[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-skillfm-skips-retrieval-generates-agent-skills-on-the-fly":10,"sections":35},{"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":30,"feedback":34,"feedback_at":22,"cost_usd":34,"total_tokens":34},8939,"skillfm-skips-retrieval-generates-agent-skills-on-the-fly","SkillFM Skips Retrieval, Generates Agent Skills On the Fly","A new research framework generates task-specific instructions for AI agents in one step instead of pulling them from a pre-built library.","Researchers have built a system that writes instructions for AI agents on demand, instead of fetching them from a pre-made list.\n\nThe framework, called SkillFM, targets a specific bottleneck in how AI agents work. Most agents rely on \"skills\" - short pieces of text that tell them how to handle a task - pulled from banks that humans curate by hand or refined through reinforcement learning, which reacts slowly and indirectly to feedback. SkillFM instead compresses skills into a continuous latent space, then uses a conditional flow model to generate a new skill representation in a single inference step. An LLM decoder turns that representation into text, which gets handed to an unmodified downstream agent. The researchers tested it on embodied-task simulator ALFWorld, a search-based QA benchmark, and a web shopping task, and report it beat comparable vector-based skill methods on the first two.\n\nThis matters because skill retrieval has become a quiet tax on agent systems: every task lookup costs latency, and every curated skill bank needs maintenance as tasks drift. If generation can match or beat retrieval without a search step, that's one less moving part in agent pipelines that are already stacked with vector databases, rerankers, and prompt templates. It's also notable that the comparison here is specifically against other vector-based skill approaches, not every agent-memory technique out there.\n\nThe code and training libraries are open-source on GitHub, which is the real test - wrapper papers for agent memory are common, and most quietly vanish once a benchmark cycle passes. ALFWorld and one QA benchmark is a narrow proving ground; whether this holds up on messier, real-world agent tasks is still an open question.","[\"ai-agents\",\"llm\",\"machine-learning-research\",\"agent-memory\"]","2026-10-01T04:00:00.000Z","2026-10-01T11:49:07.580Z","2026-10-01T11:49:18.983Z","published",null,[],"ai",[26,27,28,29],"ai-agents","llm","machine-learning-research","agent-memory",[31],{"name":32,"url":33},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.39382",0,{"sections":36},[37,40,44,49,54,59,64,69,74,78,83,88,93,98],{"name":38,"slug":24,"count":39,"latest_published_at":18},"AI",5357,{"name":41,"slug":42,"count":43,"latest_published_at":18},"Security","security",802,{"name":45,"slug":46,"count":47,"latest_published_at":48},"Policy","policy",429,"2026-10-01T02:26:17.000Z",{"name":50,"slug":51,"count":52,"latest_published_at":53},"Deals","deals",298,"2026-09-30T21:00:26.000Z",{"name":55,"slug":56,"count":57,"latest_published_at":58},"Hardware","hardware",196,"2026-09-30T13:00:00.000Z",{"name":60,"slug":61,"count":62,"latest_published_at":63},"Science","science",157,"2026-09-30T15:00:56.000Z",{"name":65,"slug":66,"count":67,"latest_published_at":68},"Consumer Tech","consumer-tech",149,"2026-09-30T22:57:11.000Z",{"name":70,"slug":71,"count":72,"latest_published_at":73},"Dev Tools","dev-tools",93,"2026-10-01T02:30:48.000Z",{"name":75,"slug":76,"count":72,"latest_published_at":77},"Software","software","2026-09-30T21:41:11.000Z",{"name":79,"slug":80,"count":81,"latest_published_at":82},"Startups","startups",84,"2026-09-30T20:39:09.000Z",{"name":84,"slug":85,"count":86,"latest_published_at":87},"Gaming","gaming",51,"2026-09-30T16:24:30.000Z",{"name":89,"slug":90,"count":91,"latest_published_at":92},"General","general",50,"2026-09-30T21:37:54.000Z",{"name":94,"slug":95,"count":96,"latest_published_at":97},"Reviews","reviews",31,"2026-09-28T14:31:34.000Z",{"name":99,"slug":100,"count":101,"latest_published_at":102},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]