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I started my career as a developer. Spent 20 years writing code, managing engineering…
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The North Star of an Enduring Business
The North Star of an Enduring Business
Key Takeaways In this episode, we talk about one of the principles of JTBD: Solutions come and go, but Jobs largely…
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Eric White posted thisOur second kid is heading to college this fall. The teen years go fast — and staying connected through the hard stuff doesn't happen by accident. My wife Clair White has a chapter on that topic out today in a brand new book: RAISING TEENS WHO TALK TO YOU. Real stories, practical tips, not theory. Digital is $1.99 today only — If you're parenting a teen (or will be), grab it. Parenting is hard. Connection is possible. Couldn't be prouder of her.
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Eric White shared thisYour prospect called and said their CFO told them to buy today. That's the power of value levers. Instead of chasing prospects for follow-up calls, prospects are calling you. Instead of "let me think about it," you get "we need to move on this." The difference is quantifying value so it shows up on the balance sheet. The best reps lead a conversations that turn vague frustrations and dull pain into a lever that gets attention upstairs. There are 7 types of value levers hiding in your sales conversations. Swipe through to see what each one sounds like, how to expose it, and how to turn it into a message that makes the CFO say "why haven't we done this already?" PS -- Marketing and Product should be laser focused on these too. Want to see the value levers hidden in one of your recent sales calls? Link in comments (or DM me for the prompt).
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Eric White shared thisI analyzed 2,128 sales calls for a company going upmarket (link to report in comments) 94% of their calls surfaced real buyer needs. But only 7% turned those into CFO-grade value levers. The team was selling a value story the CFO doesn't care about. Here's what's happening: Reps get used to selling to the pain of individual contributors. But an IC's pain doesn't translate to a manager with P&L responsibility. An IC is thrilled to save a couple hours a week. A CFO doesn't care — they'll just tell their team to work two more hours. CFO grade value levers show up on the balance sheet. So when your rep hears "integration is really messy for us" and responds with a feature pitch fro seamless integration, the call goes great. The IC is impressed. But when that IC takes it to their boss, they can't justify it and the deal dies in procurement purgatory. The fix is followup questions. Instead of settling for "it's messy," get your team to ask: → "How many engineers are spending time on that?" → "Is that their main job, or does it pull them off feature work?" → "What should they be working on instead?" Now you have job titles. Time. Opportunity cost. Concrete numbers that will tell the CFO this initiative needs to move forward now. And even better is how this will help with followup emails. Those numbers don't just help you sell. They create urgency. Your follow-up email can focus on value: "Every quarter you delay is another $45K in engineering time spent on integration instead of features." Make the cost of delay expensive. No CFO is going to pass up impact that shows up on the balance sheet this quarter. Don't let your buyer wait for the next budget cycle when there's money to be saved now. I published the full study — 2,128 calls, the exact patterns that separate won deals from lost deals when selling upmarket. Link in comments.
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Eric White reposted thisEric White reposted thisWorkday just called your AI agents "parasites." They explicitly said third-party agents are getting a "free ride" on their system, and they are going to put a consumption tax on it to stop it. Let’s translate what that actually means: A legacy vendor is going to charge you a toll every time your own AI agent looks at your own company's data. This is raw panic. For two decades, enterprise SaaS giants built their moats by trapping your data in walled gardens and forcing your team to live inside their bloated interfaces. Agentic software bypasses all of that. A modern AI agent doesn't log into a dashboard. It doesn't care about their UI. It just hits the API, pulls the context it needs, and executes. It renders the expensive incumbent platform completely invisible. If I buy a system to store my company's information, it is my data. Calling my automation a "parasite" for reading my own data is a massive mask-off moment. We are watching the start of a brutal war over data sovereignty. Incumbents are terrified of becoming commoditized, invisible databases. They are going to close their ecosystems. They will throttle APIs, build tollbooths, and try to force you to use their native AI tools by making third-party agent access financially ruinous. It is a desperate move, and it will backfire. If a legacy System of Record goes to war with your AI-native infrastructure, you aren't going to fire your agents. You are going to rip out the System of Record.
