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A guide to advanced B2B positioning

April Dunford — Tue, 10 Mar 2026 12:45:43 GMT

👋 Hey there, I’m Lenny. Each week, I answer reader questions about building product, driving growth, and accelerating your career. For more: Lenny’s Podcast | Lennybot | How I AI | My favorite AI/PM courses, public speaking course, and interview prep copilot

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As AI makes it trivial to build and launch products (and, soon, even come up with product ideas), the biggest challenge for product teams is quickly becoming distribution: getting people to pay attention to your product in the increasing cacophony of launches.

One of the most powerful tools to cut through that noise is positioning. Strong, specific positioning grabs people’s attention and helps them instantly understand why your product is for them.

April Dunford is the world’s leading expert on the topic. She is the author of the book on positioning, Obviously Awesome, and has worked with over 300 B2B companies to nail their positioning. She’s also a two-time Lenny’s guest contributor and podcast guest. As she explained in her previous, widely shared, guest post, “a single shift in positioning can mean the difference between a product that flops and one that breaks through.”

In her latest guest post, below, April offers a guide to advanced B2B positioning—four lessons for getting past the trickiest and most common roadblocks that teams run into.

Let’s get into it.

P.S. April just published an updated and expanded edition of Obviously Awesome. Grab a copy if you know what’s good for you. For more from April, subscribe to her excellent Substack (she’ll be dropping some new plug-and-play positioning templates in the next couple of weeks), and follow her on LinkedIn.

You can also listen to this post in convenient podcast form: Spotify / Apple / YouTube.

When I started out as a junior product marketer, positioning was something everyone understood but no one knew how to do, especially for tech companies. My work over the past 10 years has focused on developing a repeatable process that any B2B technology company can use as a starting point for creating strong positioning. I wrote a book, Obviously Awesome, about how a cross-functional team should work through the five components of positioning in a specific order. I’ve also covered it in this article and this podcast with Lenny.

Today, we have a much deeper understanding of how to develop good positioning—which is great for product marketers and great for the industry. But teams may encounter more advanced and challenging roadblocks that can slow momentum, derail collaboration, and break a project entirely. In this post, I’m looking beyond the basics of running a positioning process to address how to get past difficult roadblocks at different stages of the positioning development process to develop a positioning that clearly sets your product apart from your competition.

There are four patterns I see where teams encounter roadblocks during positioning development that are hard to see coming and to navigate around:

Disagreement about what to position against
Product pessimism blinds the team to product strengths
The differentiated value is poorly defined
The company doesn’t know what they are positioning

These roadblocks are common, but they’re far from impossible to manage. In this post, I’ll give you a clear view of where they may appear down the road and how you can avoid them entirely or guide your team safely around them to achieve consistent, lasting success in your B2B positioning. You’ll walk away with a greater understanding of the positioning process and four real-world strategies that you can immediately take into your next project. Now let’s get into it.

Four positioning roadblocks and how to move past them

Roadblock 1: Disagreement about what to position against

The first step in a positioning process is to look at the competitive alternatives. One of the most surprising things I have seen in positioning work is how often marketing, product, sales, and the founder/CEO have very different views on who they compete with. I’ve seen it so consistently that I believe disagreement about what to position against is the root of most weak positioning.

Each function in a B2B tech company tends to have its own set of biases when it comes to thinking about “competition.”

Marketing: Marketing is often overly influenced by a potential competitor’s marketing spend, regardless of the effectiveness of that spend (which is often completely unknown). Marketing teams watch how competitors show up in media, online, ads, and at conferences, and then often equate market visibility with competitive success—even if the sales team rarely encounters this competitor on a prospect’s short list and never loses deals to them.

Product Management: The product team is focused a little further into the future than the marketing and sales teams. Product roadmap work requires an understanding of what I would call “horizon competitors,” products that aren’t causing any pain today but could in the future. In a positioning exercise, product teams will often list twice as many “competitors” as a sales team does, many of which are never seen on a prospect’s short list.

Sales: Sales teams can have a skewed perception of competitors in two distinct ways. Firstly, they tend to have what I would call a “whale” bias. Sales can feel the sting of losing one very big deal and become overly focused on that winning competitor, even if they are never seen in more “normal” deals. The second bias is that they rarely define the status quo solution as a “competitor.” Deals lost to the status quo are often categorized as “no decision.” In the mind of a good salesperson, the customer’s “No” is mentally translated to “Not yet.” I have seen this even when the overwhelming majority of deals are lost to the status quo.

Founders: Most founders I’ve worked with have a great gut feel for positioning. In fact, many positioning exercises I’ve led end up helping newer executives understand the nuances of what the founder already knows. However, in certain situations, founders might muddy the positioning waters by bringing a bias that the rest of the team doesn’t fully understand. Three situations where I see this happening:

The founder was once heavily involved in closing deals but became less so. The founder may be biased toward what the competitive landscape used to look like and less familiar with current market dynamics.
Recent acquisitions have opened opportunities in market segments that the acquiring team (including the founder) may not understand as well as the folks on the recently acquired team.
The founder has recently been very focused on fundraising. In fundraising, the company orients more toward the future state it is building. Often, that future state is not something the sales team can sell today. Too much focus on future capabilities the company does not yet deliver can result in stalled deals and customers saying, “We love that. Come back in two years when you have it.”

The solution: Focus on the prospect’s view of the competition

The prospect’s view of competitive alternatives is the only one that matters. Because different teams interact with customers in different ways and at different points in the sales process, their understanding of how customers view alternatives won’t always align. If we go into the positioning process understanding this, we can get past the roadblock in these ways:

Imagine a world from the prospect’s POV: Rather than have the team list conflicting sets of perceived competitors, ask, “If we didn’t exist, what would a prospect do?” That reframing helps the team focus on what is happening in sales deals out in the real world, rather than who they should or could compete with.

Stay rooted in the near term: As an old boss of mine used to say, “We have to sell what’s on the truck.” The path to success is to focus on the product as it exists, in the market as it exists, and selling to the customers we can win with today. We should expect our positioning to change over time as the product, competitors, and target customers evolve, but we should also accept that we are terrible at predicting how the changes will unfold.

Don’t forget the status quo: In B2B, vendors typically lose about half their sales opportunities to whatever the prospect is currently using. I’ve worked with companies where that number exceeds 80%. We need to understand the strengths and weaknesses of the status quo solution to convince buyers to move on. Research shows that about half the time, a status quo decision is more about customer indecision than a vote for the status quo solution (see Matt Dixon’s JOLT Effect research, for example). Still, we ignore the other half at our peril. Strong positioning wins both types of “no decision” deals.

Work with a cross-functional team: The first and most obvious way to ensure that the positioning accounts for different perspectives is to work with a cross-functional team. My recommendation is that we have the heads of marketing, sales, product management, and customer success, along with the founder, CEO, or head of the business (if it is a larger company). Often it helps to include a couple of very experienced account executives from the sales team to verify what is happening in the early sales stages. If we are positioning the company or a grouping of products (more on this later), we will need to make sure we have folks with product and commercial experience for each product. We might also need sales representation across different geographies if the competitive landscape varies.

