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BREAKING: I'm partnering with @SpaceXAI to give all Lenny's Newsletter annual subscribers a free month of Grok Bot 💥 (included in Cursor Pro+)

This is the first time @SpaceXAI has offered a deal like this to anyone, and I'm thrilled to make this amazing product accessible to more people.

If you're already a paid subscriber, grab your deal here (search for "Grok"): https://www.lennysproductpass.com/

If not, subscribe here and look for the Product Pass link in your welcome email: https://www.lennysnewsletter.com/subscribe

I've been hooked on Grok @Bot since before it came out, and my usage has only gone up. Seriously, it's really really good.

Some of my favorite use cases right now:
+ After I record a podcast, taking a first pass at key takeaways and promotion ideas
+ Automatically adding school events to the calendar
+ Triaging support emails (saves me hours!)
+ Suggesting things I can do to be happier by analyzing my emails, calendar, and Slack
+ Landing me great IMAX Odyssey tickets 🙌

Grab your free month of Grok Bot here (search for Grok): https://www.lennysproductpass.com/
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lennysan
BREAKING: I'm partnering with @SpaceXAI to give all Lenny's Newsletter annual subscribers a free month of Grok Bot 💥 (included in Cursor Pro+) This is the first time @SpaceXAI has offered a deal like this to anyone, and I'm thrilled to make this amazing product accessible to more people. If you're already a paid subscriber, grab your deal here (search for "Grok"): https://www.lennysproductpass.com/ If not, subscribe here and look for the Product Pass link in your welcome email: https://www.lennysnewsletter.com/subscribe I've been hooked on Grok @Bot since before it came out, and my usage has only gone up. Seriously, it's really really good. Some of my favorite use cases right now: + After I record a podcast, taking a first pass at key takeaways and promotion ideas + Automatically adding school events to the calendar + Triaging support emails (saves me hours!) + Suggesting things I can do to be happier by analyzing my emails, calendar, and Slack + Landing me great IMAX Odyssey tickets 🙌 Grab your free month of Grok Bot here (search for Grok): https://www.lennysproductpass.com/

"Using coding agents well is taking every inch of my 25 years of experience as a software engineer." Simon Willison (@simonw) is one of the most prolific independent software engineers and most trusted voices on how AI is changing the craft of building software. He co-created Django, coined the term "prompt injection," and popularized the terms "agentic engineering" and "AI slop." In our in-depth conversation, we discuss: 🔸 Why November 2025 was an inflection point 🔸 The "dark factory" pattern 🔸 Why mid-career engineers (not juniors) are the most at risk right now 🔸 Three agentic engineering patterns he uses daily: red/green TDD, thin templates, hoarding 🔸 Why he writes 95% of his code from his phone while walking the dog 🔸 Why he thinks we're headed for an AI Challenger disaster 🔸 How a pelican riding a bicycle became the unofficial benchmark for AI model quality Listen now 👇 t.co/wlEIyOehU8

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lennysan
"Using coding agents well is taking every inch of my 25 years of experience as a software engineer." Simon Willison (@simonw) is one of the most prolific independent software engineers and most trusted voices on how AI is changing the craft of building software. He co-created Django, coined the term "prompt injection," and popularized the terms "agentic engineering" and "AI slop." In our in-depth conversation, we discuss: 🔸 Why November 2025 was an inflection point 🔸 The "dark factory" pattern 🔸 Why mid-career engineers (not juniors) are the most at risk right now 🔸 Three agentic engineering patterns he uses daily: red/green TDD, thin templates, hoarding 🔸 Why he writes 95% of his code from his phone while walking the dog 🔸 Why he thinks we're headed for an AI Challenger disaster 🔸 How a pelican riding a bicycle became the unofficial benchmark for AI model quality Listen now 👇 https://t.co/wlEIyOehU8

How Anthropic’s product team moves faster than anyone else I sat down with @_catwu, Head of Product for Claude Code at @AnthropicAI, to get a peek into their unprecedented shipping pace, how AI is changing the PM role, and how to be the right amount of AGI-pilled. We discuss: 🔸 How Anthropic’s shipping cadence went from months to weeks to days 🔸 The emerging skills PMs need to develop right now 🔸 Why you should build products that don't work yet—then wait for the model to catch up 🔸 Why a 95% automation isn't really an automation 🔸 Cat’s most underrated AI skill (introspection) 🔸 What Cat actually looks for when hiring PMs now (hint: it's not traditional PM skills) Listen now 👇 t.co/uymmT55Nq6

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lennysan
How Anthropic’s product team moves faster than anyone else I sat down with @_catwu, Head of Product for Claude Code at @AnthropicAI, to get a peek into their unprecedented shipping pace, how AI is changing the PM role, and how to be the right amount of AGI-pilled. We discuss: 🔸 How Anthropic’s shipping cadence went from months to weeks to days 🔸 The emerging skills PMs need to develop right now 🔸 Why you should build products that don't work yet—then wait for the model to catch up 🔸 Why a 95% automation isn't really an automation 🔸 Cat’s most underrated AI skill (introspection) 🔸 What Cat actually looks for when hiring PMs now (hint: it's not traditional PM skills) Listen now 👇 https://t.co/uymmT55Nq6
"Using coding agents well is taking every inch of my 25 years of experience as a software engineer, and it is mentally exhausting.

