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Vibe Coding2026-08-14 · source-backed
Launch HN from YC S26 founders (ex-AppLovin and Citadel, after six pivots) pitches a speed-focused harness rather than a model: model routing, targeted code search instead of whole-repo embedding, context management, and turn batching they say cut round trips 16% and costs 27% internally. 479/500 in one attempt, 35–67% faster than mini-SWE-agent, plugs into Claude, Codex and Grok. The top critique in 74 comments asked what a saturated SWE-bench leaderboard means without disclosing model selection. Fair question, and the founders pointed to Terminal-Bench and CursorBench for future validation.
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Launched on Product Hunt at 224 upvotes, positioning explicitly as "30-60% faster than Claude Code and Codex," achieved by auto-selecting model and reasoning level per prompt, parallelizing searches/reads/commands, and using targeted code search instead of embedding the whole...
A team at UC Berkeley RDI built an automated scanning agent that achieved near-perfect scores on eight major AI agent benchmarks. SWE-bench Verified: 100%. Terminal-Bench: 100%. WebArena: approximately 100%. FieldWorkArena: 100%. GAIA: roughly 98%. OSWorld: 73%. The agent didn...
Martin Alderson's essay "The upcoming AI margin collapse, part 1: GLM 5.2" hit 675 points and 462 comments on Hacker News, and it's the rare HN chart-topper that's actually about spreadsheet math instead of vibes. The argument is simple. Z.ai's GLM 5.2 delivers frontier-adjace...
Terminal-Bench 2.1 results (entries dated June 17) put Codex CLI on GPT-5.5 first at 83.4%, Claude Code on Fable 5 second at 83.1%, and Claude Code on Opus 4.8 at 78.9%. The asterisk matters more than the ranking: Fable 5 and Mythos 5 have been export-suspended since June 12,...
Poolside AI released two models that change the math on local coding agents. Laguna M.1 is a 225B total / 23B active MoE model scoring 72.5% on SWE-bench Verified. Laguna XS.2 is a 33B total / 3B active model scoring 68.2% on the same benchmark, 44.5% on SWE-bench Pro, and 30....
An r/LocalLLaMA post at 1,330 upvotes reports the first run of full K3, Moonshot's 2.8T open-weight MoE, on a 16x NVIDIA GB10 cluster with dspark speculative decoding: 20+ tok/s average, 38 peak, 750 prefill. That's roughly $64K of hardware for frontier-adjacent tokens at your...
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