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"To do anything well you have to be a little nutty, and be obsessed." Annie Leibovitz at Facebook HQ today!
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Christopher Noble
13.6K posts
Christopher Noble
@dyballnoble
Ex-@Meta Product Leader | VP Product / CPO | Building consumer & SaaS products used by 2B+ people. Published 📸 by @GettyImages @WashingtonPost @SInow @Surfer
United Kingdom Katılım Mart 2009
1.7K Takip Edilen1.8K Takipçiler
Christopher Noble retweetledi
What founders have to understand is that to win you have to mentally be changed forever.
"Building a company changes you permanently.
It is not something you reset with rest or balance, you become a different person.
If you want to win, you have to accept that transformation.
You cannot go back to who you were before." @jasonlk
Love to hear your thoughts on this @alanchanguk @awxjack @MaxJunestrand @marcrandolph @tjparker
Harry Stebbings@HarryStebbings
WTF is going on? Anthropic and Elon. Cerebras IPO. Ramp at $40BN. I sat down with @jasonlk & @rodriscoll to discuss the deal, along with the biggest news in tech this week: - Anthropic Buys Compute From Elon & Commits $200BN to Google - Cerebras IPO: The Breakdown - Ramp's $40BN Latest Valuation - Hubspot Tanks, Monday Rockets: WTF is Happening in Public Markets? My notes below: 1. Foundation Made the Investment of the Decade with Cerebras Jason argues that Foundation’s success with Cerebras is a masterclass in “actual venture capital” because they did not just muscle into a hot round. They incubated the company in 2016, when the category did not even make sense. By playing the long game, finding a brilliant founder, seeding the idea, and holding roughly 9% ownership through a $40B+ IPO, they proved that the biggest returns still come from doing the hard work before a deal becomes obvious. 2. What Founders Have to Understand Is That to Win, You Have to Mentally Be Changed Forever There is a fundamental breakpoint around the four-to-five-year mark when a founder’s brain is permanently rewired by the intensity of the journey. Jason notes that winning at a high level requires a commitment to becoming a different person. The happy-go-lucky version of yourself from the early days is gone, replaced by someone who can often only relate to other founders who have survived similar maelstroms. 3. The Enemy of My Enemy Infrastructure Play Anthropic’s partnership to use SpaceX’s Colossus 1 data center highlights a massive consolidation where the strongest players are hoovering up all available capacity on the planet. For Elon Musk, this move transitions xAI from a buyer of CapEx to a net seller of capacity, turning a potential money pit into a $3 to $5 billion annual revenue stream because Grok is not currently growing at the same pace as leading-edge models. 4. The Crackdown on Shadow Cap Tables Anthropic is enforcing board approval for all secondary sales to reclaim cap table control and call out "bad actors". Rory warns that side contracts for "economic rights" are legally fragile; because the company has no obligation to honor unapproved transfers, many investors face "messy" losses at the IPO. 5. Model vs. Application: The Vertical SaaS Death Zone The industry is debating if horizontal models will consume the application layer or if vertical workflows will remain independent. Jason predicts a "terminal state of decay" for legacy marketing tools because agents have no need for manual templates. Once a model can perform an application’s core function directly within a prompt, that software becomes obsolete. 6. Token Maxing vs. The 100x Engineer Despite massive growth forecasts, a "micro backlash" is growing against "token trash" generated by mediocre developers. Jason predicts a clampdown on wasteful agentic spend, where companies prioritize unlimited resources for elite "100x engineers" while restricting "web heads" who burn compute for minimal productivity gains. (links below)
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Christopher Noble retweetledi
A dozen words of framing made people describe a Monet as “garbage” that was “inferior” to the original
How you present a launch is as important as what you’re launching; people react to the story before the thing itself
Fumble the framing and people will reject even a Monet
Jediwolf@Jediwolf
What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS
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Christopher Noble retweetledi
What KLM just did is one of the smartest moves in service operations.
Hart, Heskett, and Sasser published "The Profitable Art of Service Recovery" in Harvard Business Review in 1990. Customers whose failure is well-recovered report higher satisfaction than customers who never had a failure at all. The phenomenon got named the Service Recovery Paradox in the literature that followed. Meta-analyses since have softened the loyalty claim. On word-of-mouth and short-term satisfaction the effect holds clean.
Run the math on what KLM avoided. Under the Montreal Convention they're liable up to 1,288 SDR per passenger for damaged baggage, roughly $1,700. The standard claim path is a Property Irregularity Report, a repair shop estimate, weeks of paperwork, and a partial payout that usually lands in the $80-200 range plus internal labor per claim. They spent the same money in ninety seconds at the desk.
