Terra API

That’s a wrap-up for the first Terra Health Day in San Francisco. Hundreds of @ycombinator founders got their morning workout kick with Pickleball games and some pull-ups. @bryan_johnson, the world’s most measured man, then took the stage to speak about the philosophy of longevity: Don’t Die @lancearmstrong then, in discussion with @kyriakosel, spoke about the early days, the Tour De France, the winning mindset, and the secrets of investing. More details soon!

Most people still think cycling to work is the slower option. Better for your health, better for the environment. But slower. I wasn’t convinced, so I looked at the data. I matched commute looking cycling activities against both TfL journey times and Google’s rush-hour driving estimates. The result surprised me. On 1,628 fully matched weekday commutes: • Cycling beat @TfL estimates on 92% of journeys, with a median saving of 15 minutes. • Cycling beat Google’s rush-hour driving estimate on 75% of journeys, with a median saving of 5 minutes. The busiest commuting corridors into central London were the most striking. Routes from places like Hammersmith, Wandsworth and Clapham to the City consistently favoured the bike, often saving well over 10 minutes. One result I didn’t expect was that the advantage didn’t disappear on longer commutes. I assumed the Tube would become increasingly competitive. Instead, cycling continued to perform remarkably well. That may reflect a group of committed cyclists, or the fact that people are more likely to ride longer distances when the transport network is disrupted. There are important caveats. This data only tells me about the recorded bike activity, not necessarily the entire door-to-door journey. Some people may combine cycling with walking or public transport, while the TfL and Google estimates are complete origin-to-destination trips. So this isn’t a perfect race between transport modes. But the overall pattern is hard to ignore. For many London commuters, the bike isn’t just the healthier choice. It’s the faster one. I’d happily ride even if it took a few minutes longer. I used to commute to school by bike, and still ride E-bikes as much as I can. Fresh air, a bit of movement before work, and seeing London from street level beats sitting underground. It turns out I often get there sooner as well. What’s your experience? Has cycling changed the way you commute? Full research linked to below #activetravel #healthdata #commuting

"If my doctor disagrees with ChatGPT, I change doctors." @vkhosla about the future of healthcare at the @TerraAPI x @ycombinator startup school dinner: “AI is the only way to scale medicine to be the highest quality. And it’s the only way to be objective, because humans have biases.” "There will be more than one breakthrough companies. Healthcare has too many large niches for there to be only one" The $4 trillion US healthcare system has four rough buckets: 1. Expertise 2. Diagnostics, testing and imaging 3. Drugs and therapeutics 4. Hospitals and critical care Mental health, primary care, chronic disease management, gastroenterology, neurology and endocrinology will be nearly free. “All these things will cost $2 an hour, not $400 an hour, delivered by an AI” “There is zero chance your oncologist remembers the last 5,000 articles on breast cancer that were published, usually in the last year or two. The volume of literature is so high, no human being can keep up.”

"It's better to be brutally honest than hypocritically polite" - @vkhosla The fireside chat was full of wisdom. Thank you sir and @TerraAPI. We see great innovations happen from places where failures are not treated bad, encouraging people to take risks. Always have your own objectives on why you want to start your company/work on something. All are valid. Successful people have clear objectives. The biggest impact we are gonna see in is healthcare, data shows AI are better than humans in diagnosis and help reduce the false diagnosis and companies backed by khosla ventures showing more than 90% compared to 73% accuracy by humans. #YCStartupSchool @ycombinator #AIxHealthcare

Perhaps the most @vkhosla line of the night: If his doctor’s answer differs from ChatGPT’s, he is more likely to replace the doctor. His broader point was about agency: take ownership of your health, question conclusions, and even go “founder mode” on cancer. I had the chance to hear Vinod Khosla in person for the first time at the YC Health × AI fireside hosted by @TerraAPI last night. I left incredibly energized. He is every bit the legendary investor and first-principles thinker I had imagined. The message that touched me most was simple: Dream bigger. Take bigger risks. Be willing to fail. What does “big” mean? Healthcare is one example. The world’s best medical knowledge already exists, but most people cannot access the world’s best doctors. AI may be the only way to scale the best medicine to everyone. Another important question was: Who should you listen to? Don’t automatically ask your friends. Are they actually qualified to advise you? Advice from people shaped by large organizations may not help you create a breakthrough. Listen carefully, but have your own reasons and judgment. He mentioned telling Sam Altman something to the effect that nobody around him is fully honest with him. That is why honest disagreement matters. The same applies to customers. Users can describe their problems, but they do not always know the transformation they want. A founder cannot simply say yes to every request. Return to your mission. Decide what should exist. Think from first principles. After the talk, I kept thinking about one question: How do I learn to dream bigger? When I internalized it, I realized I already had my own answers: - Trust myself and remember my purpose - Think from first principles and long term - Start with a focused niche, get fast feedback and early wins, then build toward something much larger - Become more willing to take risks and fail This is something I need to improve. Entrepreneurs make things happen. Time to make it happen.

Wrapping up YC SUS Day 1 with Health X Khosla @vkhosla @TerraAPI Enjoyed discussion about scaling healthcare with AI. Good creatine gummies too.

Thanks to @TerraAPI for hosting @vkhosla. Genuinely one of the best talks I’ve ever heard.

