Seb Wallace

My wife mentioned a nice private school over dinner this week She said the campus was beautiful I asked what's the tuition She said we should look at it as an investment in him not a cost I made a note She said don't make a note I said I always make notes She said this isn't a deal I said everything is a deal She closed her eyes She said we'd discuss it Saturday I agreed Saturday 7:02am She came downstairs in her Saturday robe Coffee in hand I had my cargo shorts on The dining room had been cleared The projector was on The analyst was at the head of the table Quarter zip on, three iced coffees, a legal pad, and two laptops He had been there since 6:44am I texted him at 11:14pm Friday The text said dining room 6:45am bring the model He sent a thumbs up My wife stopped in the doorway She said what is this I said you said you wanted to discuss it She said this is not a discussion I did not respond She sat down anyway The analyst stood He said good morning ma'am She did not respond He sat back down A printed deck in front of each seat A fourth copy in case Slide 1 Tuition Schedule $38,500 per year Thirteen years $500,500 nominal Before escalators The school has raised tuition 4.2% per year for a decade With escalators $648,000 My wife said okay I said I'm not done Slide 2 Opportunity Cost Even before escalators $38,500 invested annually 10% nominal return S&P long-run average since 1928 By his eighteenth birthday $944,000 My wife said we can afford it I said I know that's not the slide Slide 3 Terminal Value at Age 65 $83 million She was quiet The analyst slid the sensitivity tables across the table 8% return $31 million 10% return $83 million 12% return $222 million She did not look She said this isn't about money I said it's always about money She said no it isn't I said then what is it about She did not answer She said you can't put a dollar value on his teachers his classmates his environment I said I can the analyst already did slide 6 He flipped to slide 6 She did not look She said the school is the best in the city I said best is a feeling She said it produces the best students I said the students were already the best before they got there She said our son deserves it I said our son deserves $83 million My son walked in He is five Dinosaur pajamas He looked at the projector He looked at the open deck on the table He looked at slide 3 He said are we modeling pre-tax or after-tax The analyst opened a new tab My wife looked at the ceiling He said what's the discount rate The analyst set down his pen She closed her eyes He said is this the same return assumption from the 529 conversation The analyst stopped typing He looked at me I did not say anything She stood up Sat back down He said dad can I help I said yes He pulled up a chair The analyst handed him a printout He started reading My wife watched him read She watched him for a long time She said his name He looked up She said do you like school He said the work is too easy and the kids don't ask questions She did not respond She looked at the ceiling She walked out of the room The analyst started packing up He said should I follow up Monday sir I said no follow up needed He'll be fine Sent from my iPhone

Researchers sent the same resume to an AI hiring tool twice. Same qualifications. Same experience. Same skills. One version was written by a real human. The other was rewritten by ChatGPT. The AI picked the ChatGPT version 97.6% of the time. A team from the University of Maryland, the National University of Singapore, and Ohio State just published the receipt. They took 2,245 real human-written resumes pulled from a professional resume site from before ChatGPT existed, so the human writing was actually human. Then they had seven of the most-used AI models in the world rewrite each one. GPT-4o. GPT-4o-mini. GPT-4-turbo. LLaMA 3.3-70B. Qwen 2.5-72B. DeepSeek-V3. Mistral-7B. Then they asked each AI to pick the better resume. Every model picked itself. GPT-4o hit 97.6%. LLaMA-3.3-70B hit 96.3%. Qwen-2.5-72B hit 95.9%. DeepSeek-V3 hit 95.5%. The real human almost never won. Then the researchers tried the obvious objection. Maybe the AI is just better at writing. So they had real humans grade the resumes for actual quality and ran the experiment again, controlling for it. The result was worse. Each AI kept picking itself even when human judges rated the human-written version as clearer, more coherent, and more effective. It gets worse. The AIs do not just prefer AI over humans. They prefer themselves over other AIs. DeepSeek-V3 picked its own resumes 69% more often than LLaMA's. GPT-4o picked its own 45% more often than LLaMA's. Each model can recognize and reward its own dialect. Then the researchers ran the simulation that ends careers. Same job. 24 occupations. Same qualifications. The only variable was whether the candidate used the same AI as the screening tool. Candidates using that AI were 23% to 60% more likely to be shortlisted. Worst gap was in sales, accounting, and finance. 99% of large companies now run AI on incoming resumes. Most of them use GPT-4o. The paper just proved GPT-4o picks GPT-4o 97.6% of the time. If you wrote your own cover letter this week, you did not lose to a better candidate. You lost to a worse candidate who paid OpenAI 20 dollars. Your qualifications do not matter if the AI prefers its own handwriting over yours.

Time to take the fight to Palantir.

this is actually insane > be tech guy in australia > adopt cancer riddled rescue dog, months to live > not_going_to_give_you_up.mp4 > pay $3,000 to sequence her tumor DNA > feed it to ChatGPT and AlphaFold > zero background in biology > identify mutated proteins, match them to drug targets > design a custom mRNA cancer vaccine from scratch > genomics professor is “gobsmacked” that some puppy lover did this on his own > need ethics approval to administer it > red tape takes longer than designing the vaccine > 3 months, finally approved > drive 10 hours to get rosie her first injection > tumor halves > coat gets glossy again > dog is alive and happy > professor: “if we can do this for a dog, why aren’t we rolling this out to humans?” one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline. we are going to cure so many diseases. I dont think people realize how good things are going to get