Roadblock 2: Pessimism blinds the team to the products’ strengths

Some companies suffer from overly pessimistic product thinking—where teams convince themselves their product is an undifferentiated loser despite clear evidence that they’re winning in parts of the market. This can happen when teams are overly focused on closing perceived gaps with competitors or when product teams and sales teams don’t communicate well or often. The pessimism pattern is dangerous because it blinds teams to their competitive strengths and prevents the company from positioning around them. Also, this mindset tends to be contagious, spreading to marketing and sales teams, who may lose confidence in the product’s ability to deliver differentiated value. It’s hard to convince prospects to invest in a product that sellers don’t believe in.

The pessimism manifests in four key ways:

Defining ideal customers so broadly that every lost deal seems like a product failure: I have worked with companies where product teams become over-exposed to bad deals and under-exposed to good ones. PMs get pulled in to try to save lost-cause deals, even when the prospect was a poor fit for the product in the first place. Meanwhile, deals with good-fit prospects are easily closed without any PM involvement. The result is that the product team begins to develop a skewed idea of what a good-fit prospect typically looks like.
Maintaining long hypothetical competitor lists: It’s hard to differentiate your product from an overly long list of competitors, particularly when we know little about many of them because we have never had to compete against them in a deal. For roadmap work, it makes sense to track future potential competitors. For positioning work, we have to stay oriented in the reality of the market—and be prepared to shift if and when a competitor begins to truly cause us pain.
Dismissing sales team insights about why customers buy: Sometimes this type of pessimism persists even in the face of proof that the product is doing well. In one workshop, a sales team listed a set of large accounts they had won because the product was superior in a particular way. The product team insisted that those prospects had failed to evaluate the other alternative properly. In another, despite the company generating hundreds of millions in revenue with solid growth, the product leader insisted that the sales team was winning through trickery and lies. I have seen salespeople who went too far in stretching the truth, but never one who was very successful with that strategy.
Viewing the role of product management as “problem identification” rather than architecting true differentiated value: Some companies get trapped in a cycle of competitive catch-up, to the point where the team becomes very adept at pointing out product problems and less attuned to where the product is leading. Often, there is a big, boring, long-standing differentiator hiding in plain sight. The product team takes it for granted (“Oh, we have always done that!”) while sales are selling the heck out of it.

Each symptom reinforces the others, creating a toxic cycle that undermines the company’s ability to articulate and amplify its genuine competitive advantages.

The solution: Keep coming back to what’s working

To break the pattern for positioning work, expose the product team to what sales understands about what’s working in the majority of deals, and work through a positioning exercise to help both teams understand each other.

We can get past this roadblock by:

Focusing the whole team on strengths and the near-term competitive advantage: A positioning process is really about finding the heart of why we win. To get there, we need to understand the product’s strengths and competitive advantages. We understand the product isn’t perfect and that we have competitive gaps. But we need to win business now, and we need positioning that tells a clear, compelling story about the product we have today (with the full understanding that that positioning will change and hopefully improve over time). Positioning is not a product strategy, nor does it set the product’s future direction. A discussion of the ways the product falls short does not lead to strong, differentiated positioning.
Including experienced sales voices in the room: Nobody understands how a customer behaves across a sales process better than your sales team does. For positioning work, we need to rely on that experience to understand who our true competitors are, what our true differentiators are, and which types of buyers care most about those differentiators. If the company’s CRO and VP of Sales do not have much experience with early-stage deals, it helps to have an experienced account executive in the room, and having two is generally better than just one, giving us a view across a broader set of deals.
Preparing the moderator to challenge participants: If you do a group positioning exercise, choose your moderator carefully. An experienced moderator can help the team stay grounded in reality and should be prepared to challenge participants if they become overly pessimistic. The moderator should remind the team that every day, customers spend months evaluating their options and then selecting the product. These customers can’t all be careless, gullible shoppers. Similarly, if a participant claims that many deals are won for a particular reason, they should be prompted to provide evidence and details. The team needs to agree on a position to work together and make it stick after the exercise.

It’s not unusual for teams to get together to discuss product problems and gaps. However, a positioning exercise should focus on where the product outperforms the competition. Getting the team oriented around the differentiated strengths of the product is critical for great positioning.

Roadblock 3: The differentiated value is poorly defined

As vendors (and particularly product folks), it’s easy to focus on features and assume buyers will easily understand why those features matter. In my experience, a product’s most differentiated capabilities are often the most difficult for prospects to understand, precisely because they are uncommon. If we really want to answer the question “Why pick us over the alternatives?” We have to clearly articulate the value our product can deliver that other alternatives cannot. This step in the process is the one I see teams struggle with the most.

There are four ways I see teams get stuck around differentiated value:

Assuming prospects understand why a feature is important: Today, a smartphone vendor can simply advertise that their phone has a 50-megapixel camera, and the audience knows what that means. However, 20 years ago, when few people had experience with digital cameras, you would have had to explain what a megapixel was, why anyone should care, and why 50 is better than 20. The more unique a feature is, the less likely a potential customer is to understand why it is important.

Stopping short of capturing value the prospect actually understands: I once worked for a database company with patented technology that enabled us to execute a specific type of query 1,000 times as fast as our competitors. We assumed anyone buying a database would find query speed valuable. Interestingly, many companies did not care. They were running the query for a monthly or quarterly report, so getting the answer in a day or two was perfectly fine. Our best-fit accounts, however, were running those types of queries to respond to a customer question. The real value lay in responding to customers more quickly, not executing the query faster. Recently, many of the teams I’ve worked with have a value point around efficiency. But their buyers may be much more focused on driving revenue—and can’t connect the dots between efficiency and revenue themselves.
Going too far and losing the differentiation completely: In B2B, we really only have two “pure” points of value. We are helping businesses make money or save money. (Insurance folks would add reducing risk, but that one is a special case!) Unlike consumer products, a successful B2B software project isn’t going to get you a date or make you look rich. We are increasing revenue or decreasing costs, and that’s it. If you abstract the value of your product all the way down to “This product saves you money,” you will sound exactly like every other product you compete with.
Overwhelming customers by attempting to communicate too many differentiated value themes: Differentiated value should succinctly answer the question “Why pick us over the alternatives?” If we give prospects a list of 10 reasons why, they aren’t likely to connect with a clear story or remember more than a couple of them (if we’re lucky).
Confusing differentiated value with sales objection handling: If there are people on the team who have never worked in sales, they might not understand what a sales objection is or how it differs from value. Value is a reason to buy. An objection is a reason a prospect might not buy, even if the value is something they really want. Often, objections come from constituents who are not the deal champion but can kill a deal if they have specific problems with the product. For example, I worked with a company whose product was very easy for the IT team to manage, which gave them an advantage over many competitors and the status quo. However, the purchase decision was driven by a business buyer who didn’t see any value in ease of management. In this case, ease of management was only used to handle the potential objection of the IT department after the business champion had selected the product.

The solution: Home in on the “so what?”

A guide to advanced B2B positioning

Lenny Rachitsky — Tue, 10 Mar 2026 09:00:40 GMT

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It’s never been easier to launch products, which means the biggest challenge product teams are facing is quickly becoming distribution. April Dunford, the world’s leading expert on B2B positioning and author of Obviously Awesome, has spent 10 years working with more than 300 companies to help them stand out. In this episode, she goes beyond the basics to share tactics for overcoming four of the trickiest positioning roadblocks teams face.