Marketing in SF has reached the sky too not just billboards. @TerraAPI

THE @ycombinator startup school ALREADY STARTED TERRA HEALTH DAY

Read the paper: tryterra.co/research/how-s…

We studied the night Spain won the World Cup During the game, heart rate stayed 1.63 bpm higher than a normal Sunday They moved less than usual while watching, around 100 fewer steps per hour At the final whistle, heart rates jumped more than 7 bpm - the largest spike of any country Madrid celebrated the hardest, followed by Málaga, Barcelona and San Sebastián The next day many Spaniards called in sick. Average bedtime had shifted 42 minutes later than usual

"In two years, 90% of our customer base will be agents instead of developers.” @xatzistnr co-founded @foodycy, growing it from phone orders and an Excel back office to the biggest tech acquisition in Cyprus. Now he leads engineering strategy at Terra. Some insights from the discussion: - You can one-shot an app. You cannot one-shot an app that scales to 100 million users - MCPs are just APIs with instructions on top - Nothing operates well beyond 100k tokens - Every API today is written for humans, and agents lose context reading them - The decision log is the most valuable asset AI creates inside a company

Should you stack cold plunge after sauna? We analyzed ~36,000 sauna and cold plunge sessions to find out. Sauna alone wins for recovery. Sauna raises HRV and lowers nighttime heart rate - both the night of and the night after - even after controlling for workouts, alcohol, illness, and stress. Cold plunge alone barely moves the needle. Only 1 of 6 measures was clearly positive. Combining them gives the same heart rate drop as sauna alone, with no extra HRV benefit. The cold isn’t adding anything meaningful on top of the heat.

Does heat slow runners down, or make them slow down? I studied 3,361 outdoor runs from 878 users, matched against hourly temperature data. A run starting at 25°C was, on average, ~10 sec/km slower and 1.3 km shorter than a run starting at 5°C. But heart rate stayed broadly flat. I expected heat to show up as higher cardiovascular strain at the same pace. It didn’t. The data suggested something different: Runners slowed down slightly, shortened their runs, and kept their effort under control. Wearable data is often treated as pure physiology. But it also captures behaviour. The choice to go out, to go harder, to ease up, to turn back early, or to self-regulate before the body forces you, each reflects a conscious decision. It seems the heat does not make runners slow down; instead, runners slow down because of the heat

Who actually plays the most football? We analyzed 30,000+ sessions globally as the 2026 World Cup gets underway Chileans top the world at 4.1% logging football regularly - Guatemalans and Hondurans follow Norwegians lead Europe, and nearly a third of their sessions - and those of Brits - happen on Mondays The countries hosting this year's tournament aren't anywhere near the top

Did you know that eating late meals affects not only your sleep but your heart rate, too?! This was quite hard for me to wrap my head around. At @TerraAPI Research, we analysed thousands of nights of wearable data to explore whether late eating meaningfully impacts sleep. Not in a lab, not in a controlled setting, but in the messy reality of everyday life. There is a relationship between late eating and sleep. Eating closer to bedtime is associated with slightly worse recovery, as evidenced by higher heart rate, later sleep onset, more awake time and small changes in sleep structure (although sleep structure measured with wearables should be taken with a pinch of salt), but the magnitude is modest. If you’re interested, link to the full research is in the comments below

“The best founders pattern match on success, not failure - and stay ridiculously, stupidly optimistic.” @gralston is the former President of @ycombinator, the true internet pioneer with exits to Yahoo and Apple. He is now running @SAIFVC, since ‘Humanity is running on a tight rope right now’ We discussed: 0:00 Introduction 2:10 Why Silicon Valley celebrates startups 4:45 The single venture deal that created Sand Hill Road 7:55 Startup timing 11:20 The moment he quit HP 16:40 @paulg acquisition framework 26:10 Startups die from suicide 30:50 How to tell if someone is actually better than you 34:20 The day Zuck killed his company in one decision 38:55 The Steve Jobs lesson that still guides him 42:30 The real YC superpower almost nobody talks about 46:40 How far YC can actually scale 54:06 Why AI is more dangerous than people think 01:01:15 Peter Thiel is wrong about competition 01:03:31 Marc Andreessen is wrong about introspection 01:05:18 What he tried to teach his children

London 'heatwave' with @AliBrownleetri and our running club Run and intervals

Do people actually sleep better alone or together? Conventional wisdom says having a partner is good for long-term health. In theory a big chunk of that benefit should show up during sleep, our prime recovery window. So I decided to test the hypothesis: Does sharing a bed actually improve sleep and recovery? I analysed a large dataset of wearable sleep records where users had labeled whether they slept alone or with a partner. So what did I find…The results were more nuanced than I expected. • Shared-bed nights showed more awake time (roughly +8-11 minutes) and slightly less total sleep time! I’ll leave it to the reader to hypothesise on this. • Resting heart rate tended to be lower on shared nights in population views, but RMSSD (HRV) was modestly lower. • Alone-dominant users showed more stable night-to-night sleep (lower coefficient of variation). • The patterns held across population, within-person, and lifestyle cohort views, though effect sizes were generally small. The data suggests that, on average, sleeping alone is associated with better sleep continuity (less awake time, more sleep), while the recovery marker story is mixed. Of course, this is all observational. There are clear limitations and potential confounders: people who diligently label their sleep data might not be representative, alone nights often happen during travel, and we can’t cleanly separate causation from correlation. I wouldn’t rush to the spare room just yet. Unless you’re a hardcore recovery optimiser willing to run your own 10+ night experiment (controlling what you can), the data doesn’t scream that sharing a bed is ruining your recovery! Full research in the comments below