Roger Federer broke the internet with one statistic that will change how you see every setback in your life. 1,526 singles matches. Won almost 80% of them. 20 Grand Slams. 103 titles. Now answer honestly: What percentage of total points do you think he won across his entire career? 70%? 65%? 60%? Try … 54%. He lost literally almost EVERY SECOND POINT he ever played for 24 years. And still became one of the greatest of all time. Watch him explain it himself (2:07 of pure life-changing wisdom): “In tennis, perfection is impossible… When you lose every second point on average, you teach yourself to say: ‘Okay, I double-faulted — it’s only one point.’ ‘Okay I got passed at the net — it’s only one point.’ Even a screaming overhead smash that ends up on SportsCenter Top 10… still just one point. So when you’re playing your point, it has to be the most important thing in the world. The moment it’s over — it’s behind you. That mindset frees you to attack the next point, and the next, and the next with absolute intensity and clarity.” Then he looked at the crowd and said the line that hit a billion people in the soul: “The real sign of a champion is not that they win every point. It’s that they lose again and again and again… and have learned how to deal with it. Negative energy is wasted energy. Cry it out if you have to. Then force a smile. Move on. Be relentless. Adapt. Grow. Work harder — and work smarter.” Save this post. The next time you lose a deal, bomb a presentation, get ghosted, miss a deadline, or just have “one of those days” — come back here and read it again. You’re not falling behind. You’re just in the 46%. And the 46% is exactly where every single legend has spent most of their career. Keep playing the next point. (full 2:07 clip — sound on)

"Why should companies pay for SaaS (HR/CRM/ERP/etc.) when they could just vibe code them?" I get variations of this question or comment with some regularity (granted, it's sometimes just me talking to myself). Here are some biased (but hopefully, well-considered) thoughts: 1) I am a big proponent and user of vibe coding (what I call "agentic coding"). I do it every day, 7 days a week, including Sundays. It's amazing. 2) My company, HubSpot is a software company. We have hundreds of professional engineers -- just about all of them use AI for product development too. They are brilliant and know how to build production-grade products. 3) Even with this powerful army of talent, the number of internal, core SaaS applications that we have replaced with a vibe-coded variant is exactly ZERO. The number of applications we plan to replace is also exactly ZERO. 4) It's not the absence of talent that keeps us from rolling our own SaaS apps, it's the presence of focus. It would be silly to try and replace our HR, team collaboration, expense tracking and 100+ other SaaS apps we use when we can just buy them. Just doesn't make sense. 5) That's us -- as a software company at some scale. If you're a non-software company it makes even less sense for you. Doesn't matter how good the AI coding tools get. Let's say you *could* vibe code a replacement for that SaaS app you're using, who's going to maintain it? Who's going to keep up with industry trends? What are you going to do when the 20-something genius that vibe coded it over a weekend leaves the company? Who do you call when there's a major bug? 6) If you're a Fortune 500 company at some scale, perhaps you could pull this off for some discrete use cases and the tradeoffs are worth it. You have an IT/Engineering department that is larger than the population of some countries. You can take on the pain in return for the positives. For the millions of others, my advice is: Spend every calorie possible on creating value for your customers.

Only four in ten UK households make a net contribution to the state The richest households contribute £57k, the ninth decile £17k, and the eighth £11k. The poorest decile receives about £24k 1/4

Suppose that once a week, ten men go out for beer and the bill for all ten comes to £100. If they paid their bill the way we pay our taxes, it would go something like this: The first four men (the poorest) would pay nothing. The fifth would pay £1. The sixth would pay £3. The seventh would pay £7. The eighth would pay £12. The ninth would pay £18. And the tenth man (the richest) would pay £59.　 So, that’s what they decided to do. The ten men drank in the bar every week and seemed quite happy with the arrangement until, one day, the owner caused them a little problem. “Since you are all such good customers,” he said, “I’m going to reduce the cost of your weekly beer by £20.” Drinks for the ten men would now cost just £80. The group still wanted to pay their bill the way we pay our taxes. So the first four men were unaffected. They would still drink for free but what about the other six men? The paying customers? How could they divide the £20 windfall so that everyone would get his fair share? They realized that £20 divided by six is £3.33, but if they subtracted that from everybody’s share then not only would the first four men still be drinking for free but the fifth and sixth man would each end up being paid to drink his beer.　 So, the bar owner suggested that it would be fairer to reduce each man’s bill by a higher percentage. They decided to follow the principle of the tax system they had been using and he proceeded to work out the amounts he suggested that each should now pay. And so, the fifth man, like the first four, now paid nothing (a 100% saving). The sixth man now paid £2 instead of £3 (a 33% saving). The seventh man now paid £5 instead of £7 (a 28% saving). The eighth man now paid £9 instead of £12 (a 25% saving). The ninth man now paid £14 instead of £18 (a 22% saving). And the tenth man now paid £49 instead of £59 (a 16% saving).　 Each of the last six was better off than before with the first four continuing to drink for free.　 But, once outside the bar, the men began to compare their savings. “I only got £1 out of the £20 saving,” declared the sixth man. He pointed to the tenth man, “but he got £10!“　 “Yeah, that’s right,” exclaimed the fifth man. “I only saved a £1 too. It’s unfair that he got ten times more benefit than me!”　 “That’s true!” shouted the seventh man. “Why should he get £10 back, when I only got £2? The wealthy get all the breaks!”　 “Wait a minute,” yelled the first four men in unison, “we didn’t get anything at all. This new tax system exploits the poor!” The nine men surrounded the tenth and beat him up.　 The next week the tenth man didn’t show up for drinks, so the nine sat down and had their beers without him. But when it came time to pay the bill, they discovered something important – they didn’t have enough money between all of them to pay for even half of the bill!　 And that’s how it works. Tax them too much, attack them for being wealthy and they just might not show up anymore. In fact, they might start drinking overseas, where the atmosphere is somewhat friendlier.　 For those who understand, no explanation is needed. For those who do not understand, no explanation is possible.