Un `SKILL.md` signé Google Chrome pour injecter les bonnes pratiques web modernes directement dans vos agents de code — APIs natives, performance, accessibilité, au lieu des vieux patterns que les LLMs reproduisent par défaut.
https://t.co/Kt18SjxPKC
Picsou 1.0.0 est dispo!
Votre outil de gestion de patrimoine gratuit, entièrement hébergé chez vous avec la synchronisation pour les comptes bancaires + Trade Republic.
Have fun =)
https://t.co/YBtBXQbIJ3
One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.
The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.
The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.
However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.
Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.
What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.
[Original text: The Batch newsletter]
🔴🇫🇷 ALERTE — Le DMP (Dossier Médical Partagé), un service public numérique de santé destiné à des millions d'assurés français, aurait été compromis.
Plus de 34 millions de personnes seraient potentiellement concernées, avec l'exposition présumée de données telles que :
👉 noms et prénoms
👉 numéros de sécurité sociale
👉 IBAN
👉 adresses postales
👉 adresses e-mail
👉 numéros de téléphone
Un jour, une fuite... c'est une hécatombe.
Après Almerys, c'est désormais un service public de santé français qui se retrouve au cœur d'une revendication de piratage de grande ampleur.
Le même cybercriminel à l'origine de la revendication visant Almerys affirme désormais détenir une base de données attribuée au DMP (Dossier Médical Partagé), un service public numérique de santé permettant de centraliser certaines informations relatives aux assurés français.
Search as Code is the most underrated architecture shift in agentic AI right now.
The old model: agent calls search, gets a result, moves on.
The new model: agent *writes the search pipeline in Python* — parallel queries, deduplication, filtering — before a single token hits context.
The result: 2.5× ahead of the next system on WANDR. 85% fewer tokens on real research tasks.
We've been treating search as a black box for agents. Perplexity just blew the box open.
Introducing the Printing Press, a CLI-factory and a CLI-library. Built with @trevin. 🏭🖨📚
Most APIs suck for agents. Most MCPs suck for agents. Most official CLIs suck for agents. They waste tokens and time. @steipete started making his own because of this.
📚 A Library of agent-native CLIs you install today (Linear, ESPN, Flight GOAT (Google Flights + Kayak nonstop), Contact Goat (LinkedIn + Happenstance + Deepline more) +30+ more)
🏭 A factory that prints new ones for any service - just type /printing-press <product name>
CLIs are fast, local, SQLite-backed. Work in Claude Code, Codex, OpenClaw, Hermes.
🌐 https://t.co/GjnN9E9yTH
@Frontieresmedia C’est quand même anormal que la presence de drapeau etrangé soit normal et par opposition la presence du drapeau Français soit considéré comme hostile. On est chez les fous