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Eric White posted thisThe two ways of using AI for commenting on LinkedIn: Quantity vs Value. AI can minimize the effort it takes me to post a comment -OR ->> Maximize the impact and value of a comment If the goal is to post 50 comments every day then AI tools to to get that done without even having to read the comment before posted. If the goal is to write a comment that adds value and builds on the conversation, then AI can help us get to the point, communicate in our own voice, and evolve the original post into an interesting conversation. The high quantity comments can be helpful for increasing the number of people who will see the original post, helping the thought spread. The value added comments are great for making it fun and valuable to read. This isn't a moral debate — it's a market. The quantity commenters help increase distribution for the posters and value commenters. The people writing thoughtful replies get surfaced to the top. The people blasting volume are still adding fuel to the fire underneath. And the algorithm makes it all work.
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Eric White shared thisTakeaway 1: If you are a cs grad starting your career, there has never been more need for your skills. Give AI doomers the attention they deserve -- none. Takeaway 2: Non programmers keep building! You now have the ability to express your ideas as a functional prototype rather than text. If you have the luxury of passing it off to a dev or a dev team do it. Take it from Richard Kronick -- you do not want to have to maintain an app. As the dust settles, people who are great at programming will learn how to stand apart and function at a high level. So will everyone else. Build.Eric White shared this“AI built my entire app.” 🤖 I keep seeing people say this everywhere. As a software engineer who actually uses and experiments with the latest AI tools and models... here’s the reality: Yes, AI can generate working apps and websites surprisingly well. But working code is not the same as production-grade software. And that difference matters a lot. Real systems have: • complex and evolving business rules • security requirements • messy edge cases • performance constraints • evolving product requirements • complicated integrations That level of complexity is where things change. Right now, most AI-generated code feels similar to what you might expect from a junior developer - it usually seems to work, but it almost always needs architectural guidance, refactoring, and careful review before it’s production-ready. And just because something works at the start, doesn't mean it is easy to maintain and add features to. That doesn’t make AI less impressive. In fact, it makes it one of the most powerful tools engineers have ever had. The developers who thrive in this new era won’t be the ones typing every line of code. They’ll be the ones who can: • design systems • guide architecture • anticipate edge cases • refine AI output into clean, maintainable software And to be clear, AI models will continue to improve. Eventually, they may be able to build systems as complex as the ones many of us work on today. But we’re not there yet. And until we are, software engineering is still very much an engineering discipline, not just prompting an AI. Curious how other engineers are experiencing this. #ArtificialIntelligence #AI #SoftwareEngineering #GenerativeAI #Tech
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Eric White shared thisAlmost true, but a bit more specificity and data will go a long way here. -- Add customer insights (use PonderAI to get them from interviews and sales calls) -- Add a couple of features or fixes being debated -- Prepare to have a conversation not a one shot answer We did this last week for the CPO of one of our clients. He was working on a new feature that would be adjacent to a core product. He noted that he got the core functionality in place but it was lacking magic. We looked through customer feedback and sales calls and found dozens of examples of customers clamoring for this feature with plenty of specific problem and value statements. Gave Claude Code everything (CPO frustration, GitHub repo, customer insight data) and asked it to give us 3 features and inspire us to build them based on what customers said. Now anyone in the company can take his repo and go find the magic. Project management isn't going to be outsourced to a one sentence prompt (not that Lenny is saying that). Learning how to provide the the right context data and questions as input to a tool like Claude Code will result in giving yourself and your product a promotion.