The shrink wrap is the operational tell. Pre-wrapped replacement suitcases staged at the service desk means somebody at KLM ran the unit economics and built a SOP around it. The clerk had a procedure and the materials within reach.
What KLM got back: a verified-account passenger writing a glowing post comparing them favorably to Singapore Airlines on the world's largest tech distribution network. KLM's paid social CPM sits in the $8-15 range. The suitcase paid for itself before the contents finished swapping over.
Most airlines protect the claims budget and pay the brand cost. KLM ran the math the other way.
Stephen Fleming@StephenFleming
Kudos to @AirFranceKLM. They destroyed my wife’s suitcase (stuff happens), so we trudged to the service desk. I was hoping for some duct tape and expected to fill out a form where, maybe, they’d send me twenty bucks in six weeks or so. Nope! The friendly and efficient clerk apologized for the damage, measured our suitcase, went into the back room, and returned with a brand-new suitcase, the same size, still in the shrink wrap. We swapped the contents right there and rolled out of baggage claim with the new suitcase. Nicely done. That’s the sort of service I’d expect from Singapore Air, not a European carrier. (By the way, what happened to @SamsoniteUSA? Apparently they’re no longer gorilla-proof…)
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Christopher Noble retweetledi
Christopher Noble retweetledi
Every "PM is dead" take from the last 18 months was wrong. The job didn't die. It got the leverage it always needed.
For two years the consensus was that AI would replace product managers. The reasoning was that PMs sit between engineers and customers, and AI can talk to both. Every PM on this app has read some version of this argument. Most of them have lost a night of sleep to it.
The actual data from 2026 says the opposite happened.
LinkedIn just renamed product manager to full-stack builder and added a new career ladder, not because PMs are obsolete but because the role finally has the tools to do what it was always supposed to do. Microsoft, Anthropic, Google, and Stripe all increased PM headcount in Q1, not decreased it. The Senior PM AI comp band moved from $400K to $1.3M+ in 18 months. Top tech is paying nearly four times more for the role they were supposedly about to automate.
The reframe is simple. Pre-2026, a PM had judgment about what to build and no way to ship without spending six months coordinating across design, engineering, and approvals. The judgment was the asset. The handoffs were the tax. Most of the role's frustration was the gap between what the PM knew should ship and what the org would let them ship.
Claude Code closed that gap. A PM with good judgment now ships a working prototype to ten customers in a week. The judgment finally meets the artifact in the same person. The tax is gone.
This is why the comp band exploded. The market figured out that a PM with shipping leverage is worth four times a PM without it, because they validate four times the hypotheses per quarter and surface four times the customer learning. Companies will pay for that all day.
The PMs who took the "PM is dead" framing seriously and pivoted to AI engineering or solutions architect roles spent 2025 learning skills they didn't need. The PMs who learned Claude Code, n8n, and the agent loop now have the highest-leverage version of their original job.
Mahesh Yadav spent 13 years shipping AI at Microsoft, Amazon, Meta, and Google. His last role was Senior PM at Google in AI. He left to prove the same thesis from the outside. His point: the premium is for PMs who can finally execute on their own taste.
Stop reading takes that were obvious 18 months ago and wrong even then. The PM job is healthier than it has ever been. The handoffs were the problem. The handoffs are gone.
Aakash Gupta@aakashgupta
This guy literally broke down how to become a $1.4M "builder PM" with n8n, Claude Code, and OpenClaw: 1:53 - What a "builder PM" actually is 6:04 - Your first agent in n8n (live build) 14:18 - Why every agent needs these 4 things 21:35 - The multi-agent eval loop 29:47 - Where n8n dies 33:39 - When to graduate to Claude Code 35:08 - What broke in December 2025 47:17 - The self-improving PRD reviewer 1:02:28 - Mocks and prototypes without designers 1:05:15 - OpenClaw and the new agent OS 1:22:06 - What AI PM interviews look like now
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Christopher Noble retweetledi
Jack Dorsey, co-founder of Twitter (now X) and Block, on why treating AI as a "copilot" is a losing strategy:
@jack argues that most companies are approaching AI in a way that will make it nearly impossible for them to survive.
"I think most of the industry is thinking about AI as like a co-pilot, as something that is augmented onto, rather than like how do you just rebuild our whole company with this as the core."
His concern is that bolting AI onto existing structures produces companies that look indistinguishable from each other, and from the AI labs themselves.
"If it doesn't make sense for your business to do that and you end up being or looking very similar or rhyming too closely with the frontier labs, then I think it's going to be very, very challenging to differentiate and survive."
This thinking has been driving his decisions since early 2024, when these tools "really came to bear."
That's when his team began building Goose, an agent coding harness, as part of a broader effort to rebuild around AI rather than layer it on top.
The core insight?