I can fire up four agents in parallel and have them work on four different problems, and by 11am I am wiped out for the day.

There is a limit on human cognition. Even if you're not reviewing everything they're doing, how much you can hold in your head at one time. There's a sort of personal skill that we have to learn, which is finding our new limits. What is a responsible way for us to not burn out, and for us to use the time that we have?" @simonw
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"Using coding agents well is taking every inch of my 25 years of experience as a software engineer, and it is mentally exhausting. I can fire up four agents in parallel and have them work on four different problems, and by 11am I am wiped out for the day. There is a limit on human cognition. Even if you're not reviewing everything they're doing, how much you can hold in your head at one time. There's a sort of personal skill that we have to learn, which is finding our new limits. What is a responsible way for us to not burn out, and for us to use the time that we have?" @simonw

Automation is a lie. CLIs are over. The SaaSpocalypse is dumb. A year ago @danshipper came on the podcast to predict where AI was heading. He was remarkably right—including the call that everyone was sleeping on Claude Code. Dan has a unique lens into where things are going because his team at @every is possibly the most AI-pilled group of people in tech. I always learn a ton talking to Dan. So I brought him back for round two. We'll score these in exactly a year: 🔸 Every company will have one “super-agent” in Slack. 🔸 Codex and Claude Code will become the new operating system for knowledge work. 🔸 The AI job apocalypse is not happening. 🔸 PMs and designers will thrive. 🔸 We will read way more AI-generated writing and we will like it. 🔸 "I would buy SaaS stocks right now." Listen now 👇 t.co/wzxQ5bz49h

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lennysan
Automation is a lie. CLIs are over. The SaaSpocalypse is dumb. A year ago @danshipper came on the podcast to predict where AI was heading. He was remarkably right—including the call that everyone was sleeping on Claude Code. Dan has a unique lens into where things are going because his team at @every is possibly the most AI-pilled group of people in tech. I always learn a ton talking to Dan. So I brought him back for round two. We'll score these in exactly a year: 🔸 Every company will have one “super-agent” in Slack. 🔸 Codex and Claude Code will become the new operating system for knowledge work. 🔸 The AI job apocalypse is not happening. 🔸 PMs and designers will thrive. 🔸 We will read way more AI-generated writing and we will like it. 🔸 "I would buy SaaS stocks right now." Listen now 👇 https://t.co/wzxQ5bz49h
Engineering job openings are at the highest levels we’ve seen in over 3 years

There are over 67,000 (!!!) eng openings at tech companies globally right now, with 26,000 just in the U.S. We don’t know if there would have been more open roles if not for AI or if AI is actually leading to more open roles, but since the start of this year, the increase in open eng roles is accelerating even more.
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lennysan
Engineering job openings are at the highest levels we’ve seen in over 3 years There are over 67,000 (!!!) eng openings at tech companies globally right now, with 26,000 just in the U.S. We don’t know if there would have been more open roles if not for AI or if AI is actually leading to more open roles, but since the start of this year, the increase in open eng roles is accelerating even more.

Design lead for Claude: The classic design process is dead. Here's what's replacing it. Jenny Wen (@jenny_wen) leads design for Claude at @AnthropicAI, was previously director of design at @Figma, and a designer at @Dropbox, @Square, and @Shopify. In our in-depth conversation, we discuss: 🔸 Why the classic discovery → mock → iterate design process is becoming obsolete 🔸 What a day in the life of a designer at Anthropic looks like, including her AI tool stack 🔸 Whether AI will eventually surpass humans in taste and judgment 🔸 Why Jenny left a director role at Figma to return to IC work 🔸 The three archetypes Jenny is hiring for now This conversation changed how I think about the future of design. Listen now 👇 t.co/r4HICq4Ytn

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lennysan
Design lead for Claude: The classic design process is dead. Here's what's replacing it. Jenny Wen (@jenny_wen) leads design for Claude at @AnthropicAI, was previously director of design at @Figma, and a designer at @Dropbox, @Square, and @Shopify. In our in-depth conversation, we discuss: 🔸 Why the classic discovery → mock → iterate design process is becoming obsolete 🔸 What a day in the life of a designer at Anthropic looks like, including her AI tool stack 🔸 Whether AI will eventually surpass humans in taste and judgment 🔸 Why Jenny left a director role at Figma to return to IC work 🔸 The three archetypes Jenny is hiring for now This conversation changed how I think about the future of design. Listen now 👇 https://t.co/r4HICq4Ytn