Listen now: YouTube | Apple | Spotify

In this episode, you’ll learn:

The four roadblocks every team faces when making positioning decisions
Why cross-functional teams almost always disagree on who they compete with
How to break the cycle of product pessimism
Why the “So what?” test is critical for defining your differentiated value
How to use your GTM strategy to drive positioning decisions

References:

April Dunford: https://www.linkedin.com/in/aprildunford/
April Dunf…

🎙️ This week on How I AI: Mastering Midjourney: How to create consistent, beautiful brand imagery without complex prompts

Lenny Rachitsky — Mon, 09 Mar 2026 15:03:09 GMT

Every Monday, host Claire Vo shares a 30- to 45-minute episode with a new guest demoing a practical, impactful way they’ve learned to use AI in their work or life. No pontificating—just specific and actionable advice.

Mastering Midjourney: How to create consistent, beautiful brand imagery without complex prompts

Brought to you by:
Vanta—Automate compliance and simplify security
Lovable—Build apps by simply chatting with AI

Jamey Gannon is an AI creative director who has spent thousands of hours working inside Midjourney. In this episode, she walks through the system she uses to generate consistent, high-quality brand imagery using mood boards, style references, and personalization codes. She and Claire cover her full workflow for turning loose inspiration into a scalable visual system, how to avoid the biggest mistakes people make with AI image tools, and why a single image reference can often outperform a paragraph of prompting.

Detailed workflow walkthroughs from this episode:

How I AI: Jamey Gannon’s Workflow for Consistent Brand Imagery in Midjourney: https://www.chatprd.ai/how-i-ai/consistent-brand-imagery-in-midjourney
How to Generate Realistic AI Self-Portraits for Content: https://www.chatprd.ai/how-i-ai/workflows/how-to-generate-realistic-ai-self-portraits-for-content
How to Fix and Refine AI-Generated Images: https://www.chatprd.ai/how-i-ai/workflows/how-to-fix-and-refine-ai-generated-images
How to Create a Consistent Brand Aesthetic in Midjourney: https://www.chatprd.ai/how-i-ai/workflows/how-to-create-a-consistent-brand-aesthetic-in-midjourney

Biggest takeaways:

Avoid prompting. Jamey’s entire workflow is designed to minimize text prompting: “I try to avoid prompting at all costs in my process.” Instead of writing complex JSON prompts or detailed descriptions, she relies on style references, image references, and personalization codes to communicate visually with AI.
Style references (SREFs) often outperform mood boards. While mood boards are a good starting point, using SREFs as the mood board can give much better results. This is because mood boards with varied styles can cause Midjourney to “average things out,” while SREFs provide more direct style guidance.
Personalization codes create your unique aesthetic. By carefully rating images during the personalization process, you can create codes that consistently deliver your preferred style. Jamey recommends “only picking things that I would like if I generated it” and being mindful of potential “style bleeding” from consistently selecting certain elements.
Editorial and camera references are prompting shortcuts. Instead of describing complex aesthetics, simply reference known publications or camera models: “When you just say ‘Dazed editorial,’ depending on how famous the publication is, Midjourney’s gonna know what you’re talking about.” This communicates lighting, composition, and style instantly.
When something’s not working, remove it completely. Rather than trying to fix problematic elements through prompting, Jamey takes a more direct approach: “If you’re getting too much green, just boot the thing that is so obvious and overwhelming.” This might mean removing an image from your references or cropping out distracting elements.
Use AI routing to get the best from each model. Jamey uses different tools for different purposes: Midjourney for initial creation, Nano Banana for editing specific elements, and Flora for packaging and delivering brand imagery to clients. Each tool has strengths that complement the others.
See things from the AI’s perspective. When troubleshooting, try to understand what the AI is “seeing” in your references: “I think where a lot of people get tripped up is trying to make AI work the way you want it to work instead of actually understanding how it works.” This perspective shift often leads to better results.

▶️ Listen now on YouTube | Spotify | Apple Podcasts

If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.

Catch you next week,
Lenny

P.S. Want every new episode delivered the moment it drops? Hit “Follow” on your favorite podcast app.

Mastering Midjourney: How to create consistent, beautiful brand imagery without complex prompts

Claire Vo — Mon, 09 Mar 2026 12:03:55 GMT

Jamey Gannon is an AI creative director who specializes in creating consistent, beautiful brand imagery using AI tools. In this episode, Jamey demonstrates her streamlined workflow for generating cohesive brand assets using Midjourney, Nano Banana, and other AI image tools. She walks through her process of creating mood boards, using style references, developing personalization codes, and strategically iterating to achieve a consistent aesthetic. Rather than relying on complex prompts, Jamey shows how visual references and strategic shortcuts can produce better results with less effort.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

How to create effective mood boards that communicate your desired aesthetic to AI image generation tools
Why style references (SREFs) often produce more consistent results than general mood boards in Midjourney
A systematic approach to testing and refining your visual style
How to use personalization codes in Midjourney to develop your own unique aesthetic preferences
Techniques for combining image references, style references, and minimal prompting to achieve consistent brand imagery
A workflow for using Nano Banana to fix specific elements in Midjourney-generated images without extensive editing
How to package and deliver your brand imagery system to clients so they can continue generating consistent assets

Brought to you by:

Vanta—Automate compliance and simplify security

Lovable—Build apps by simply chatting with AI

In this episode, we cover:

(00:00) Introduction to Jamey Gannon

(02:31) Creating mood boards as the foundation for AI image generation

(08:45) Using SREFs for better consistency

(11:15) Test prompts for evaluating style consistency

(12:33) The iterative process of creating and refining images

(24:28) Combining techniques for consistent brand imagery

(28:25) Scaling out your aesthetic across different subjects

(35:48) Using Nano Banana for targeted image refinements

(38:23) Creating realistic AI self-portraits for content

(43:04) Building a visual reference library for inspiration

(46:50) Troubleshooting techniques when AI isn’t cooperating

Tools referenced:

• Midjourney: https://www.midjourney.com/

• Nano Banana: https://gemini.google/overview/image-generation/

• Flora: https://flora.ai/

• Pinterest: https://www.pinterest.com/

• Cosmos: https://www.cosmos.so/

Other reference:

• Style references (SREFs) in Midjourney: https://docs.midjourney.com/hc/en-us/articles/32180011136653-Style-Reference

Where to find Jamey Gannon:

Website: https://www.brand-sprints.com/links

LinkedIn: https://www.linkedin.com/in/jameygannon/

X: https://x.com/jameygannon

Instagram: https://www.instagram.com/jameygannon

Maven Course (get 10% off with this link): https://bit.ly/4b18RfM

Where to find Claire Vo:

X: https://x.com/chintanturakhia

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

The most successful AI company you’ve never heard of | Qasar Younis

Lenny Rachitsky — Sun, 08 Mar 2026 12:31:38 GMT

Qasar Younis is the co-founder and CEO of Applied Intuition, a $15 billion AI company that adds intelligence to cars, tractors, planes, submarines, and other vehicles—essentially, Tesla or Waymo without the hardware. He was previously COO of Y Combinator, started his career as an engineer at GM and Bosch, and was born on a farm in Pakistan.