Speeding up old workflows with AI is a short-term gain every competitor will match. Real differentiation comes from rebuilding the company itself around intelligence.
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Christopher Noble retweetledi
Worrying that your startup will be eaten by the model companies is like worrying that your life will be constrained after you become a movie star. You're far more likely simply to fail.
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Christopher Noble retweetledi
Christopher Noble retweetledi
Christopher Noble retweetledi
Hamming's talk is so important that I reproduced it on my site. It's one of the only things on my site written by someone else.
paulgraham.com/hamming.html
Ihtesham Ali@ihtesham2005
A mathematician who shared an office with Claude Shannon at Bell Labs gave one lecture in 1986 that explains why some people win Nobel Prizes and other equally smart people spend their whole lives doing forgettable work. His name was Richard Hamming. He won the Turing Award. He invented error-correcting codes that made modern computing possible. And he spent 30 years at Bell Labs sitting in a cafeteria at lunch watching which scientists became legendary and which ones faded into nothing. In March 1986, he walked into a Bellcore auditorium in front of 200 researchers and told them exactly what he had seen. Here's the framework that has been quoted by every serious scientist for the last 40 years. His opening line landed like a punch. He said most scientists he worked with at Bell Labs were just as smart as the Nobel Prize winners. Just as hardworking. Just as credentialed. And yet at the end of a 40-year career, one group had changed entire fields and the other group was forgotten by the time they retired. He wanted to know what the difference actually was. And he said it wasn't luck. It wasn't IQ. It was a specific set of habits that almost nobody is willing to follow. The first habit was the one that hurts the most to hear. He said most scientists deliberately avoid the most important problem in their field because the odds of failure are too high. They pick a safe adjacent problem, solve it cleanly, publish it, and move on. And because they never swing at the hard problem, they never hit it. He said if you do not work on an important problem, it is unlikely you will do important work. That is not a motivational line. That is a logical one. The second habit was about doors. Literal doors. He noticed that the scientists at Bell Labs who kept their office doors closed got more done in the short term because they had no interruptions. But the scientists who kept their doors open got more done over a career. The open-door scientists were interrupted constantly. They also absorbed every new idea passing through the hallway. Ten years in, they were working on problems the closed-door scientists did not even know existed. The third habit was inversion. When Bell Labs refused to give him the team of programmers he wanted, Hamming sat with the rejection for weeks. Then he flipped the question. Instead of asking for programmers to write the programs, he asked why machines could not write the programs themselves. That single inversion pushed him into the frontier of computer science. He said the pattern repeats everywhere. What looks like a defect, if you flip it correctly, becomes the exact thing that pushes you ahead of everyone else. The fourth habit was the one that hit me the hardest. He said knowledge and productivity compound like interest. Someone who works 10 percent harder than you does not produce 10 percent more over a career. They produce twice as much. The gap doesn't add. It multiplies. And it compounds silently for years before anyone notices. He finished the lecture with a line I have never been able to shake. He said Pasteur's famous quote is right. Luck favors the prepared mind. But he meant it literally. You don't hope for luck. You engineer the conditions where luck can land on you. Open doors. Important problems. Inverted questions. Compounded hours. Those are not traits. Those are choices you make every single day. The transcript has been sitting on the University of Virginia's computer science website for almost 30 years. The video is free on YouTube. Stripe Press reprinted the full lectures as a book in 2020 and Bret Victor wrote the foreword. Hamming died in 1998. He gave his final lecture a few weeks before. He was 82. The lecture that explains why some careers become legendary and others disappear is still free. Most people who could benefit from it will never open it.
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Christopher Noble retweetledi
Leave behind a more beautiful world than the one you found.
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Christopher Noble retweetledi
The hottest job for the next five years is going to be the agent operator.
They don't need to be an engineer. They can walk into marketing, legal, or life sciences research and actually make agents work for that function.
Required skills:
> MCPs
> CLIs
> Writing skills (the file kind)
> agents.md fluency
> Business acumen
None of this is in any CS curriculum today.
Soon, enterprises will be pressured to redesign their workflows for agents, not for people. And when that happens, agent operators will be in massive demand.
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Christopher Noble retweetledi
This is true.
The layoffs are clearly still all about over-hiring and under-managing. And blips in hiring college students are companies (mistakenly) going for quicker/easier near term fixes.
The demand for labor is going to skyrocket as companies learn what AI does. Just as the demand for labor increased as computing diffused through product and service delivery.
