Alexis Rondeau

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Bookmarked from European Defense Tech @Eurodefensetech

“To win this war, everybody has to sit down and think: What can I do?”

In October, we hosted Europe’s biggest Defense Tech Hackathon together with TUM Venture Labs for the 4th time in Munich 💥

Over 300 participants worked across 56 projects, with a special focus on counter-drone solutions to protect our airspace, from detection to classification and interception.

A huge thank you to our key partner @HelsingAI, our hackathon partner Lateration, and everyone else, including TYTAN Technologies, Pilotix, IABG, Autonomous Teaming, Bifrost Defence, SE3 Labs, and the Ukrainian Ministry of Defense @DefenceU for supporting us and making this possible!

Special thanks go to TUM Venture Labs for hosting us — especially Connor Rehn, Florian Doetzer, Antoine Leboyer — and to German Stelmakh 🇺🇦 & Artem Melnychuk (DroneAid Collective), Jonatan H. Luther-Bergquist @mountbranch (EDTH/@inflection_fund), Paolo Trecate & @AkimKarpach9 (EDTH) for co-organizing.

Excited to be back in Munich in February for one of our most important hackathons next year, in parallel to the Munich Security Conference @MunSecConf!

Video credit: @AkimKarpach9

Bookmarked from DHH @dhh

Whenever I see programmer salary numbers from Europe, I always have to do a double take. It's hard to fathom that we work in the same industry. With bonuses this year, many of our folks are at $400,000+, and we're not even in any AI-hype sector.

Bookmarked from Bryan Johnson @bryan_johnson

Three exciting longevity results came back from my first dose of mushrooms: >35% decrease in inflammation, a deeply relaxed state and neuroprotective effects.

Inflammation (hsCRP)
My systematic inflammation levels dropped from elite to undetectable. This decrease is significant, aligning with clinical reports of reduced inflammation markers (CRP, TNF-alpha, and IL6) seven days post high dose psilocybin.

+ pre-mushrooms: 0.23mg/dL
+ post-mushrooms: < detection limit 0.15mg/dL
+ >35% decrease

Deep low stress state (HPA Axis)
My cortisol and DHEA-S dropped by 42% and 45%, respectively, suggesting a profound inhibition of the Hypothalamus-Pituitary-Adrenal (HPA) axis, which corresponds with the "after-glow" effect.

+ DHEA-S: 287µg/dL to 157 µg/dL
+ morning cortisol: 10.3 µg/dL to 5.9 µg/dL

While cortisol spikes acutely during the trip, the post-session drop indicates a shift from sympathetic to parasympathetic dominance. This aligns with my sustained relaxed and joyful state.

Neuroprotection (Estradiol)
Estradiol increased 3x (11.3 to 36 pg/ml). This may be due to peripheral activation of 5HT2A receptors stimulating aromatase activity, the enzyme that converts testosterone to estradiol.

A study has shown 5HT2A stimulation in human placental cells can drive aromatase gene expression and activity. My testosterone levels remained unchanged, indicating my body compensated for the minor conversion to estradiol.

The increase is within the normal male range and is generally positive, as estradiol provides anti-inflammatory, neuroprotective and cardiovascular protective effects.

Conclusion
Taken together, these data suggest that a single high dose psilocybin experience can transiently push my biology into a low inflammation, low stress configuration that is theoretically favorable for longevity.

Measurement window: 4 days before vs. 5 days post-dose

Bookmarked from GREG ISENBERG @gregisenberg

i reverse engineered 8 apps that hit $50K MRR in under 180 days and explain the pattern behind all of them

1/ find a group that spends money
2/ find a problem they repeat weekly
3/ use AI to make it work with photos/videos/inputs
4/ make the output dead-accurate
5/ replace their slow existing tools

full breakdown in the video along with my 6 mobile app frameworks and 25+ startup ideas

all free. i want to see you build some iconic apps.

i believe 2026 is an incredible time to be building mobile apps

happy building, my friends.

Bookmarked from Nic Cruz Patane @niccruzpatane

NVIDIA CEO Jensen Huang said @elonmusk was there for him as a customer when nobody else was.

