☕️Sebastián Pérez Saaibi☕️

“Spokesman” looking for a job, i hear

a lot of engineering orgs (Stripe, Ramp, Coinbase) are building internal cloud coding agents we're releasing a fully OSS one today - every company should have the power of cloud agents at their fingertips

curl -X POST agents.ramp.com/cards/waitlist -d website=yoursite.com -d email=you@yoursite.com

Stuff like this is the easiest management problem to solve. Make slop, get a stern warning. Do it again, you’re gone. Yahoo is bound to have layoffs soon. Might as well attrit this way instead.

A small thank you to everyone using Claude: We’re doubling usage outside our peak hours for the next two weeks.

Latin America has a serious pipeline problem in mathematics education. I regularly interview candidates, and one thing becomes clear very quickly: even graduates from top universities in the region often lack solid mathematical foundations. That’s not a talent issue. The talent is clearly there. It’s a system problem. You can see it in outcomes. Latin America rarely appears near the top in major international mathematics competitions, despite having a large population and plenty of capable students. The training pipeline simply isn’t producing enough mathematically strong graduates. Because of this, for many companies in the region, a graduate from a mid-tier U.S. STEM university is often perceived as significantly stronger than a graduate from even a leading local university. That gap says a lot about the structure of the education system. Brazil might be a partial exception — it has several strong institutions and a more developed research ecosystem — but across much of the region the mathematics pipeline still needs serious strengthening. The potential is there. The system just needs to unlock it.

Amazon had four Sev-1 outages (their highest severity level) in a single week. Internal memos say AI-assisted code changes were a contributing factor. The timeline here is wild. In October 2025, Amazon laid off 14,000 corporate employees. In January 2026, another 16,000. That’s about 30,000 people in five months, roughly 10% of the corporate workforce. CEO Andy Jassy said the cuts were about culture, not AI. During those same months, Amazon set a target: 80% of developers using AI coding tools at least once a week. They tracked adoption closely and blocked rival tools like OpenAI’s Codex. Even so, 30% of developers still hadn’t touched Amazon’s in-house tool Kiro by January. In December 2025, Kiro caused a 13-hour AWS outage. The AI tool had production-level permissions and decided the best fix for a bug was to delete and recreate an entire live environment. A second incident involved Amazon Q Developer, another AI tool. Amazon blamed both on “user error, not AI.” But quietly added mandatory peer review for all production access afterward. Then March 5: Amazon’s retail site went down for about six hours. Over 22,000 users reported checkout failures, missing prices, and app crashes. Amazon called it a “software code deployment” error. Five days later, SVP Dave Treadwell made the normally optional weekly engineering meeting mandatory. His memo acknowledged “GenAI tools supplementing or accelerating production change instructions, leading to unsafe practices.” These problems trace back to Q3 2025. Amazon’s own assessment: their GenAI safeguards “are not yet fully established.” The new rule: junior and mid-level engineers now need senior sign-off on any AI-assisted production changes. Treadwell also announced “controlled friction” for the most critical parts of the retail experience. For context, Google’s 2025 DORA report found 90% of developers use AI for coding but only 24% trust it “a lot.” An Uplevel study of 800 developers found Copilot users introduced 41% more bugs with no improvement in output. Amazon is finding out what those numbers look like at the scale of a $500 Billion revenue company, with 30,000 fewer people on staff to catch the mistakes.

Cursor events in these cities over the next two weeks: • Barcelona • Ljubljana • Brisbane • Barranquilla • Copenhagen • Riga • Detroit • Salt Lake City • Cebu • Bangkok • Manila • Mannheim • Istanbul • Bangalore • Buenos Aires • Calgary • Stockholm • São Paulo • Kigali • Porto Alegre • Zurich • Toronto • Mexico City • Monterrey • Valdivia • London • Cotonou • Heilbronn • Lomé • Shenzhen • Vancouver

tru

AMAZON PRIME VIDEO BLOODBATH 2,847 employees got the email at 6:47 AM PST "Your role has been eliminated effective immediately" Badges dead by 7:15 AM. Slack access revoked mid-sentence Senior engineers who built the entire streaming infrastructure. Gone The team that shipped 40% faster last quarter using Claude for code generation. Eliminated 847 contractors in Bangalore just got handed their prompt libraries and deployment scripts Same streaming platform. Same feature velocity expected 14 remaining Seattle engineers to "manage AI-augmented offshore delivery" The kicker: those eliminated seniors spent 8 months documenting every architectural decision into internal wikis Every code pattern. Every debugging workflow. Every performance optimization trick That documentation just became training data for the AI systems replacing them VP of Engineering sent company-wide: "This transition represents our commitment to AI-first development" Severance packages include mandatory 90-day non-compete clauses Meanwhile the Bangalore team already pushed 12 commits using the extracted knowledge base One former L7 told me: "I literally trained the AI that made me redundant" If you're at FAANG and not seeing this coming you're already dead DMs open for anyone who needs to talk