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Eric White shared thisThe A in AI isn't talked about enough. Last year, Apple dropped a paper called "The Illusion of Thinking." Their finding: these models don't think. They imitate thinking. That tracks with everything I've seen building our product. Yesterday a client asked us whether their sales team is asking for referrals, and if the referral program is actually working. Nobody had the answer. Not because it wasn't important — because getting it would have meant someone listening to thousands of hours of calls. We pointed our tool at 6,000 transcripts. Three minutes later we had patterns across every rep — who's asking, who's not, how prospects respond, what the top performers do differently. That's the artificial part. Processing at a scale no human would ever attempt. That meant we could spend our time on the part AI can't do as well: -- Sensemaking: What do these patterns actually mean right now? -- Creating thinking: What actions could lead to positive results? -- Communicating: How do we get busy sales people to add another thing to their already packed sales conversations? A year ago this work just wouldn't have been done because it was too mundane and so time consuming it just wasn't feasible. Now the limitation is knowing what to ask.
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Eric White shared thisAGI will be when AI writes funny LI posts rather than the "I'm sitting backwards in a chair so you know this is a serious conversation" we've been stuck in for a while now.
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Eric White reacted on thisEric White reacted on thisWe're partnering with NVIDIA to make sure every AI agent your enterprise deploys can be seen, measured, and governed—from the desktop to the data center. At Knowledge 2026, we're introducing Project Arc: an autonomous desktop agent that thinks, writes code, and executes complex work across your enterprise tools. Every action it takes runs inside NVIDIA OpenShell, a secure runtime, and is governed by AI Control Tower—so it's fully auditable before it ever reaches production. This is what enterprise AI should look like: autonomous, but never unsupervised. https://lnkd.in/g-gSVGun
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Eric White reacted on thisEric White reacted on thisI was out of town for work a couple days earlier this week. I got home late after the kids were already in bed… then left the next morning before I got to see my daughter. So she asked my wife to take her to the gym. Just so she could see me. Cue my heart melting. My wife caught this video of her running up and giving me the biggest hug. And honestly, if that’s not enough to remind me what matters most right now, I don’t know what is.
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Eric White reacted on thisEric White reacted on thisI’m excited to share that I’ve joined Vagaro as its chief marketing officer. If you've ever booked a haircut, a massage, or a workout class online or on your phone, there's a good chance that Vagaro was quietly making that moment happen. Behind each one of those bookings is a small business owner pouring everything they have into their craft. Helping those entrepreneurs be successful is exactly the kind of mission I want to spend my time on, and I’m excited to work with the team at Vagaro to make it happen. Thanks to everyone in my network who was helpful during this process. https://www.vagaro.com/proVagaro Pro - Salon, Spa, & Fitness Business SoftwareVagaro Pro - Salon, Spa, & Fitness Business Software
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Eric White liked thisEric White liked thisExcited to announce that I’ll be hosting an Executive Forum roundtable at MAU Vegas 2026 alongside an incredible group of mobile and growth leaders. 📍 MAU Vegas - MGM Grand 🗓 Wednesday, May 20, 2026 ⏰ 2:30 PM – 4:00 PM 🎯 Topic: UA Is Only Half the Story: Winning on Retention & LTV User acquisition costs continue to rise, but the companies winning in mobile today aren’t just focused on acquisition — they’re obsessed with retention, engagement, and maximizing LTV. This roundtable will be a candid, peer-driven discussion focused on: ✅ What’s actually working across push, SMS, email, and lifecycle marketing ✅ Strategies for retaining hard-to-acquire users ✅ Building habit-forming engagement loops ✅ How AI-powered and agentic martech platforms are changing personalization and orchestration at scale ✅ Real-world lessons from teams driving measurable growth No slide decks. No vendor pitches. Just honest conversations with operators and executives navigating these challenges in real time. If you’re attending MAU and care about mobile growth, lifecycle marketing, AI, or customer engagement strategy, I’d love to connect and see you there. #MAUVegas #MobileGrowth #LifecycleMarketing #Retention #LTV #AI #MarTech #ProductManagement #CustomerEngagement #SMSMarketing #PushNotifications