Listen on YouTube, Spotify, and Apple Podcasts

We discuss:

Why the biggest AI revolution will play out in mining, farming, construction, and trucking over the next 5 to 10 years, not in software
Why Qasar intentionally stayed under the radar for nearly a decade while building Applied Intuition, and why most founders shouldn’t do that
The truth about China’s AI capabilities and why comparisons to American companies are fundamentally flawed
The company values that drive Applied Intuition: speed above everything, laugh a lot, half the work is follow-up, never disappoint the customer
The biggest lessons from Qasar’s stint as YC’s COO, including that the most successful companies show traction very early
How reading old books is the best way to build taste

Brought to you by:

Omni—AI analytics your customers can trust
Vanta—Automate compliance. Simplify security.
Lovable—Build apps by simply chatting with AI

Where to find Qasar Younis:

• X: https://x.com/qasar

• LinkedIn: https://www.linkedin.com/in/qasar

• Website: https://qy.co

• Reading list: https://qy.co/books

Referenced:

• Applied Intuition: https://www.appliedintuition.com

• Marc Andreessen: The real AI boom hasn’t even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom

• Elad Gil’s website: https://eladgil.com

• Bosch: https://www.bosch.com

• Berkshire Hathaway: https://www.berkshirehathaway.com

• Naval Ravikant on X: https://x.com/naval

• Y Combinator: https://www.ycombinator.com

• Waymo: https://waymo.com/

• Tesla: https://www.tesla.com

• DeepSeek: https://www.deepseek.com

• Rivian: https://rivian.com

• Crate & Barrel: https://www.crateandbarrel.com

• OpenClaw: https://openclaw.ai

• Sam Altman on X: https://x.com/sama

• Peter Ludwig on LinkedIn: https://www.linkedin.com/in/peterwludwig

• What Steve Jobs really meant when he said ‘Good artists copy; great artists steal’: https://www.cnet.com/tech/tech-industry/what-steve-jobs-really-meant-when-he-said-good-artists-copy-great-artists-steal

• 7 quotes on the power of reading from Charlie Munger: https://www.neil.blog/articles/7-quotes-power-reading-charlie-munger

• Andreessen Horowitz: https://a16z.com

• John Doerr on LinkedIn: https://www.linkedin.com/in/john-doerr-03248211

• Gandhi’s quote: https://www.azquotes.com/author/5308-Mahatma_Gandhi/tag/truth#google_vignette

• Steve Ballmer on X: https://x.com/Steven_Ballmer

• General Motors: https://www.gm.com

Recommended books:

• House of Huawei: The Secret History of China’s Most Powerful Company: https://www.amazon.com/House-Huawei-History-Powerful-Company/dp/0593544633

• Maintenance: Of Everything, Part One: https://press.stripe.com/maintenance-part-one

• The Autobiography of Malcolm X: As Told to Alex Haley: https://www.amazon.com/Autobiography-Malcolm-Told-Alex-Haley/dp/0345350685

• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884

• The Emperor of All Maladies: A Biography of Cancer: https://www.amazon.com/Emperor-All-Maladies-Biography-Cancer/dp/1439170916

• Made in America: https://www.amazon.com/Sam-Walton-Made-America/dp/0553562835

• My American Journey: https://www.amazon.com/American-Journey-Autobiography-Colin-Powell/dp/0679432965

• Guns, Germs, and Steel: The Fates of Human Societies: https://www.amazon.com/Guns-Germs-Steel-Fates-Societies/dp/0393317552

• Collapse: How Societies Choose to Fail or Succeed: https://www.amazon.com/Collapse-Societies-Choose-Succeed-Revised/dp/0143117009

• SPQR: A History of Ancient Rome: https://www.amazon.com/SPQR-History-Ancient-Mary-Beard/dp/0871404230

• A World Appears: A Journey into Consciousness: https://www.amazon.com/World-Appears-Journey-into-Consciousness/dp/198488199X

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.

Lenny may be an investor in the companies discussed.

My biggest takeaways from this conversation:

🧠 Community Wisdom: Business books that haven’t aged well, vibe coding with your Figma design systems, Claude Code vs. other coding tools and more

Kiyani — Sat, 07 Mar 2026 16:44:42 GMT

How to debug a team that isn’t working: the Waterline Model

Molly Graham — Tue, 03 Mar 2026 13:45:17 GMT

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Molly Graham is the epitome of the type of person I love to collaborate with. She spent decades working closely with some of the most successful leaders in tech, including Mark Zuckerberg, Sheryl Sandberg, Chamath Palihapitiya, and Bret Taylor, and more recently (through her Glue Club community), she’s guided hundreds of leaders through the chaotic, lonely, and overwhelming journey inside early-stage and fast-growing companies. Drawing from these experiences, she is able to find patterns in what works and doesn’t and, more than anyone else I’ve met, is able to translate these lessons into powerful and memorable metaphors.

In her piece below, which I suspect will become as iconic as “Give Away Your Legos,” she builds on our recent podcast conversation to unpack a management framework that will change how you tackle team challenges: the Waterline Model.

Let’s get into it.

For more from Molly, check out her Substack and LinkedIn, and her Glue Club community. You can listen to this post in convenient podcast form: Spotify / Apple / YouTube.

There’s a moment most leaders recognize. You’ve set a clear goal (or so you think), your team’s bought in (or so they say), yet timelines keep slipping, execution is messy, and you’re having the same conversations over and over. When that happens, it’s tempting to jump straight to people-based explanations: “This team just doesn’t work well together.” “That person isn’t strong enough.” “We need better execution.”

Sometimes that’s true. But after two decades of working inside companies like Google, Facebook, and the Chan Zuckerberg Initiative, and supporting leaders at companies like Stripe, Anthropic, OpenAI, Microsoft, and Gamma, I’ve come to believe that blaming people for problems that are actually structural is one of the biggest leadership traps there is.

I’ve learned to slow down in these moments and use a simple diagnostic tool I picked up early in my career: the Waterline Model.

I first learned how to use this tool when I was leading 75-day wilderness expeditions in Patagonia and Alaska for the National Outdoor Leadership School at age 22. Out there, when a team isn’t working, things fall apart fast. People get cold, hungry, tired, scared. There’s no hiding behind process or politeness, and there’s definitely no time for vague diagnoses like “the vibe is off.” You have to identify the source of what’s disrupting the team—not just the symptoms—and fix it quickly.

We learned the Waterline Model1 as instructors and taught it as part of the curriculum to students. Since then, I’ve used it anytime a team is underperforming, missing goals, or struggling more than they should be. More than anything, it has helped me avoid misdiagnosing problems, cycling through people unnecessarily, and wasting time fixing the wrong thing. At its core, the Waterline Model is a way to diagnose where a problem is actually coming from before you decide what to do about it.

In this post, I’ll walk through the model and show you how to use it as a practical diagnostic tool when a team is underperforming. We’ll look at the four levels where problems tend to show up—structure, dynamics, interpersonal, and individual—and how to work through them in the right order. By the end, you should be better equipped to slow down in those “something’s off” moments, identify the real source of friction on a team, and fix the right problem instead of defaulting to people changes.

How the Waterline Model works

Here’s the basic picture. Imagine a boat moving across the water—that boat is your team. The boat’s destination is your goal: hitting a KPI, winning a major new customer, shipping a product. Sometimes the water is calm and the boat is moving forward smoothly. Other times, it feels like you’re rowing through a hurricane and no one can quite explain why.

