[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-coact-cuts-coding-agent-token-use-by-33-without-losing-accuracy":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},3778,"coact-cuts-coding-agent-token-use-by-33-without-losing-accuracy","CoACT Cuts Coding Agent Token Use by 33% Without Losing Accuracy","A new compression method trims what AI coding agents remember between steps, cutting token costs by a third on standard benchmarks.","AI coding agents are getting more efficient at forgetting things they don't need.\n\nResearchers have released CoACT, a compression method that shrinks the observations LLM-based coding agents accumulate as they work through software tasks. The core idea, which they call next-action preservation (NAP), is that a compressed observation is only valid if it would cause the agent to take the same next step as the full, uncompressed version. During training, a teacher model generates multiple compressed candidates; CoACT then filters them using two rewards — one for action preservation, one for length reduction — and trains a lightweight compressor on the survivors. Tested on SWE-bench Verified across three agentic models, CoACT cut average total token consumption by 33% while keeping task-solving performance close to baseline.\n\nToken costs are one of the less-discussed drags on agentic AI in production. Coding agents work iteratively — each tool call or file read appends more text to the context, and that context gets re-processed on every inference step. A 33% reduction in token use at that layer compounds quickly across long tasks and large deployments. The NAP framing also offers something earlier compression work lacked: a concrete, behavioral signal for whether a compression is actually safe to apply.\n\nWhether the gains hold outside benchmark conditions — on messier, real-world codebases with noisier observations — is the question any team evaluating this should ask first.","[\"ai\",\"dev-tools\",\"coding agents\",\"llm\"]","2026-07-07T04:00:00.000Z","2026-07-07T08:17:12.172Z","2026-07-07T08:17:15.171Z","published",null,[],"ai",[24,26,27,28],"dev-tools","coding agents","llm",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.02911",0,{"sections":35},[36,40,45,50,55,60,65,70,75,78,83,87,92,97],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":76,"slug":26,"count":77,"latest_published_at":18},"Dev Tools",59,{"name":79,"slug":80,"count":81,"latest_published_at":82},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":84,"slug":85,"count":81,"latest_published_at":86},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":88,"slug":89,"count":90,"latest_published_at":91},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":93,"slug":94,"count":95,"latest_published_at":96},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":98,"slug":99,"count":100,"latest_published_at":101},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]