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Eric White liked thisEric White liked thisThe CMOs I talk to keep describing the same failed hire. The PMM walked them through impressive launches in the interview. A year in, they couldn't tell them which company number they'd helped move. That's the gap I keep seeing in PMM hiring. CMOs evaluate craft. They should be evaluating how candidates connect their work to the numbers. We looked at how 25+ senior PMM leaders measure their own impact, across Anthropic, Twilio, ServiceNow, Iterable, Box, and Verkada. The strongest describe their work as a chain to a number. Priyanka Srinivasan at Verkada puts it plainly. Revenue is shared. PMM runs the campaign, sales closes the deal, and clean attribution doesn't exist. The work is the sum of the parts. Priya Gill, CMO at Iterable, names the three numbers PMM influences without directly driving: pipeline, win rate, and product adoption. Vanessa Thompson at Twilio coaches her team to act as the "mini CMO" for the products they cover, with pipeline as the shared signal. Emi Hofmeister at Zuora watches three signals together: pipeline contribution, win rate lift, and whether reps get tripped up on Gong calls. Sarah Khogyani Wolf, who leads startup marketing at Anthropic, sharpens the point. PMMs should set KRs they can actually influence. Not "launch the website." Instead: "launch a website that contributes to a 10% lift in self-service signups by Q4." The first is a task. The second is a chain. This is the gap I keep landing on when CMOs ask me what to look for in their next head of PMM. The contributors describe a similar pattern. Start with a company outcome. Name the leading indicator PMM influenced. Track the lagging result. Show the qualitative proof from sales calls, customer feedback, or retros. That pattern is the interview. Ask a candidate to walk you through one piece of work that way. The specific number doesn't matter. What you're listening for is whether they can build the chain at all. Most can't. They were promoted on launches. Full deep dive in the comments.
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Eric White liked thisEric White liked thisGreat quick trip for TipTop VC out to SF last week to two events worth the flight Wednesday: Entrepreneurs First Demo Day 17 companies from their London and Bangalore cohorts presenting in SF. Alice Bentinck called it the highest-traction batch in EF’s history - 25% with > $1M in revenue or LOIs, every one live with customers. Impressive companies spanning defense, dev tools, health, construction, fintech, and hospitality. Thursday: Murph Capital VC/LP Mixer 180+ GPs and LPs in the room. Great energy leading to engaging conversations and real connections. It was one of the better emerging manager events I’ve been to recently: thoughtful GPs, engaged LPs, and a candid panel with folks who've closed funds ranging from $40M to $15B on what fundraising really looks like in this market. The event was under Chatham House rules, so I won’t share specific notes, but Andy Chen (Outcast Ventures), Jason Freedman (Orange Collective), and Kevin Deeth (Andreessen Horowitz) shared a lot of practical, relevant insights for GPs raising today. Huge shoutout to Pavel Prata for hosting and curating such a high-quality group for the first one. Already looking forward to the next!
Experience
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Education
Publications
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The North Star of an Enduring Business
JTBDin5 by Eric White and Alan Klement
Solutions focused businesses come and go, the Jobs focused business is built to last. Here’s why.
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It's More Than A Milkshake
Rocketship.fm
In this second episode of the Product series, we dive into some practical examples of the Job's To Be Done (JTBD) framework. Eric White helps us look into how Bob Moesta was able to transform the sellability of condominiums in Detroit that seemed unsellable. We then take a look at how Clay Christensen used the JTBD framework to find the job that a milkshake does for millions of people every morning. From there we finish off the episode with Alan Klement talking about how Dan Martell used the…
In this second episode of the Product series, we dive into some practical examples of the Job's To Be Done (JTBD) framework. Eric White helps us look into how Bob Moesta was able to transform the sellability of condominiums in Detroit that seemed unsellable. We then take a look at how Clay Christensen used the JTBD framework to find the job that a milkshake does for millions of people every morning. From there we finish off the episode with Alan Klement talking about how Dan Martell used the JTBD framework to find a need, and then fulfill it inside of the Startup world.
