Lean Zig by building an LLM from scratch
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Hi HN, I'm Daniel, part of the team at Agnes AI, a Singapore-based AI lab. We've been building quietly for a while and I wanted to share what we've made with this community and get honest feedback from people who actually build things. What is Agnes AI? Agnes AI gives you access to three models through a single free API. We have text, image and video models. The API is fully OpenAI-compatible, so you can just swap the base URL to https://apihub.agnes-ai.com/v1 and use your Agnes API key. No othe
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Hi HN, Here's a little website for a hobby project I have, and maybe the AI use disclaimer on it is useful to others. I believe it's a fundamental duty of open source maintainers to disclose the extent of their AI use on a per-project basis. The usual discussions here devolve into "this is vibe coded" for tools which may or may not be, and it's not great. I greatly dislike vibe-coding, but I believe in responsible tool use, such as responsible use of AI. The linked page is CC0, feel free to copy
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OpenAI and Broadcom introduce Jalapeño, a custom AI chip built for LLM inference to improve performance, efficiency, and scale across AI systems.
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When AI generates code, I first instruct the model to find, fix, and verify any issues. After that, I start the server and test whether it actually works from the user’s perspective. What I’m looking for is a workflow where issues are received, fixed, tested, and deployed—but it seems that current AI agents aren’t very good at performing browser tests from the user’s perspective. I’ve tried using the built-in browsers in Codex and Cursor, but they often only checked whether the page loaded. In t
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