When I use this model, I’m able to move beyond the natural human instinct to automatically blame the people. The Waterline Model helps me investigate one question: What’s going on below the surface that’s making things harder than they should be?

This model gives you four places to look, in order, and it comes with a memorable rule of thumb: snorkel before you scuba. Start at the top, always. Snorkeling means checking the shared systems first—goals, roles, and decision-making—before you start diagnosing personalities.

At the top, just below the surface, is structure. This is the stuff that helps people know what they’re doing, why they’re doing it, and how success is defined: vision, goals, context, expectations, role clarity, and org design. In my experience, this is where a huge percentage of issues on teams actually shows up.

The next layer is dynamics—how the team works together day-to-day. This is where I look at how decisions get made, how conflict shows up and gets resolved, and how information flows (or doesn’t). Even with clear goals and roles, teams can struggle here. Structure and dynamics are systems shared by everyone on the team, so you can most directly affect the collective team performance at these levels.

Below that is interpersonal—tension between two people, lack of trust, unresolved conflict, style clashes. These issues are real, but they’re often caused or amplified by problems higher up.

And at the very bottom is individual—what’s happening inside a single person: skill gaps, stress, confidence, values, life stuff.

All four layers matter. Any one of them can make the water choppy.

But the Waterline Model and “snorkel before you scuba” remind me to start with the issues that impact the most people—closest to the surface—and only go deeper once I’ve ruled things out. Before you decide someone is the issue, you need to know that structure and dynamics aren’t pushing them toward exactly the behavior you’re frustrated by.

Let’s walk through each level and use common examples of issues on underperforming teams to show how you can use the model.

Structure: the most common culprit

A few years ago, I was asked to take over a struggling marketing team: “Go figure out what this team actually does, and why we’re spending so much money without seeing results.”

The temptation in a situation like this is to diagnose the people—who is a high performer, who is dragging people down—but the Waterline Model has taught me to start by evaluating the structure. So instead, I asked each person on my new team how they would describe their role, what goals they thought the team was responsible for, and what numbers they believed they personally owned and were expected to move. Almost immediately, those questions surfaced structural issues.

The team’s answers were wildly inconsistent. Individuals had no idea what their goals were or which metric the team was responsible for. People defined their roles in ways that were far too narrow, or disconnected, to make sense. What leadership thought the team was responsible for, and how success was measured, were very different from how people understood their own jobs.

In this case, it was impossible to determine whether the individuals were the right fit, because they were operating inside a deeply broken structure. If I had automatically assumed people were the problem, I probably would have fired the whole team and started over again. And then I’d likely have ended up with the same issues all over again. But once I realized this was a structural problem, the fix was clear.

I started by re-clarifying the team’s mandate, the goals the team actually owned, individual role definitions, and what success looked like for each role. Only after that work was complete did it make sense to evaluate whether each individual was a good fit for their role.

That clarity surfaced a few real fit issues. But it also immediately improved performance for most of the team—simply because people finally knew what their job was and what was expected of them. People are often smart and motivated, but (to use the boat analogy) they’re rowing in different directions because the structure isn’t doing its job. Structural clarity alone often resolves more issues than you’d expect.

Dynamics: teams behaving rationally inside bad systems

Dynamics are the cultural norms you’ve built for how the team actually works together day-to-day. What’s experienced, not what’s written down. You can have clear goals and roles and still find yourself with decisions bottlenecked at the top, endless debate with no resolution, or constant confusion about who has input versus who actually decides.

As an example, one member in Glue Club came to us with a familiar story: “My founder is constantly frustrated that the team is moving more slowly than they want. But when people try to move quickly or ship things or make decisions, the founder swoops in and unmakes decisions at the last minute or second-guesses people’s judgment. It doesn’t feel safe to move quickly.”

This wasn’t a structure problem. Goals were clear, roles were defined, and, on paper, people had decision rights. But in practice, decisions weren’t stable. Work would move forward, then get reversed later. Context would change after the fact. People learned that even if they did what was asked, they could still be wrong.

The team adapted in a very rational way: They slowed down. They added extra layers of alignment. They escalated decisions that technically didn’t need to be escalated. They optimized for not being wrong instead of for progress.

From the outside, it looked like a performance problem. From the inside, it felt like self-protection. The dynamics of this team taught people that speed is risky, and that was the problem.

People adapt quickly to what’s rewarded, punished, tolerated, or ignored. Over time, the team learns how to survive inside the system a leader creates, whether implicit or explicit. Dynamics problems show up when a team’s behavior makes sense given the environment—even if the results are exactly what you don’t want.

Dynamics problems often show up as process issues, but they’re rarely solved by process alone. They usually trace back to the signals leaders send through their behavior: what gets rewarded, what gets second-guessed, and what happens when things go wrong. That’s why dynamics issues can feel harder than structural ones. Fixing them doesn’t require a re-org or a new doc; it requires leaders to be consistent about how decisions are made, how disagreement is handled, and when they intervene. It requires a hard look in the mirror at how your behavior or the behavior of those above you is causing people to respond.

The good news is that when those signals change, behavior changes quickly. Teams adapt fast to new rules, especially when they’re enforced through action, not words. That’s the leverage at the dynamics level: change the rules of interaction, and people will respond.

Interpersonal: don’t assume interpersonal conflict, but don’t ignore it either

When something feels off on a team, leaders almost always leap to this layer first—“those two people hate each other.” To be fair, a lot of the time that instinct isn’t wrong; it’s just incomplete.

Very often, what looks like interpersonal conflict is actually being caused by something higher up the waterline. Roles aren’t clear, ownership overlaps, or individual or team incentives are not aligned. Two people are stepping on each other’s toes because the structure put them there. In those cases, the conflict isn’t really about the relationship. It’s a structural problem wearing a human face.

But interpersonal dynamics can absolutely destroy teams all on their own. You can have clear goals, clean roles, solid decision-making, etc., and still have two leaders who fundamentally don’t trust or like each other. And when that’s true, it always shows up in the business eventually, through slowed decisions, hoarded information, and teams quietly picking sides.

Once you’ve ruled out structure and dynamics issues, you move to interpersonal, and this is the moment where management gets more direct. At this level, the fix isn’t redesigning the system but, rather, addressing the relationship itself. That usually means naming the tension explicitly, grounding the conversation in how it’s affecting the work, and being clear about what needs to change for the relationship to function. You can make building a solid relationship with a business partner an expectation of someone’s role—something you judge their performance on, particularly if it’s business-critical.

This is the more familiar work of team leadership and management. Sometimes that work leads to repair. Sometimes it becomes clear that trust won’t be rebuilt in a reasonable time frame, and a change has to be made.

Individual: only make it about the person after the system is sound

If your goals are clear, the role is cleaned up, the dynamics are working well, and someone is still not performing, then you’re likely looking at an actual individual issue. At that point, the work is no longer diagnostic. It’s about making a decision.

Individual issues can be personal. Someone going through a tough time outside of work may not be able to meet the expectations of the role right now. Your job as a manager is to decide whether the person can successfully fulfill the role, given the current circumstances.

Evaluate the person against the role as it exists today. Decide whether the gap is coachable in the time frame the business can afford. If it is, invest and be explicit about what needs to change. If it’s not, change the role or make a clean exit. What doesn’t work is lingering in ambiguity.