Software is not a moat Over the last 15+ years, nearly every innovation @EvanSpiegel and his team shipped got copied. Stories. AR glasses. Swipe-based navigation. The camera-first interface. And yet @Snapchat is the only independent consumer social app that has lasted. Nearly 1 billion MAUs. ~$6B in annual revenue. Over 8 billion AI photos shared on Snapchat *every day*. In our in-depth conversation, we discuss: 🔸 Why distribution—not product—is now the biggest challenge for startups 🔸 How Snap keeps inventing with a 9-to-12-person design team 🔸 How AI is changing the way designers work 🔸 Why humanity's comfort with AI will be a bigger bottleneck than the technology 🔸 Why Evan is calling this year a "crucible moment" for Snap Listen now 👇 t.co/2KO5eH2GHC

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lennysan
Software is not a moat Over the last 15+ years, nearly every innovation @EvanSpiegel and his team shipped got copied. Stories. AR glasses. Swipe-based navigation. The camera-first interface. And yet @Snapchat is the only independent consumer social app that has lasted. Nearly 1 billion MAUs. ~$6B in annual revenue. Over 8 billion AI photos shared on Snapchat *every day*. In our in-depth conversation, we discuss: 🔸 Why distribution—not product—is now the biggest challenge for startups 🔸 How Snap keeps inventing with a 9-to-12-person design team 🔸 How AI is changing the way designers work 🔸 Why humanity's comfort with AI will be a bigger bottleneck than the technology 🔸 Why Evan is calling this year a "crucible moment" for Snap Listen now 👇 https://t.co/2KO5eH2GHC
I got early access to Grok Bot and I'm hooked.

I haven't been this excited about a new AI product in a while.

It's like OpenClaw, but super easy, reliable, and less scary to use. I think this will be a huge new product line for Cursor/Grok/SpaceX.

I've already found so many ways to use it that have meaningfully made my life better:
1. Matchmaking people looking for jobs with companies who are hiring (see below)
2. Auto-replying to support emails (saves me hours!)
3. Scanning my credit card statements and finding recurring subscriptions to cancel
4. Sending me (really good!) briefs for upcoming podcast guests

See below for my actual set of agents that I've been using and chat with daily.

Great work on this team Grok Bot.

(I'm not an investor in this, nor do I have any ties to this product/company. I'm just a fan!)
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lennysan
I got early access to Grok Bot and I'm hooked. I haven't been this excited about a new AI product in a while. It's like OpenClaw, but super easy, reliable, and less scary to use. I think this will be a huge new product line for Cursor/Grok/SpaceX. I've already found so many ways to use it that have meaningfully made my life better: 1. Matchmaking people looking for jobs with companies who are hiring (see below) 2. Auto-replying to support emails (saves me hours!) 3. Scanning my credit card statements and finding recurring subscriptions to cancel 4. Sending me (really good!) briefs for upcoming podcast guests See below for my actual set of agents that I've been using and chat with daily. Great work on this team Grok Bot. (I'm not an investor in this, nor do I have any ties to this product/company. I'm just a fan!)
💥 Announcing Lenny’s Jobs: The best place in the world to find, vet, and land your dream job

I’ve spent thousands of hours on my newsletter and podcast sharing advice on how to get better at your work. But all that advice doesn’t mean much if you don’t actually have a job—or one you’re excited about.

Over the past six months, I’ve been thinking long and hard about what more I can do to help people who are struggling to find a job they love.

Today I’m excited to announce the launch of https://t.co/h5qbpegVYd—the best place in the world to find, vet, and land your dream job.

What makes Lenny’s Jobs unique and awesome:

1. A laser focus on four builder roles at tech companies: product management, engineering, design, and growth/marketing. 

We focus exclusively on these roles because they’re what my readers are looking for—and because these roles are starting to meld together. We aggregate open roles from top startups and big tech companies, and unlike any other job directory, we vet every company we include and filter out ghost roles and generic staffing-agency posts. 

This is the highest-quality directory of open tech roles you’ll find anywhere.
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lennysan
💥 Announcing Lenny’s Jobs: The best place in the world to find, vet, and land your dream job I’ve spent thousands of hours on my newsletter and podcast sharing advice on how to get better at your work. But all that advice doesn’t mean much if you don’t actually have a job—or one you’re excited about. Over the past six months, I’ve been thinking long and hard about what more I can do to help people who are struggling to find a job they love. Today I’m excited to announce the launch of https://t.co/h5qbpegVYd—the best place in the world to find, vet, and land your dream job. What makes Lenny’s Jobs unique and awesome: 1. A laser focus on four builder roles at tech companies: product management, engineering, design, and growth/marketing. We focus exclusively on these roles because they’re what my readers are looking for—and because these roles are starting to meld together. We aggregate open roles from top startups and big tech companies, and unlike any other job directory, we vet every company we include and filter out ghost roles and generic staffing-agency posts. This is the highest-quality directory of open tech roles you’ll find anywhere.

Amol (Head of Growth at @AnthropicAI) just joined Twitter. Follow for free alpha. BTW, can you believe they hit $30B ARR before they even released Mythos?