Anthony Pompliano 🌪@APompliano
I have changed my mind on how AI will impact jobs in America. Previously, I believed AI would replace many entry level roles typically filled by young employees. The technology would then work its way up the organization and eventually reduce the total number of jobs in a company. The data is saying something different, so when I get new information I am willing to change my mind. The number of software engineers being hired has been increasing. The number of open software engineer roles is growing. The number of new college grads who get hired has increased 5.6% over the last 12 months. The unemployment level for people aged 20-24 years old who have a college degree has fallen from nearly 9% to almost 5% as well. The Wall Street Journal recently wrote “AI created 640,000 jobs between 2023 and 2025 in the U.S., according to an analysis by LinkedIn of job posting data, including new white-collar positions such as Head of AI and AI engineer.” And I am starting to see companies throughout our portfolio aggressively hiring to keep up with the demand for their products and services. If AI can make employees more productive, which is widely accepted as fact, then companies are going to want as many productive units of labor as possible. This is a key reason why I am changing my mind. AI appears to be a magical technology that will make companies more productive and more profitable. The net result will be more corporations, more startups, and more jobs. All three are big, positive wins for the American economy.
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Christopher Noble retweetledi
Modern problems require modern solutions.
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Christopher Noble retweetledi
Kevin Kelly @kevin2kelly is neck and neck with Ray Kurzweil for the best technology forecaster of the last 40 years.
Jeff Huber@jeffreyhuber
reminder that @kevin2kelly called all of this in 2016
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Christopher Noble retweetledi
You truly do not need to know how to ‘prompt’ anymore. This is important and many folks don’t get this. ‘Prompting’ was a 2025 skill. It was important … then.
Today I told @Replit in 1 English sentence to build us a site for all the SaaStr AI annual parties this year, grab the images, make interactive, and automate sign-ups in one plain English sentence.
No prompting required anymore. No mapping it out in Claude first. No defining guardrails. Just 1 sentence
It crushed
That’s it. And it’s only April.
Amjad Masad@amasad
Nearing the “post promoting” era of AI
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Christopher Noble retweetledi
Christopher Noble retweetledi
I used to think MAUs and WAUs were the dumbest metric. Now I think it's the most important.
"I used to think MAUs and WAUs did not matter, now I think they are critical.
In the AI era, usage is the leading indicator of value.
If your usage is growing faster than revenue, you are building something people truly want." @jasonlk
Love to hear your thoughts on this @joshelman @kirbyman01 @Joshuabrowder @an21m @mignano and how your thoughts on what matters changed?
Harry Stebbings@HarryStebbings
This is the big f**king deal. Cursor acquired for $60BN by xAI I sat down with @jasonlk and @rodriscoll to discuss the deal, along with the biggest news in tech this week: - Anthropic Hits $1TRN in Secondary Markets - Anthropic Launches Claude Code - Rippling Hits $1BN in ARR - Cerebras Files for IPO My notes below: 1. This $60B deal actually makes sense The potential $60 billion acquisition of Cursor by xAI/SpaceX is an industrial "marriage made in heaven". Cursor has an exploding business with billions in ARR but "shitty" gross margins because they lack their own compute and models. Elon Musk has the massive Colossus GPU data center and a model (Grok) but effectively no revenue, making the vertical integration of these two companies a strategic fix for both. 2. How Claude Design Will Hurt Figma Anthropic’s Claude Design is a full design application, not just a set of prompts or skills. It poses an existential threat because it allows product and engineering teams to bypass the traditional 30-day designer turnaround. By enabling "normal people" to design and move into production immediately, it will "maim and nibble" at Figma’s growth over the coming quarters. 3. I used to think MAUs and WAUs were the dumbest metric. Now I think it's the most important. In the B2B world, usage metrics like MAUs, WAUs, and DAUs are now more critical than revenue. If usage isn't growing faster than revenue, it's a sign of a struggling startup or "stealth churn," where users have stopped active engagement despite the company still collecting fees. In the AI age, the ultimate test of a product's value is whether people are actually using its AI features daily. 4. Why the biggest fintech players are in for a shock. Existing moats for fintech giants like Brex and Ramp are weakening as the selection criteria for vendors shifts. Customers are no longer prioritizing a dashboard's UI; they care which API works best with their autonomous AI agents. If a new vendor offers a superior API that allows an "AI VP of Finance" to automate tasks like collections, companies will switch vendors in a single week. 5. Agent fabric is the layer that manages all your agents The defining 2027 challenge is the "agent fabric". The infrastructure needed to manage and secure hundreds of autonomous agents. This gives a massive advantage to incumbents like Salesforce. They are positioning themselves as the trusted governance layer to guardrail agents and prevent them from going rogue
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Christopher Noble retweetledi
Now a famous case, Radiologists defied AI job loss predictions of -7% and are growing rapidly at 9%
Not every profession will be like this. But many will
There are 𝘵𝘰𝘯𝘴 of expensive things that we want to be cheaper. It’s possible ALL of healthcare is like this
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