“When I announced this thing, nobody in the world wanted it. I had no purchase orders—not one. Nobody wanted to buy it. Nobody wanted to be part of it, except for Elon. He was at the event, and we were doing a fireside chat about the future of self-driving cars. And he goes, “You know what? I have a company that could really use this.” And I said, “Wow, my first customer.” I was pretty excited about it. And he goes, “Yeah, we have this company. It’s a non-profit company”, and all the blood drained out of my face. I had just spent a few billion dollars building this thing. It cost $300,000. And the chances of a non-profit being able to pay for this thing were approximately zero, and he goes, “You know, it’s an AI company, and it’s a non-profit. And we could really use one of these supercomputers.”

So I picked it up. I built the first one for ourselves—we’re using it inside the company. I boxed one up, drove it up to San Francisco, and delivered it to Elon in 2016. I walked up to the second floor, where they were all kind of crammed into a room smaller than this place here, and that place turned out to be OpenAI.”

Bookmarked from Lenny Rachitsky @lennysan

My biggest learnings from Jeanne DeWitt Grosser (ex-Chief Business Officer at @Stripe, now @Vercel COO):

1. What failed seven years ago now works with AI. In 2017, Jeanne tried to build a system at Stripe that would automatically personalize outbound emails based on company data. Despite working with world-class data scientists, it failed due to too many errors. Today, that exact same approach works. This shows how AI has made previously impossible ideas suddenly viable.

2. A single GTM engineer at Vercel reduced a 10-person sales team to 1 (in just 6 weeks). Jeanne’s team at Vercel had an engineer build an AI agent that handles inbound lead qualification, outbound prospecting, and deal loss evaluation. The agent costs $1,000 per year to run versus over $1 million in salaries for the sales team. The nine displaced team members moved to higher-value work rather than being laid off, and the remaining salesperson is 10 times more efficient.

3. Their AI deal-loss bot has become better at understanding what went wrong than humans. When Jeanne analyzed her biggest loss of the quarter, the salesperson blamed pricing. But an AI agent reviewed every email, call transcript, and Slack message and discovered the real reason: they never spoke to the person who controls the budget, and when ROI came up, the customer clearly didn’t believe the value claims. They are now using AI to analyze sales calls in real time and send alerts like “You’re halfway through the sales process and haven’t talked to a budget decision-maker yet.”

4. Wait until $1 million in revenue before hiring your first salesperson. Founders should continue selling themselves until they reach around $1 million in annual revenue with a repeatable process. The key is having a defined ideal customer profile—customers who look alike.

5. Segment customers on what drives their buying decisions, not just company size. OpenAI has roughly 3,000 employees, which would typically put them in the “mid-market” category. But they’re a top-25 website globally by traffic, so Vercel treats them as enterprise customers requiring complex sales. Effective segmentation combines company size with growth rate, web traffic, workload type, and industry—because selling to e-commerce companies requires completely different language than selling to crypto companies.

6. Most customers buy to avoid risk, not to gain opportunity. About 80% of customers purchase to reduce pain or avoid problems, while only 20% buy to increase upside. This means you should focus your sales messaging on what could go wrong without your product—like falling behind competitors or damaging their reputation—rather than just talking about exciting features. This is especially true when selling to larger companies, where individual careers are on the line.

7. Sales teams should be indistinguishable from product managers—for a bit. Jeanne hires salespeople who have such deep product knowledge that if you put one in front of a group of engineers, it should take 10 minutes to realize they’re not a product manager. This credibility allows sales teams to serve as an extension of research and development—a 20-person sales team talks to hundreds of customers weekly and can translate those conversations into product insights at scale.

8. Building your own AI sales tools may beat buying off-the-shelf software. Because AI is so new and every company’s sales process is unique, Jeanne finds that building custom internal agents often delivers more value than buying vendor solutions. A single go-to-market engineer built their deal analysis bot in just two days, perfectly tailored to their specific workflow. These engineers shadow top salespeople to understand their workflows, then build automation that would have taken months or been impossible just a few years ago.

9. Make every sales interaction great, whether customers buy or not. Jeanne replaced boring discovery calls at Stripe with collaborative whiteboarding sessions where customers drew their payment architecture. Many customers had never visualized their own systems before. They left with a useful asset and a feeling of collaboration, regardless of whether they bought. Many returned years later to purchase. Think about your go-to-market process like a product, not just a sales function.

10. Product-led growth has a ceiling—no $100 billion company runs on it alone. While product-led growth (where users can sign up and start using a product without talking to sales) works well for early growth, customers generally won’t spend a million dollars through a self-service flow. Every major technology company eventually builds a sales team for larger deals. The mistake is waiting too long, since building a predictable sales process takes time.