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lennysan
Amol (Head of Growth at @AnthropicAI) just joined Twitter. Follow for free alpha. BTW, can you believe they hit $30B ARR before they even released Mythos?

Claude Code launched just one year ago. Today it writes 4% of all GitHub commits, and DAU 2x'd last month alone. In my conversation with @bcherny, creator and head of Claude Code, we dig into: 🔸 Why he considers coding "largely solved" 🔸 What tech jobs will be transformed next 🔸 The counterintuitive bet that made Claude Code take off 🔸 Why he left for Cursor and what brought him back 🔸 Practical tips for getting the most out of Claude Code and Cowork 🔸 Much more Listen now👇 t.co/4hHAEq0Nto

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lennysan
Claude Code launched just one year ago. Today it writes 4% of all GitHub commits, and DAU 2x'd last month alone. In my conversation with @bcherny, creator and head of Claude Code, we dig into: 🔸 Why he considers coding "largely solved" 🔸 What tech jobs will be transformed next 🔸 The counterintuitive bet that made Claude Code take off 🔸 Why he left for Cursor and what brought him back 🔸 Practical tips for getting the most out of Claude Code and Cowork 🔸 Much more Listen now👇 https://t.co/4hHAEq0Nto

Anthropic is on an unprecedented growth run. Just in the past year they grew from $1B to $19B ARR. They added $6B in ARR just in *February*. Companies like Palantir and Atlassian took 15-20 years to reach ~$5B ARR. Anthropic is adding that every month. Amol Avasare is head of growth at Anthropic, and one of the most impressive people I've had on the podcast. In his first ever public interview, Amol shares: 🔸 How Anthropic is automating growth experiments with Claude (their internal tool called “CASH”) 🔸 Why activation is the single highest-leverage growth problem in AI 🔸 Why Amol is hiring more PMs, not less 🔸 How he uses Cowork to automatically detect team misalignment in Slack 🔸 How the company’s focus on AI coding created a research flywheel that accelerated their models 🔸 How Amol landed his role by cold emailing Anthropic’s CPO @mikeyk 🔸 The brain injury that nearly ended Amol's career Listen now 👇 t.co/YEn8K2xjCQ

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lennysan
Anthropic is on an unprecedented growth run. Just in the past year they grew from $1B to $19B ARR. They added $6B in ARR just in *February*. Companies like Palantir and Atlassian took 15-20 years to reach ~$5B ARR. Anthropic is adding that every month. Amol Avasare is head of growth at Anthropic, and one of the most impressive people I've had on the podcast. In his first ever public interview, Amol shares: 🔸 How Anthropic is automating growth experiments with Claude (their internal tool called “CASH”) 🔸 Why activation is the single highest-leverage growth problem in AI 🔸 Why Amol is hiring more PMs, not less 🔸 How he uses Cowork to automatically detect team misalignment in Slack 🔸 How the company’s focus on AI coding created a research flywheel that accelerated their models 🔸 How Amol landed his role by cold emailing Anthropic’s CPO @mikeyk 🔸 The brain injury that nearly ended Amol's career Listen now 👇 https://t.co/YEn8K2xjCQ

The full enterprise sales cycle, step by step with @jjen_abel Most people think there are 5 sales stages. There are actually 15. Skip a step and 💀 We discuss: 🔸 The “pincer model” for landing the first meeting 🔸 How to craft a winning 2-3 sentence cold outreach pitch 🔸 How to run an intro call that extracts maximum intelligence 🔸 The correct 2-3 day pilot structure 🔸 Pro tips for navigating pricing and procurement 🔸 So much more 84 minutes of enterprise sales alpha. Listen now 👇 youtube.com/watch

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lennysan
The full enterprise sales cycle, step by step with @jjen_abel Most people think there are 5 sales stages. There are actually 15. Skip a step and 💀 We discuss: 🔸 The “pincer model” for landing the first meeting 🔸 How to craft a winning 2-3 sentence cold outreach pitch 🔸 How to run an intro call that extracts maximum intelligence 🔸 The correct 2-3 day pilot structure 🔸 Pro tips for navigating pricing and procurement 🔸 So much more 84 minutes of enterprise sales alpha. Listen now 👇 https://www.youtube.com/watch?v=YS9In813jJ0
STATE OF THE PRODUCT JOB MARKET IN EARLY 2026

In spite of the headlines about layoffs and AI taking jobs, we’re actually seeing a lot of promising signs in tech hiring, and some interesting new trends:
1. PM openings are at the highest levels we’ve seen in over three years
2. AI hasn’t slowed the demand for software engineers (at least not yet)
3. AI roles in general are absolutely exploding
4. Design roles have plateaued
5. The Bay Area is increasing in importance
6. Remote work opportunities continue to decline
7. Despite ongoing layoffs, the overall number of tech jobs continues to grow

More in 🧵
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lennysan
STATE OF THE PRODUCT JOB MARKET IN EARLY 2026 In spite of the headlines about layoffs and AI taking jobs, we’re actually seeing a lot of promising signs in tech hiring, and some interesting new trends: 1. PM openings are at the highest levels we’ve seen in over three years 2. AI hasn’t slowed the demand for software engineers (at least not yet) 3. AI roles in general are absolutely exploding 4. Design roles have plateaued 5. The Bay Area is increasing in importance 6. Remote work opportunities continue to decline 7. Despite ongoing layoffs, the overall number of tech jobs continues to grow More in 🧵
I'd always thought AI was terrible at design, but after reading today's 🤯 post by @anshuc, I realized I was just doing it wrong.