That’s the leverage at the individual level: once the system is sound, clarity and decisiveness are kinder than dragging things out.

Start at the top. Always. If your team isn’t working well, here’s what the Waterline Model tells you to do:

How to debug a team that isn’t working: the Waterline Model

Lenny Rachitsky — Tue, 03 Mar 2026 13:02:55 GMT

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When their team underperforms, most managers jump straight to blaming people. Molly Graham—who’s worked alongside Mark Zuckerberg, Sheryl Sandberg, and Chamath Palihapitiya—explains how that’s one of the biggest leadership traps there is. In this episode, she shares the Waterline Model: a diagnostic model to help uncover the real source of team problems, before touching an org chart.

Listen now: YouTube | Apple | Spotify

In this episode, you’ll learn:

Why blaming people for structural problems is one of the biggest leadership mistakes
The four layers of the Waterline Model, and why that order matters
Why you should always “snorkel before you scuba”
How self-preservation can be a rational response to a faulty environment
How to make clean, decisive calls when you finally reach the individual layer

Read the post

🎙️ This week on How I AI: 5 OpenClaw agents run my home, finances, and code & How Coinbase scaled AI to 1,000+ engineers

Lenny Rachitsky — Mon, 02 Mar 2026 16:02:20 GMT

5 OpenClaw agents run my home, finances, and code | Jesse Genet

Brought to you by: Optimizely—Your AI agent orchestration platform for marketing and digital teams

Jesse Genet is a homeschooling parent and entrepreneur who operates five specialized OpenClaw agents, each on its own Mac Mini, to manage homeschool curriculum, family finances, scheduling, development projects, and household operations. She treats each agent like a new hire: defined role, scoped access, decision log, and progressive trust. In this episode she shares how she photographs curriculum books to auto-generate lesson plans, builds custom apps with zero prior terminal experience, partitions sensitive data across machines, and bridges the digital and physical world by inventorying every toy and supply in her house.

Detailed workflow walkthroughs from this episode:

• How I AI: Jesse Genet’s 5 OpenClaw Agents for Homeschooling, App Building, and Physical Inventories: https://www.chatprd.ai/how-i-ai/jesse-genets-5-openclaw-agents-for-homeschooling-app-building-and-physical-inventories

• Automate Homeschool Lesson Planning and Material Creation with an AI Agent: https://www.chatprd.ai/how-i-ai/workflows/automate-homeschool-lesson-planning-and-material-creation-with-an-ai-agent

• Build a Custom ‘Slop-Free’ Kids’ TV App Without Coding Experience: https://www.chatprd.ai/how-i-ai/workflows/build-a-custom-slop-free-kids-tv-app-without-coding-experience

• Create an AI-Powered Inventory of Your Physical Items: https://www.chatprd.ai/how-i-ai/workflows/create-an-ai-powered-inventory-of-your-physical-items

Biggest takeaways:

Treat your AI agent like a new hire, not an extension of yourself. Jesse’s entire agent management philosophy comes from her experience hiring employees. She gives agents their own identities, separate data access, and communication channels—never full access to her email or accounts. Progressive trust is the model: start limited, expand as the agent proves reliable.
Physical partitioning is a real security strategy. Running each agent on its own Mac Mini sounds extreme, but it solves a real problem: preventing one agent from accidentally leaking sensitive data through another agent’s communication channel. The finance agent can read bank statements but can’t text anyone. The scheduling agent can text, but has no financial data. This is a practical framework anyone managing multiple agents should think through.
Photos are the most underrated input for AI agents. Jesse’s core workflow is shockingly simple: take a photo, send it to the agent, get structured output. She photographs lesson activities, book pages, physical supplies, and curriculum materials. The agent handles all the heavy lifting of logging, categorizing, and connecting that information. No typing, no structured input—just photos.
You don’t need to be technical to build real software with a coding agent. Jesse had never opened a terminal before six months ago. With Cole, her coding agent, she built a custom kids’ TV app, iterated over four days, and deployed it to a Google TV Streamer. Her approach: describe what you want, push back when the agent says something isn’t possible, and keep going.
Inventory your physical world so AI can reach into it. One of Jesse’s most powerful moves was photographing all her educational supplies and having Sylvie build an inventory. Now when she asks for a lesson plan, the agent can say, “Also, pull out the tracing board from the cupboard.” This bridges the gap between the digital agent and the physical world in a way that’s immediately useful.
Use “decision files” to prevent agents from relitigating settled questions. Jesse maintains a decisions file in Obsidian that each agent knows about. When she makes a final call, she flags it, and the agent knows not to revisit it. This is a simple, powerful pattern for anyone dealing with agents that keep second-guessing or re-asking about things you’ve already resolved.

▶️ Listen now on YouTube | Spotify | Apple Podcasts

How Coinbase scaled AI to 1,000+ engineers | Chintan Turakhia

Brought to you by:
WorkOS—Make your app enterprise-ready today
Rovo—AI that knows your business

Chintan Turakhia leads engineering at Coinbase, where he’s helped turn a 1,000-plus-person org into an AI-native team. In this episode, Chintan shares how Coinbase got 100 engineers to ship 75 PRs in 15 minutes, cut PR review time from 150 hours to 15, and built internal agents that turn user feedback into shipped features in minutes. Claire and Chintan dive into the “speed run” tactic that broke through skepticism, how to identify and replicate AI power users, and why the best engineering leaders are getting more hands-on with code in the AI era.

Detailed workflow walkthroughs from this episode:

• How I AI: Chintan Turakhia’s Playbook for AI Adoption at Coinbase: https://www.chatprd.ai/how-i-ai/playbook-for-ai-engineering-adoption-at-coinbase

• Use ChatGPT to Become Your Own Personal Wine Sommelier: https://www.chatprd.ai/how-i-ai/workflows/use-chatgpt-to-become-your-own-personal-wine-sommelier

• Build an Automated User Feedback to Pull Request Pipeline: https://www.chatprd.ai/how-i-ai/workflows/build-an-automated-user-feedback-to-pull-request-pipeline

• Create a Data-Driven AI Adoption Playbook Using Cursor: https://www.chatprd.ai/how-i-ai/workflows/create-a-data-driven-ai-adoption-playbook-using-cursor

Biggest takeaways:

Organize “speed runs” to kickstart widespread AI adoption. Coinbase gathered 100 engineers for a 15-minute session where everyone used AI tools to push 75 PRs simultaneously. The high success rate of merged PRs proved AI’s effectiveness at scale and transformed the team’s mindset about what they could accomplish.
Show, don’t tell, when driving AI adoption in engineering teams. Chintan spent months personally using Cursor daily, discovering use cases and techniques before asking his team to adopt it. By tackling real bugs and showing concrete wins, he built credibility that made adoption natural rather than forced.
Focus AI adoption on eliminating “soul-sucking” work first. Rather than tackling complex engineering challenges, Chintan targeted the tedious tasks engineers hate: writing unit tests, fixing linting issues, and managing Git commands. Engineers naturally want to build better things faster, and removing friction from their workflow created immediate buy-in.
Create public channels to showcase AI wins. Coinbase established a “Cursor Wins” Slack channel where engineers shared their successes. This visibility created organic FOMO and peer learning as engineers saw colleagues shipping more code with less effort.
Measure the entire feedback-to-feature cycle time, not just lines of code. Coinbase reduced PR review times from 150 hours to 15 hours and built systems to capture user feedback and convert it to shipped features in minutes rather than weeks. This end-to-end acceleration creates a virtuous cycle where faster shipping leads to more user feedback and continuous improvement.
Engineering leaders should be writing more code, not less. Chintan’s calendar is now nearly empty, as AI has eliminated coordination overhead and meetings. Instead, he spends more time writing code, fixing bugs, and exploring technical approaches.
Use AI to analyze AI adoption patterns. Chintan used Cursor itself to analyze Cursor usage data, identifying natural user cohorts from inactive to super-users. This meta-application of AI allowed him to create targeted guidance for each segment, helping engineers progress from light usage to power usage. The analysis revealed that agent-heavy users were 16x more productive with AI than other users, providing concrete data to drive further adoption.

