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4matches
CLI reads Claude Code transcripts to show per-turn context cost—what ships before the first keystroke, unused payload, and skills that never reached the agent—so you can trim defaults instead of guessing.
Datadog’s first investigation-focused model (post-trained on GLM-5.3 Flash with RL in incident simulations) powers Bits AI SRE: medium effort matches GPT-6.1 Sol / Claude Opus 5.5 quality at ~3–8× lower estimated inference cost; closed preview for production alerts.
Show HN: jevcrawl (Apache-2.0 MCP + CLI) crawls for a goal and returns only relevant passages—small Jev model picks links/passages instead of Claude in the loop; README claims ~2× answer-page hit rate vs Crawl4AI and ~10× cheaper per answer than LLM-driven crawl; tools: crawl/scrape/map.
LiteLLM open-sourced Moyai—the Devin-like cloud agent they run in production: Slack/browser tasks get isolated cloud workspaces (terminal+FS+browser), run Codex/Claude Agent SDK/Hermes/OpenCode, open PRs, and attribute spend through your LiteLLM gateway (they estimate ~79% lower vs their Devin bill).