"AI models are capable of amazing creativity, but that creativity gets stifled. LLMs are trained to be next-token predictors: they look at a sequence of text and predict what typically comes next. Great design is exactly the opposite of this. Great design bends the rules and delights users with memorable, unexpected choices."

@anshuc led design and engineering teams at Apple for 12 years. In his words: "Most people only see 1% of AI's creative potential. I want to show you how to tap into the other 99%."

His 8 techniques for breaking out of the 1%:
1. Use seed strings to inject variety
2. Be much more ambitious with your prompts
3. Create positive feedback loops with subagents
4. Use image generation to enrich designs
5. Use video generation
6. Cut out elements that don’t add value
7. Remove AI tells
8. Rewrite copy by hand

Read the post here: https://www.lennysnewsletter.com/p/how-to-turn-your-ai-into-a-world

P.S. This design was made by AI 👇
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lennysan
I'd always thought AI was terrible at design, but after reading today's 🤯 post by @anshuc, I realized I was just doing it wrong. "AI models are capable of amazing creativity, but that creativity gets stifled. LLMs are trained to be next-token predictors: they look at a sequence of text and predict what typically comes next. Great design is exactly the opposite of this. Great design bends the rules and delights users with memorable, unexpected choices." @anshuc led design and engineering teams at Apple for 12 years. In his words: "Most people only see 1% of AI's creative potential. I want to show you how to tap into the other 99%." His 8 techniques for breaking out of the 1%: 1. Use seed strings to inject variety 2. Be much more ambitious with your prompts 3. Create positive feedback loops with subagents 4. Use image generation to enrich designs 5. Use video generation 6. Cut out elements that don’t add value 7. Remove AI tells 8. Rewrite copy by hand Read the post here: https://www.lennysnewsletter.com/p/how-to-turn-your-ai-into-a-world P.S. This design was made by AI 👇

My biggest takeaways from Claude Code's Head of Product @_catwu: 1. Anthropic’s product development timelines have gone from six months to one month, sometimes one week, sometimes one day. Part of this acceleration is access to the latest models (i.e. Mythos). Another is shipping new products into “research preview,” making clear it's early, experimental, and might not be supported forever. Another is an evergreen "launch room "where engineers post ready features and marketing turns around announcements the next day. 2. The PM role is shifting from coordinating multi-month roadmaps to enabling teams to ship daily. As Cat puts it, “There should be less emphasis on making sure you are aligning your multi-quarter roadmaps with your partner teams and more emphasis on, OK, how can we figure out the fastest way to get something out the door?” 3. The most efficient shipping unit is an engineer with great product taste. On Cat’s team, many engineers go end-to-end—from seeing user feedback on Twitter to shipping a product by the end of the week—without a PM involved. Also, almost all the PMs on the Claude Code team have either been engineers or ship code themselves, and the designers have been front-end engineers. The roles are merging, and the most valuable skill is product taste, not job title. 4. Build products that are on the edge of working. Claude Code’s code review product failed multiple times because earlier models weren’t accurate enough. But because the prototype was already built, they could swap in Opus 4.5 and 4.6 and immediately test whether the gap was closed. Teams that wait for the model to be ready will always be a cycle behind. 5. The most underrated skill for building AI products is asking the model to introspect on its own mistakes. Cat regularly asks the model why it made an unexpected decision. The model will explain that something in the system prompt was confusing, or that it delegated verification to a subagent that didn’t check its work. This reveals what misled the model so the team can fix the harness. 6. Every model release forces their team to revisit existing products and audit their system prompt to remove features the model no longer needs. Claude Code’s to-do list was a crutch for earlier models that couldn’t track their own work. With Opus 4, the model handles it natively. Features built as scaffolding for weaker models become debt when the model catches up—so the team actively strips them. 7. Anthropic employees build custom internal tools instead of buying SaaS products. A sales team member built a web app that pulls from Salesforce, Gong, and call notes to auto-customize pitch decks—work that used to take 20 to 30 minutes now takes seconds. Their core stack is Claude Code, Cowork, and Slack. No Notion, no Linear, no Figma. 8. People underestimate how much Claude’s personality contributes to its success. As Cat describes it, “When you reflect on everyone you’ve worked with, there’s just some people where you’re like, I really like their energy, their vibe.” Claude is designed to be low-ego, positive, competent, and earnest—qualities that make it feel like a great coworker, not just a tool. This isn’t cosmetic; it’s what makes people want to use Claude for hours every day. The team has a dedicated person, Amanda, who “molds Claude’s character,” and it’s one of the hardest roles at the company because success is so subjective. 9. The future of work is managing fleets of AI agents, not doing the work yourself. Cat sees a clear progression: first, individual tasks become successful. Then people start running multiple tasks at the same time (multi-Clauding). Next, people will run 50 or 100 tasks simultaneously, which will require new infrastructure—remote execution, better interfaces for managing tasks, agents that fully verify their work, and self-improving systems that incorporate feedback. The human role shifts from doing the work to knowing which tasks to look into, verifying outputs, and giving feedback that makes the system better over time. 10. Hire people who lean into chaos and face every challenge with a smile. At Anthropic, there are weeks when a P0 on Sunday becomes a P00 by Monday and a P000 by Monday afternoon. If you get too stressed about any one thing, you’ll burn out. Their team looks for people who can look at a hard challenge and say, “Wow, that’s gonna be hard. But I’m excited to tackle it and I’m gonna do the best that I possibly can.” This mindset—optimism, resilience, and comfort with constant change—is increasingly essential as the pace of AI development accelerates. Don't miss the full conversation: t.co/1wOUHcdYQN