▶️ Listen now on YouTube | Spotify | Apple Podcasts

If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.

Catch you next week,
Lenny

P.S. Want every new episode delivered the moment it drops? Hit “Follow” on your favorite podcast app.

How Coinbase scaled AI to 1,000+ engineers | Chintan Turakhia

Claire Vo — Mon, 02 Mar 2026 13:03:27 GMT

Chintan Turakhia is Senior Director of Engineering at Coinbase, where he’s led the transformation of a 1,000-plus-engineer organization to embrace AI tools at scale. When tasked with rewriting Coinbase’s self-custody wallet into a consumer social app in just six to nine months, Chintan turned to AI as a force multiplier. His team has achieved remarkable efficiency gains, including reducing PR review times from 150 hours to just 15 hours, and dramatically compressing the cycle from user feedback to shipped features.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

How to drive AI adoption in large, established engineering organizations
The “speed run” technique that got 100 engineers to push 70 PRs in 15 minutes
How to identify and replicate the behaviors of AI power users
Why engineering leaders must get hands-on with AI tools to drive adoption
How to build custom AI agents that integrate with your existing workflows
The metrics that actually matter when measuring AI’s impact on engineering velocity
How to compress the cycle from user feedback to shipped features

Brought to you by:

WorkOS—Make your app enterprise-ready today

Rovo—AI that knows your business

In this episode, we cover:

(00:00) Introduction to Chintan

(02:38) How Coinbase approached rewriting their app with AI assistance

(08:00) The importance of leadership conviction and hands-on demonstration

(10:30) The “PR speed run” technique that transformed team adoption

(17:57) Measuring success

(19:20) Demo: Real-time feedback-to-feature implementation

(23:14) Using Cursor to analyze AI adoption patterns

(33:15) Quick recap and appreciation

(36:00) Demo: Building a live feedback capture system using AI transcription

(40:50) Using custom Slack bots to automate engineering workflows

(47:10) Advice for driving AI adoption within your organization

(50:00) Personal use case: AI for wine selection based on taste preferences

(55:23) Lightning round and final thoughts

Tools referenced:

• Cursor: https://cursor.sh/

• Linear: https://linear.app/

• Slack: https://slack.com/

• ChatGPT: https://chat.openai.com/

• Claude: https://claude.ai/

• GitHub Copilot: https://github.com/features/copilot

Other references:

• Coinbase: https://www.coinbase.com/

• React Native: https://reactnative.dev/

• How custom GPTs can make you a better manager | Hilary Gridley (Head of Core Product at Whoop): https://www.lennysnewsletter.com/p/how-custom-gpts-can-make-you-a-better-manager

Where to find Chintan Turakhia:

LinkedIn: https://www.linkedin.com/in/chintanturakhia/

Base App (formerly Coinbase Wallet): https://base.app/

Where to find Claire Vo:

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

The design process is dead. Here’s what’s replacing it. | Jenny Wen (head of design at Claude)

Lenny Rachitsky — Sun, 01 Mar 2026 13:31:18 GMT

Jenny Wen leads design for Claude at Anthropic. Prior to this, she was Director of Design at Figma, where she led the teams behind FigJam and Slides. Before that, she was a designer at Dropbox, Square, and Shopify.

Listen on YouTube, Spotify, and Apple Podcasts

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 at Anthropic
The three archetypes Jenny is hiring for now
Why chatbot interfaces may be more durable than most people expect

Brought to you by:

Mercury—Radically different banking
Orkes—The enterprise platform for reliable applications and agentic workflows
Omni—AI analytics your customers can trust

Where to find Jenny Wen:

• X: https://x.com/jenny_wen

• LinkedIn: https://www.linkedin.com/in/jennywen

• Substack: https://jennywen.substack.com

• Website: https://jennywen.ca

Referenced:

• Figma: https://www.figma.com

• Anthropic: https://www.anthropic.com

• v0: https://v0.app

• Navigating a Design Career with Jenny Wen | Figma at Waterloo: https://www.youtube.com/watch?v=OHcBPMh2ivk

• Claude Cowork: https://claude.com/product/cowork

• Use Claude Code in VS Code: https://code.claude.com/docs/en/vs-code

• Claude Code in Slack: https://code.claude.com/docs/en/slack

• Lex Fridman’s website: https://lexfridman.com

• Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens

• OpenClaw: https://openclaw.ai

• OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai

• Marc Andreessen: The real AI boom hasn’t even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom

• Socratica: https://www.socratica.info

• Anthropic’s CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next

• Radical Candor: From theory to practice with author Kim Scott: https://www.lennysnewsletter.com/p/radical-candor-from-theory-to-practice

• Evan Tana’s ‘legibility matrix’ on X: https://x.com/evantana/status/1927404374252269667

• How to spot a top 1% startup early: https://www.lennysnewsletter.com/p/how-to-spot-a-top-1-startup-early

• Palantir: https://www.palantir.com

• Stripe: https://stripe.com

• Linear: https://linear.app

• Notion: https://www.notion.com

• Julie Zhuo’s website: https://www.juliezhuo.com

• Sentimental Value: https://www.imdb.com/title/tt27714581

• The Pitt on Prime Video: https://www.amazon.com/The-Pitt-Season-1/dp/B0DNRR8QWD

• Noah Wyle: https://en.wikipedia.org/wiki/Noah_Wyle

• ER on Prime Video: https://www.amazon.com/gp/video/detail/B0FWZSDYRP

• Retro: https://retro.app

• Granola: https://www.granola.ai

Recommended books:

• Radical Candor: Be a Kick-Ass Boss Without Losing Your Humanity: https://www.amazon.com/Radical-Candor-Kick-Ass-Without-Humanity/dp/1250103509

• The Power Broker: Robert Moses and the Fall of New York: https://www.amazon.com/Power-Broker-Robert-Moses-Fall/dp/0394480767

• Insomniac City: New York, Oliver Sacks, and Me: https://www.amazon.com/Insomniac-City-New-York-Oliver/dp/162040494X

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.

Lenny may be an investor in the companies discussed.

