Congratulations to my dear friend @ep_qc on her new book, "Made to Deliver," which you can get here!👇🏽amazon.com/dp/B09LB1QFLJ/ref…

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]

Your vibe design partner just got more collaborative! To celebrate I/O, here are 5 major upgrades (and one big bonus!): 🌊 Streaming 📄 Start with your existing design ⏩ In-place AI Edits 🎥 Motion on HTML-native Canvas 🚀 More Import / Export Options (.fig, Netlify, Loveable, Bolt) 🌟 BONUS: Import and sync your codebase Rolling out now. Details and product walkthrough video in 🧵

"Dude there's no way you could ever win unless every single person in front of you crashed"

The best code changes happen automatically. Jules now proactively finds performance optimizations in your codebase. Turn on Suggested Tasks and let Jules find inefficient loops, redundant computations, N+1 database calls, and more.

Last week we shipped a ton • Suggested Tasks • Scheduled Tasks • Debug deployments with @render Here's everything recapped in 217 seconds

Introducing Repoless in Jules • Run sessions without a GitHub repo • Upload your own context: code, files, photos... • Download everything when it's done Perfect for prototypes, custom tools, quick scripts, or anything you want to build in an AI powered sandbox.

Try out Jules with Gemini 3. Let us know what you think! We've made a lot of other improvements, too, so it should feel slick!