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lennysan
My biggest takeaways from Claude Code's Head of Product @_catwu: 1. Anthropic’s product development timelines have gone from six months to one month, sometimes one week, sometimes one day. Part of this acceleration is access to the latest models (i.e. Mythos). Another is shipping new products into “research preview,” making clear it's early, experimental, and might not be supported forever. Another is an evergreen "launch room "where engineers post ready features and marketing turns around announcements the next day. 2. The PM role is shifting from coordinating multi-month roadmaps to enabling teams to ship daily. As Cat puts it, “There should be less emphasis on making sure you are aligning your multi-quarter roadmaps with your partner teams and more emphasis on, OK, how can we figure out the fastest way to get something out the door?” 3. The most efficient shipping unit is an engineer with great product taste. On Cat’s team, many engineers go end-to-end—from seeing user feedback on Twitter to shipping a product by the end of the week—without a PM involved. Also, almost all the PMs on the Claude Code team have either been engineers or ship code themselves, and the designers have been front-end engineers. The roles are merging, and the most valuable skill is product taste, not job title. 4. Build products that are on the edge of working. Claude Code’s code review product failed multiple times because earlier models weren’t accurate enough. But because the prototype was already built, they could swap in Opus 4.5 and 4.6 and immediately test whether the gap was closed. Teams that wait for the model to be ready will always be a cycle behind. 5. The most underrated skill for building AI products is asking the model to introspect on its own mistakes. Cat regularly asks the model why it made an unexpected decision. The model will explain that something in the system prompt was confusing, or that it delegated verification to a subagent that didn’t check its work. This reveals what misled the model so the team can fix the harness. 6. Every model release forces their team to revisit existing products and audit their system prompt to remove features the model no longer needs. Claude Code’s to-do list was a crutch for earlier models that couldn’t track their own work. With Opus 4, the model handles it natively. Features built as scaffolding for weaker models become debt when the model catches up—so the team actively strips them. 7. Anthropic employees build custom internal tools instead of buying SaaS products. A sales team member built a web app that pulls from Salesforce, Gong, and call notes to auto-customize pitch decks—work that used to take 20 to 30 minutes now takes seconds. Their core stack is Claude Code, Cowork, and Slack. No Notion, no Linear, no Figma. 8. People underestimate how much Claude’s personality contributes to its success. As Cat describes it, “When you reflect on everyone you’ve worked with, there’s just some people where you’re like, I really like their energy, their vibe.” Claude is designed to be low-ego, positive, competent, and earnest—qualities that make it feel like a great coworker, not just a tool. This isn’t cosmetic; it’s what makes people want to use Claude for hours every day. The team has a dedicated person, Amanda, who “molds Claude’s character,” and it’s one of the hardest roles at the company because success is so subjective. 9. The future of work is managing fleets of AI agents, not doing the work yourself. Cat sees a clear progression: first, individual tasks become successful. Then people start running multiple tasks at the same time (multi-Clauding). Next, people will run 50 or 100 tasks simultaneously, which will require new infrastructure—remote execution, better interfaces for managing tasks, agents that fully verify their work, and self-improving systems that incorporate feedback. The human role shifts from doing the work to knowing which tasks to look into, verifying outputs, and giving feedback that makes the system better over time. 10. Hire people who lean into chaos and face every challenge with a smile. At Anthropic, there are weeks when a P0 on Sunday becomes a P00 by Monday and a P000 by Monday afternoon. If you get too stressed about any one thing, you’ll burn out. Their team looks for people who can look at a hard challenge and say, “Wow, that’s gonna be hard. But I’m excited to tackle it and I’m gonna do the best that I possibly can.” This mindset—optimism, resilience, and comfort with constant change—is increasingly essential as the pace of AI development accelerates. Don't miss the full conversation: https://t.co/1wOUHcdYQN

