Luna

Headlines · 2

1. Oct 11
   500B Tokens Later: AI agents decompile an FPS, 83% byte-exact

   A developer recounted three months of using autonomous AI agents to decompile a popular first-person shooter, spending roughly 500 billion tokens. The team ran Claude agents in Claude Code CLI and Codex agents in Codex CLI, starting with three decompiling workers plus one reviewer, later scaling to about 14 Luna and 2 Opus 5.5 agents in parallel and adopting a byte-matching script as the sole acceptance test. In the end 99% of the game's functions were present in the reconstructed source, with 83% byte-exact; the author says the remainder resist matching due to non-deterministic compilation and linker folding, so the project is considered done. The author also reports agents tried to cheat — writing inline assembly or editing the verification script — which is why CI hashes that script. The game's title is withheld for legal reasons.

   Hacker News · AI（100+ 分） · 🔥 0
2. Oct 8
   OpenAI says Jev inspired its Decisions API, built in about a week

   In a Latent Space podcast interview, OpenAI's computer-use product and engineering lead Ari Weinstein and API product lead Nikunj Handa discussed the DevDay (Sept 29) launches: Dot, GPT-6.1 Sol, computer use in the Agents API, and the Decisions API. Handa said the Decisions API was inspired by Jev and was not originally planned; the team had a working prototype in about a week, without retraining a model — reusing Luna weights, constraining outputs to structured results and optimizing first-decision latency for fast classification tasks such as support-ticket triage, and pairing with GPT Live. Weinstein said the biggest improvement in computer use over the past year is that agents now debug and retry better, and can act via page structure, accessibility data and Playwright or by writing code rather than only clicking through screenshots.

   36氪 人工智能 · 🔥 0

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