OK this thing is totally insane. Before going to bed I... * used try to make a new qmdresearcher directory * told my pi to read this github repo and make a version of that for the qmd query-expansion model with the goal of highest quality score and speed. Get training data from tobi/qmd github. * woke up to +19% score on a 0.8b model (higher than previous 1.6b) after 8 hours and 37 experiments. I'm not a ML researcher of course. I'm sure way more sophisticated stuff is being done by real researchers. But its mesmerizing to just read it reasoning its way through the experiments. I learned more from that than months of following ml researchers. I just asked it to also make a new reranker and its already got higher base than the previous one. Incredible.

Ahí tiene su “desinformación” pintada

💯 how do companies move fast? picking leads that can own design, eng and product and more why? less ceremony and "conceptual integrity" for the product 👉 you ship faster and higher quality if you don't, any AI gains are offset by process drag

I have a little different take on this, and I say that with all the admiration for that team, which I honestly think it is one of the best teams I ever had the pleasure to work with when it comes to understanding developers. I owe them everything I know. Here's my take: They spent years becoming masters of that craft: To make every line of code beautiful, the most delightful code editing experience for humans. And they became the best at that. Their tools became standard across all the tech industry. The challenge is that the world changed fast, and now if you are worried about the line of code editing experience for humans, you are building a typewriter while others build computers. Any team, anywhere, would struggle to change culture so fast and completely shift the focus to a world where AI is your main user and the developer is no longer the one writing or even looking at code anymore. (And many other similar teams too are struggling with this right now. It's not like someone already had the recipe for others to copy) The only thing orders of magnitude harder than learning how to ride a bicycle is unlearning it. In times like this, you have a better shot by starting from zero rather than refactoring.

Unfortunately I think we'll see meaningful layoffs in software this year. And I want to explain why it's just air cover to call them "AI-driven layoffs", even though every company will do so. Yes, AI makes companies more efficient. Developers and marketers can do more. CSMs can have a wider span of control. You can answer 70% of your tier 1 support cases with AI. But that's not really what's going on. But two things are more elemental to the situation, and the actual driver: 1. Valuations have reset, with a totally valid and reasonable focus on free cash flow minus stock compensation. And the math simply doesn't math. 2. Many of these companies staffed up during COVID and never actually took their medicine and got fit. They thought demand would come back and it mostly hasn't. Not in the same way. Illustrative example, to pick on two companies, Atlassian and HubSpot, that I actually really admire: - Age: Atlassian is 24 years old. HubSpot is 19 years old - # of employees: Atlassian has 14k employees at $22B market cap. HubSpot has 9k employees at $15B market cap - SBC-Adjusted FCF: Basically ZERO That's right. After 20 years, the actual cash generated and available to shareholders is ZERO I do think the owners of these businesses understand that is no longer tenable. But they have two issues now: 1. The actual technical talent needs to get paid 2. Their stocks are down 60-70% from recent highs So here's the situation: They need to start making actual money, they have to pay their tech talent, their dollar grants are going to have serious dilution consequences, and their cost structures are completely bloated for their current market cap, especially compared to more nimble competitors. If they keep paying all of these people in stock, their dilution will continue and the stocks will continue to be punished. If they pay them all in cash, they will have no fcf. TL;DR Layoffs are unfortunately the only true answer. They are coming. They will be credited to AI, and that will be air cover for the real problem.

Codex Security is now also available on ChatGPT Pro accounts.

I often don’t share this kind of thing because it’s usually AI slop. But this article about building a Chief of Staff with Claude Code is one of the best real examples of agentic systems I’ve seen.

Por ahí si va!

The PM playbook of writing PRDs and aligning stakeholders is dead. At Brex, Product Managers design agent workflows, go deep on model behavior, live inside our P&L, and own outcomes end-to-end — from 0→1 to production across tens of thousands of finance teams. And combined with Capital One, Brex will soon be operating at an unprecedented scale and serving millions of businesses in the US. I’m hiring PMs to work with me on some of our top initiatives. Here’s what we’re looking for: - You use AI Coding tools every day to build your own artifacts, not just overseeing people who do - Founder DNA — you’ve built something from scratch, or you will - Extraordinarily high agency and product taste, obsess over craft and design details - In-person in SF, NYC, Seattle, Vancouver or São Paulo Come define the next version of the PM role here. Open product roles below / DM or email: pedro@brex.com

Google just dropped an official CLI for gmail, drive, calendar sheets and more complete with skills and an MCP server 👌