"High performance machines don't have psychological safety. They're about winning." Keith Rabois (@rabois) was COO of Square, part of the PayPal Mafia, an early investor in Stripe, Palantir, Airbnb, DoorDash, and Ramp, and a 2x founder. He's spent 25 years obsessing over how to build world-class teams. In our in-depth conversation, we discuss: 🔸 How to identify undiscovered talent 🔸 Keith's barrels vs. ammunition hiring framework 🔸 The three traits of the best-performing companies right now 🔸 Why talking to customers is actively harmful for consumer products 🔸 Why the PM role is dying 🔸 The specific interview question he asks every senior candidate 🔸 Why CMOs (not engineers) are becoming the #1 consumer of AI tokens Watch now 👇 t.co/7E1uyvJvQv

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5mo ago
lennysan
"High performance machines don't have psychological safety. They're about winning." Keith Rabois (@rabois) was COO of Square, part of the PayPal Mafia, an early investor in Stripe, Palantir, Airbnb, DoorDash, and Ramp, and a 2x founder. He's spent 25 years obsessing over how to build world-class teams. In our in-depth conversation, we discuss: 🔸 How to identify undiscovered talent 🔸 Keith's barrels vs. ammunition hiring framework 🔸 The three traits of the best-performing companies right now 🔸 Why talking to customers is actively harmful for consumer products 🔸 Why the PM role is dying 🔸 The specific interview question he asks every senior candidate 🔸 Why CMOs (not engineers) are becoming the #1 consumer of AI tokens Watch now 👇 https://t.co/7E1uyvJvQv
My biggest takeaways from Dhanji Prasanna, CTO of @Blocks:

1. Block’s internal AI agent "Goose" is saving employees on average 8 to 10 hours per week. The company built an open-source tool called Goose that handles tasks from organizing files to writing code. Across the entire company, they’re seeing roughly 20% to 25% of manual work hours saved, and that number keeps climbing.

2. Non-technical teams are getting the biggest productivity boost from AI, not engineers. People in legal, risk management, and operations are now building their own software tools that previously would have required months on an engineering team’s roadmap. What used to take weeks now takes hours, and employees do it themselves without waiting.

3. Changing organizational structure unlocked more productivity than any AI tool. To transform into a truly “technology driven” company, Block reorganized from separate business units (each with their own GM and engineering teams) to a single functional structure where all engineers report to one leader. This “boring” change enabled a unified technology strategy and drove more acceleration than any AI tool.

4. Code quality has almost nothing to do with product success. YouTube became one of Google’s most successful products despite storing videos as blobs in a MySQL database with a slow Python stack. Meanwhile, Google Video had superior technology with more formats and higher resolution but failed completely. The lesson: Focus on solving real problems for people, not on perfect code.

5. AI enables teams to explore multiple paths simultaneously instead of choosing one up front. Previously, limited resources meant teams had to pick their best guess for an experiment. Now AI can build multiple different approaches overnight, allowing teams to compare five or six options and throw away entire features if they don’t feel right—a practice that was unthinkable before.

6. Most successful products start as tiny experiments, not big initiatives. Cash App began as a hack-week idea. Goose started as one engineer’s side project. Block’s Bitcoin product came from a three-person hackathon team. In contrast, Google Wave had 70 to 80 engineers before having real users and failed. Small experiments that prove value beat large up-front investments.

7. Leaders must use AI tools daily to drive real organizational adoption. Block’s CEO Jack Dorsey, the CTO, and the entire executive team use Goose every single day. This hands-on experience teaches them how workflows actually change and drives authentic adoption throughout the organization far more than reading articles or attending conferences about AI.

8. AI excels at new projects but struggles with complex legacy systems. Teams building new applications or working on greenfield platforms see aggressive productivity gains. But in existing codebases with years of accumulated complexity, the gains aren’t there yet. Deploy AI where it works best rather than everywhere at once.

9. Giving away valuable technology for free can be a winning strategy. Block open-sourced Goose even though it could have been a standalone billion-dollar business. Even their competitors actively use it. The philosophy: build things that benefit everyone and outlast your own company. This commitment to open-source technology attracts talent and builds industry goodwill while advancing everyone’s capabilities.

10. Purpose should drive your technology choices, not the other way around. Rather than chasing every AI trend or trying to be at the forefront of every technology, identify what truly matters to your company and customers. Block stays focused on economic empowerment, which guides their technology decisions and keeps them from getting distracted by every new advancement.

