysis to understand where your AI product breaks, build robust evals you can trust, and create a continuous improvement flywheel that catches regressions before they ship.

Check it out: https://lnkd.in/g6W2xZXq

Limited-time offer: Exclusively for my readers, get 35% off Hamel and Shreya's course by using code LENNYSLIST at checkout. This is the largest discount they've ever offered on their course. I highly recommend you hop on this asap. Enrollment closes in 2 days. Register here: https://bit.ly/4myp27m

Thank you for sharing this gold with us, Hamel and Shreya 🙏

After introducing the Product Pass a couple of months ago, the most common question I get—other than “Wait, is this for real??”—is how I and others use these tools. So I’ve put together a short 2-part series about how I use each tool, what I love about it, and what you can do with it.

This week I’ll cover Replit, Warp, Linear, Wispr Flow, Gamma, Magic Patterns, Descript, and Mobbin. 

Next month I’ll cover Lovable, bolt.new, n8n, Granola, Superhuman, Raycast, Perplexity, and ChatPRD.

My goal here isn’t to sell you the products (you already get them for free as a paid subscriber!) but to help you get the maximum value out of your paid subscription.

Check it out: https://lnkd.in/guWYsHQj

Proud of my latest vibe-coded app: Download all of the images inside a Google Doc super easily

Prompts:
- "Make an app that takes a Google Docs URL (that's publicly available) and returns downloadable hi-res images of all the images in the doc."
- "Make the design of the page look ASCII art style"
- "When you click 'Download all' make that a zip file of the images vs. each image downloading individually."

Link: https://lnkd.in/grNMMTPR

Julie Zhuo's #1 piece of advice for new managers: Have a point of view.

Julie wrote the bestselling book "The Making of a Manager," and this is the most common pitfall she keeps seeing new managers fall into:

"Managers don't pay enough attention to what their true belief is. They feel like they need to be soldiers. They get orders, and they have to execute them. 

Watching your conviction is really important, particularly since you're not the founder of the company. As a middle manager, you didn't create the vision, but you are in some ways expected to execute it. You have to really check in with yourself on it. If you don't feel good about it, then it's not gonna be very likely that the project's going to succeed.

If you don't really believe in what you're doing, or you're just kind of parroting the thing that got passed through the organization, it's very hard for you to then be able to help other people see what that magic is. Or to be actually really effective as a person who can hold that vision and that purpose."

Because if you don't really believe in what you're doing, and or you're just kind of parroting the thing that got passed through the organization, it's very hard for you to then be able to help other people see what that magic is. Or to be actually really effective as a person who can hold that vision and that purpose."

If feedback is a gift, why is it so hard to receive? And give?

It’s because no one taught us how to give feedback correctly.

Through thousands of feedback conversations and hundreds of hours of research, today's guest author, Jack Cohen developed an evidence-based, immediately applicable framework for giving feedback that he calls GAIN. As Jack puts it, “GAIN is both a useful acronym and the core of the philosophy.”

It's profoundly more effective and inspiring to frame feedback based on the results we want to move toward (the *gain*) instead of focusing only on what we want to move away from (the pain).

This guide is essentially a how-to for Radical Candor, and the most specific (and easy-to-remember) framework for giving great feedback that you’ll find anywhere.

The post includes templates, AI tools to practice, specific phrases for tough situations, and how to handle resistance: https://lnkd.in/gv74v743

Share this with your team and reports to start getting better feedback. 

Here's the framework:

G - Goal: Open with the future impact you both want, not the current problem you want to avoid.
- Instead of: "Your sloppy handoffs are frustrating"
Try: "I want us to ship faster and reduce handoff friction"

A - Actions & I - Impacts: Name specific behaviors you observed and their effects. Zero judgments. Critical: acknowledge your own contribution too.
- Instead of: "You're controlling and don't trust people"
- Try: "You're on every sales call and in all the Slack channels, and I can see how exhausting that must be. When you check in before our agreed timeframes, I stop what I'm working on to respond, which leads to context-switching that slows down delivery"

N - Next: Close with concrete commitments: Who will do what by when. Ask for their ideas first, then make specific requests that are easy to say no to.
→ "Can you include that context next time?"
→ "Let's check in Friday to see how this experiment goes"

Why this works: Research shows framing feedback around potential gains (vs. avoiding pain) leads to 4x more action and significantly better results. It activates approach mode instead of threat mode. It activates curiosity instead of defensiveness.

Learn more: https://lnkd.in/gv74v743

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