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UI Breakfast Podcast. Episode 30: Describing Customer Motivation (Jobs to Be Done) with Eric White
UIBreakfast
Discovering customer motivation is the core part of UX research! Today you’ll learn to do it using Jobs to Be Done methodology (JTBD). Our special guest is Eric White, a customer-insight consultant who helps businesses understand why their customers buy. You’ll discover the JTBD principles, and learn how to run an effective customer interview.
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Jobs to be Done in 5 Podcast
Eric White and Alan Klement
A 5 minute podcast where Alan Klement and Eric White talk about how to create and market innovative products with Jobs to be Done thinking.
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Projects
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Arlo: The lasting value of JTBD insight
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For over 5 years, Arlo has leveraged insights from our work together. Since our project in 2019, Arlo has:
💰Added a subscription product to generate a recurring revenue stream
🚀 Launched new products that help people protect their families.
📈 Enjoyed massive growth in a high performing segment
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In 2019, Arlo was the home security camera market leader, enjoying industry awards and consistent YoY growth.
But they had scrappy startups like Ring and major…For over 5 years, Arlo has leveraged insights from our work together. Since our project in 2019, Arlo has:
💰Added a subscription product to generate a recurring revenue stream
🚀 Launched new products that help people protect their families.
📈 Enjoyed massive growth in a high performing segment
***
In 2019, Arlo was the home security camera market leader, enjoying industry awards and consistent YoY growth.
But they had scrappy startups like Ring and major players like Google and Amazon entering their space.
With no clear vision, too many ideas, and mis-alignment over where to invest resources to build a moat they reached out to us for help.
* We started by conducting win-loss research to reveal buyer journey and product JTBDs
* We then expanded their new product feature ideas into a UX Storyboards. And used those storyboard to run simulated sales conversations with people in ICP to test value and demand.
* Next, we enhanced storyboard with videos of consumer reaction themes.
* Finally, we activate the team through empathy and decision making workshops.
This research provided clear evidence of the three features they should build (and one that they should absolutely NOT build)
We helped them test demand, think deeply about their target customers, and make high stakes decisions.
They executed. And they keep growing.
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Husein Kareem
🎙️ NSCoder Chicago — Episode 5 is live! 🍎💬 Episode 5 takes a fun and reflective turn, blending industry intrigue with personal journeys in tech. 🔍 In this episode: • Recent software leaks and references to unreleased goodies 👀 • Our origin stories in the software business — how it all started and what we learned along the way Whether you’re early in your career or many years in, this episode offers perspective on how the industry evolves — and how developers evolve with it. NSCoder Chicago is a monthly meetup for Apple-platform developers and tech enthusiasts. If you enjoy conversations like these, we’d love to see you in person at an upcoming meetup. 📍 Learn more & RSVP: 👉 https://lnkd.in/gxw8-7_p #NSCoderChicago #iOSDevelopment #Swift #AppleEcosystem #SoftwareEngineering #TechCareers #Leadership #ChicagoTech #Meetup
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Jeffrey DeCoux
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Tracy Winkler
Andrew stepped into my lane today. No, the mustache is not real. And yes, that would be a hard no. But the metaphor? Spot on. Most accountability problems are clarity problems in disguise. When follow-through breaks down, it usually sounds like: • “I thought you were handling that.” • “Wait — what did we decide?” • “I didn’t realize that was mine.” • “Let’s circle back next week.” That’s rarely a motivation issue. It’s usually because: • “Good” wasn’t clearly defined. • Ownership wasn’t named. • The next step wasn’t locked in. • No one closed the loop. Clear expectations make follow-through easier. Ownership makes execution stick. I’m curious, where do you hear this show up most on your team? And reminder, Andrew… When accountability and follow-through slip at home, the mustache does not work either. Hard no. 😄
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