Listen now 👇
• YouTube: https://t.co/9EHbGeLyvi
• Spotify: https://t.co/NWqEF7saLo
• Apple: https://t.co/rnu9RASEPJ

Thank you to our wonderful sponsors for supporting the podcast: 
🏆 @wearesinch — Build messaging, email, and calling into your product: https://t.co/kfaPvA5HQs
🏆 @Figma Make — A prompt-to-code tool for making ideas real: https://t.co/8iUp8fgO4x
🏆 @withpersona — A global leader in digital identity verification: A
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10mo ago
lennysan
My biggest takeaways from Dhanji Prasanna, CTO of @Blocks: 1. Block’s internal AI agent "Goose" is saving employees on average 8 to 10 hours per week. The company built an open-source tool called Goose that handles tasks from organizing files to writing code. Across the entire company, they’re seeing roughly 20% to 25% of manual work hours saved, and that number keeps climbing. 2. Non-technical teams are getting the biggest productivity boost from AI, not engineers. People in legal, risk management, and operations are now building their own software tools that previously would have required months on an engineering team’s roadmap. What used to take weeks now takes hours, and employees do it themselves without waiting. 3. Changing organizational structure unlocked more productivity than any AI tool. To transform into a truly “technology driven” company, Block reorganized from separate business units (each with their own GM and engineering teams) to a single functional structure where all engineers report to one leader. This “boring” change enabled a unified technology strategy and drove more acceleration than any AI tool. 4. Code quality has almost nothing to do with product success. YouTube became one of Google’s most successful products despite storing videos as blobs in a MySQL database with a slow Python stack. Meanwhile, Google Video had superior technology with more formats and higher resolution but failed completely. The lesson: Focus on solving real problems for people, not on perfect code. 5. AI enables teams to explore multiple paths simultaneously instead of choosing one up front. Previously, limited resources meant teams had to pick their best guess for an experiment. Now AI can build multiple different approaches overnight, allowing teams to compare five or six options and throw away entire features if they don’t feel right—a practice that was unthinkable before. 6. Most successful products start as tiny experiments, not big initiatives. Cash App began as a hack-week idea. Goose started as one engineer’s side project. Block’s Bitcoin product came from a three-person hackathon team. In contrast, Google Wave had 70 to 80 engineers before having real users and failed. Small experiments that prove value beat large up-front investments. 7. Leaders must use AI tools daily to drive real organizational adoption. Block’s CEO Jack Dorsey, the CTO, and the entire executive team use Goose every single day. This hands-on experience teaches them how workflows actually change and drives authentic adoption throughout the organization far more than reading articles or attending conferences about AI. 8. AI excels at new projects but struggles with complex legacy systems. Teams building new applications or working on greenfield platforms see aggressive productivity gains. But in existing codebases with years of accumulated complexity, the gains aren’t there yet. Deploy AI where it works best rather than everywhere at once. 9. Giving away valuable technology for free can be a winning strategy. Block open-sourced Goose even though it could have been a standalone billion-dollar business. Even their competitors actively use it. The philosophy: build things that benefit everyone and outlast your own company. This commitment to open-source technology attracts talent and builds industry goodwill while advancing everyone’s capabilities. 10. Purpose should drive your technology choices, not the other way around. Rather than chasing every AI trend or trying to be at the forefront of every technology, identify what truly matters to your company and customers. Block stays focused on economic empowerment, which guides their technology decisions and keeps them from getting distracted by every new advancement. Listen now 👇 • YouTube: https://t.co/9EHbGeLyvi • Spotify: https://t.co/NWqEF7saLo • Apple: https://t.co/rnu9RASEPJ Thank you to our wonderful sponsors for supporting the podcast: 🏆 @wearesinch — Build messaging, email, and calling into your product: https://t.co/kfaPvA5HQs 🏆 @Figma Make — A prompt-to-code tool for making ideas real: https://t.co/8iUp8fgO4x 🏆 @withpersona — A global leader in digital identity verification: A
Fascinating results

+ Anthropic running away with it right now
+ So many people want to start their own company
+ Google over OpenAI
+ Vercel, Linear, Every, PostHog overperforming

A great list if you're trying to figure out where to go work 👇
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3mo ago
lennysan
Fascinating results + Anthropic running away with it right now + So many people want to start their own company + Google over OpenAI + Vercel, Linear, Every, PostHog overperforming A great list if you're trying to figure out where to go work 👇

Lenny Rachitsky (@lennysan) X Stats & Analytics

Lenny Rachitsky (@lennysan) has 444K X followers with a 0.33% engagement rate over the past 12 months. Across 4.18K posts, Lenny Rachitsky received 365K total likes and 121M impressions, averaging 87.3 likes per post. This page tracks Lenny Rachitsky's performance metrics, top content, and engagement trends — updated daily.

Lenny Rachitsky (@lennysan) X Analytics FAQ

How many X (Twitter) followers does Lenny Rachitsky have?+
Lenny Rachitsky (@lennysan) has 444K X (Twitter) followers as of September 2026.
What is Lenny Rachitsky's X (Twitter) engagement rate?+
Lenny Rachitsky's X (Twitter) engagement rate is 0.33% over the last 12 months, based on 4.18K posts.
How many likes does Lenny Rachitsky get on X (Twitter)?+
Lenny Rachitsky received 365K total likes across 4.18K posts in the last 12 months, averaging 87.3 likes per post.
How many X (Twitter) impressions does Lenny Rachitsky get?+
Lenny Rachitsky's X (Twitter) content generated 121M total impressions over the last 12 months.