My biggest takeaways from this conversation:

🧠 Community Wisdom: Building your tech stack from scratch, surviving painful product demos, managing LLM credit costs, resources for new designers, and more

Kiyani — Sat, 28 Feb 2026 17:16:48 GMT

AI is critical for humanity’s survival: Cisco president on the AI revolution | Jeetu Patel

Lenny Rachitsky — Thu, 26 Feb 2026 13:31:32 GMT

Jeetu Patel is the president and chief product officer at Cisco, where he leads a team of 30,000 people and is playing a central role in the massive AI infrastructure buildout happening right now. Previously, he spent five years as CPO at Box and 17 years running his own startup. Recently Jeetu organized an AI summit featuring industry leaders like Jensen Huang, Sam Altman, Marc Andreessen, and Fei-Fei Li.

Listen on YouTube, Spotify, and Apple Podcasts

We discuss:

How Cisco went AI-first across 90,000 employees
His six-part framework for building great companies: timing, market, team, product, brand, distribution
Why he says he couldn’t have done this job without AI
His “right to win” strategic framework
His communication framework for preventing “packet loss” across an organization
Why he flips “praise in public, criticize in private” and does the exact opposite
The important communication lesson his mother taught him

Brought to you by:

Sentry—Code breaks, fix it faster
Framer—Build better websites faster
Samsara—Saving lives with AI built for physical operations

Where to find Jeetu Patel:

• X: https://x.com/jpatel41

• LinkedIn: https://www.linkedin.com/in/jeetupatel

• Website: https://blogs.cisco.com/author/jeetupatel

Referenced:

• Jensen Huang on LinkedIn: https://www.linkedin.com/in/jenhsunhuang

• Sam Altman on X: https://x.com/sama

• Marc Andreessen: The real AI boom hasn’t even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom

• Fei-Fei Li on LinkedIn: https://www.linkedin.com/in/fei-fei-li-4541247

• Lip-Bu Tan on LinkedIn: https://www.linkedin.com/in/lip-bu-tan-284a7846

• Matt Garman on LinkedIn: https://www.linkedin.com/in/mattgarman

• Anthropic’s CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next

• Kevin Scott on LinkedIn: https://www.linkedin.com/in/jkevinscott

• Cisco: https://www.cisco.com

• Elon Musk on X: https://x.com/elonmusk

• Ray Kurzweil’s website: https://www.thekurzweillibrary.com

• $46B of hard truths from Ben Horowitz: Why founders fail and why you need to run toward fear (a16z co-founder): https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz

• Aaron Levie on LinkedIn: https://www.linkedin.com/in/boxaaron

• Box: https://www.box.com

• Chuck Robbins on LinkedIn: https://www.linkedin.com/in/chuck-robbins

• Jeffrey Queisser on LinkedIn: https://www.linkedin.com/in/queisser

• Rick Devenuti on LinkedIn: https://www.linkedin.com/in/rick-devenuti-ba55432

• Jeremy Burton on LinkedIn: https://www.linkedin.com/in/jburton0

• Wes Bush: https://en.wikipedia.org/wiki/Wesley_G._Bush

• Michael Capellas on LinkedIn: https://www.linkedin.com/in/michael-capellas-36104887

• 10 contrarian leadership truths every leader needs to hear | Matt MacInnis (Rippling): https://www.lennysnewsletter.com/p/10-contrarian-leadership-truths

• Dunbar’s number: https://en.wikipedia.org/wiki/Dunbar%27s_number

• Pat Gelsinger on LinkedIn: https://www.linkedin.com/in/patgelsinger

• Bernie Madoff: https://en.wikipedia.org/wiki/Bernie_Madoff

• Taj Mahal: https://en.wikipedia.org/wiki/Taj_Mahal

• Six Things a Company Needs to Be Successful: https://www.youtube.com/watch?v=XnlTsEsm6qM

• Mark Lewis on LinkedIn: https://www.linkedin.com/in/mlewis62

• Web3: https://en.wikipedia.org/wiki/Web3

• F1: The Movie: https://www.imdb.com/title/tt16311594

• Zak Brown: https://en.wikipedia.org/wiki/Zak_Brown

• McLaren Racing: https://www.mclaren.com

• ChatGPT: https://chatgpt.com

• Gemini: https://gemini.google.com

• Grok: https://grok.com

• Sizzler: https://sizzler.com

Recommended books:

• Be Useful: Seven Tools for Life: https://www.amazon.com/Be-Useful-Seven-Tools-Life/dp/0593655958

• The Innovator’s Dilemma: The Revolutionary Book That Will Change the Way You Do Business: https://www.amazon.com/Innovators-Dilemma-Revolutionary-Change-Business/dp/0062060244

• The Innovator’s Solution: https://www.amazon.com/Innovators-Solution-n/dp/B001HYXNKW

• The Hard Thing About Hard Things: Building a Business when There Are No Easy Answers―Straight Talk on the Challenges of Entrepreneurship: https://www.amazon.com/Hard-Thing-About-Things-Building/dp/0062273205

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.

Lenny may be an investor in the companies discussed.

My biggest takeaways from this conversation:

5 OpenClaw agents run my home, finances, and code | Jesse Genet

Claire Vo — Wed, 25 Feb 2026 13:04:23 GMT

Jesse Genet is a homeschooling parent and entrepreneur who runs her household with five specialized OpenClaw agents. She layers them on top of her Obsidian “second brain,” deploys each on its own Mac Mini, and assigns every agent a distinct role—homeschool, finance, scheduling, development, and operations—so each one operates with clear scope and responsibility.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

How Jesse set up five OpenClaw agents, each with its own role, persona, SOUL.md file, and dedicated Mac Mini
The workflow for photographing an entire curriculum book and having an agent generate formatted, ready-to-teach lesson plans from the images
Using a coding agent to build a custom kids’ TV app from scratch and ship it to a real television in four days (with zero prior terminal experience)
Why Jesse treats agent onboarding like employee onboarding
The “decision file” trick and other incantations for managing agents that actually stick
Where multi-agent collaboration breaks down, and why no current messaging platform handles agent-to-agent handoffs well
How photographing every toy, book, and supply in the house lets the AI recommend real physical materials during lesson planning
The hands-free printing loop that took Jesse from scan → upload → email → print to “Sylvie, print this” in 30 seconds flat

Brought to you by:

Optimizely—Your AI agent orchestration platform for marketing and digital teams

In this episode, we cover:

(00:00) Meet Jesse and her “after Claw” life

(02:30) Layering OpenClaw on top of Obsidian

(04:44) Logging homeschool lessons automatically

(07:12) Turning books into a structured curriculum

(13:09) Using SOUL.md files to give each agent a personality

(14:39) Running multiple specialized AI agents

(16:43) Agent collaboration

(18:19) Partitioning data across Mac Minis

(27:00) Building a custom YouTube app with AI

(37:00) Creating a physical inventory from cupboard photos

(41:00) Printing from voice: reducing friction

(44:00) Managing agent memory and decision files

Tools referenced:

• OpenClaw: https://openclaw.ai/

• Obsidian: https://obsidian.md

• Slack: https://slack.com

• QuickBooks: https://quickbooks.intuit.com

• Google Gemini: https://gemini.google.com/

• Mac Mini: https://www.apple.com/mac-mini/

Other references:

• Claude Code for product managers: research, writing, context libraries, custom to-do system, and more | Teresa Torres: https://www.lennysnewsletter.com/p/claude-code-for-product-managers

Where to find Jesse Genet:

X: https://x.com/jessegenet

LinkedIn: https://www.linkedin.com/in/jessegenet/

Where to find Claire Vo: