Plus de 639.000 vues après un long marathon de 11h en direct. Merci beaucoup à notre communauté qui ne cesse de montrer son soutien continu à la chaîne.
RV demain In Shaa Allah demain en direct de Dakar Arena pour terminer ce week-end de travail en beauté!🙏🏾
La Coupe du monde commence dans une semaine, et @footdigest fait peau neuve.
Des analyses d'avant et d'après-match, des stats en direct et leur impact, et un simulateur pour jouer les 104 matchs avant même le coup d'envoi.
Suivez toute la compétition à votre rythme sur https://t.co/RSmpt4T5vj
1/ World model research is fragmented: every paper reimplements its own data pipeline, baselines, and eval harness. Comparing two methods fairly is weeks of infra work.
𝘀𝘁𝗮𝗯𝗹𝗲-𝘄𝗼𝗿𝗹𝗱𝗺𝗼𝗱𝗲𝗹 is a new open-source platform that standardizes the whole thing: https://t.co/Gg3V3LhKJr
Why is the creator of OpenCode pretty skeptical about AI productivity gains, and the hype around AI? A very conversation @thdxr (and lots of truth bombs:)
Timestamps:
00:00 Intro
07:03 Dax’s path into tech
09:04 Early startup experience
13:16 Getting involved with open source
16:13 OpenCode
23:17 Anthropic banning OpenCode
30:34 From terminal to GUI
32:34 OpenCode’s business model
36:33 Why inference is profitable
39:11 GPU bottlenecks
40:54 AI hype
45:50 AI spending
48:47 Dax’s memo
55:41 Dax’s skepticism of predictions
58:58 Engineering culture at OpenCode
1:02:38 How building works at OpenCode
1:05:36 Taste and quality
1:11:32 Dax’s work setup
1:12:35 The role of engineers and EMs
1:15:50 Advice for engineers
1:18:12 Book recommendation
Brought to you by:
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• @turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable https://t.co/w9y67Gs8ab
Three interesting thoughts from Dax:
1. No AI-native coding agent company is “winning” by being better with AI.
Dax says that none of OpenCode’s competitors are crushing them, and that nobody is using AI so well that others cannot compete.
2. Most software engineers profit from AI as time gained, not increased output — unless you change incentives!
Dax says the natural way for software engineers to “cash out” their AI tooling gains is with time savings, by doing the same work as before, but faster. Until compensation and motivation structures change, most teams should expect output to stay flat while engineers go home earlier. There’s nothing wrong with this, but AI vendors sell a different outcome to CFOs: increased output.
3. AI code generation mutes the “guilt” of doing the wrong thing, but this builds up tech debt.
Pre-AI, writing a hack felt bad, the second time it felt really bad, and by the third time you’d often just refactor in order to fix up the code. Now, the agent hides the hack, which skews devs’ judgment and results in less tech debt being cleaned up.
Ouf, enfin les congés 🕺. Cette première partie de l'année a été intense pour mon équipe et moi: plateforme déployée de bout en bout dans 5 pays, plus de 4 millions de dollars de revenus générés, des centaines de personnes formées et autonomisées. Je suis épuisé, mais extrêmement fier de ce que nous avons accompli. Maintenant, place au mouton, à la fête, à la famille et aux plages. Je vais réduire ma présence en ligne au maximum, mais Insh'Allah je continuerai à écrire sur Substack. Eid Mubarak en avance à tous ceux qui célèbrent. Prenez soin de vous. 🐏🌴✈️
Meet Gemini 3.5 Flash — our strongest agentic and coding model yet.
It delivers frontier-level performance at 4x the speed of comparable frontier models — often at less than half the cost.
Generally available, starting today. 🧵
#GoogleIO