Microsoft proposes training agent skills like neural networks, with validation gates and no weight updates
Saboo_Shubham_ · x · 2026-07-21
Microsoft lays out a strategy for self-evolving agent skills: treat skills like neural-network training, with epochs, minibatch size, learning rates, and validation gates, while keeping model weights frozen.
The attached SkillOpt paper/site says the system optimizes a skill document rather than model weights, using scored rollouts and bounded edits. A candidate edit is accepted only if it improves held-out validation, with learning-rate budgeting and slow meta-updates to keep training stable. The resulting bestskill.md reportedly transfers across models and harnesses, and improves benchmark accuracy without adding inference-time calls.
Related event: Microsoft Open-Sources SkillOpt for Self-Evolving Agent Skills(2 posts)→
More from coding & agent
- shadcn's /improve skill paired with Grok on SuperGrok Heavy for plowing through issues — shadcn · 2026-10-27
- Paradigm Launches Envoys: Your Claude Code and Codex on Your Research Graph, Free — tensorqt · 2026-10-27
- AXL launches remote MCP server exposing 1,284 sales and marketing APIs to Claude and Codex — EdTech_Padre · 2026-10-27
- GitHub's Thomas Dohmke ships Entire, a Git forge built for agent-human collaboration — carrycooldude · 2026-10-27
- OmarchyTV hits GitHub: Omarchy-style TV launcher with AI TUI and MCP — alexcovo_eth · 2026-10-27
- AWS on agent prompt caching: explicit + implicit patterns to slash token costs — AWS ML Blog · 2026-10-27