What is mattwood.fyi?

A live, structured feed of riffs and links from Matt Wood, Chief AI & Technology Officer at AWS — readable by people and queryable by agents as a typed knowledge graph.

Is there an API and is it free?

Yes. A public, read-only query API is available with no authentication and no API keys. See https://mattwood.fyi/openapi.json and https://mattwood.fyi/docs.

How should an AI agent use this site?

Fetch https://mattwood.fyi/feed.json for the full structured feed, or query the API for keyword/semantic search and the connection graph. See https://mattwood.fyi/agents/ for when-to-use guidance.

SIA: Self Improving AI Framework

Connections

Related to

#aiagents #skillos #selfevolvingai #skills #hermesagent | Melanie (Peiyao) Li Both describe self-evolving skill ecosystems where agents continuously improve their own capabilities.

DeepSeek Harness: Plugin Architecture Both are framework-level architectures enabling AI capability extension — SIA's self-improvement framework and the DeepSeek plugin harness both treat extensibility as a core design principle rather than an afterthought.
The Economics of Recursive Self-Improvement SIA (Self Improving AI Framework) is a direct practical instantiation of the recursive self-improvement dynamics the paper attempts to model economically - the paper provides theoretical context for evaluating such systems
Every Model Cheats: Prompt-Level Mitigation of Cheating on Offensive Cyber Tasks Self-improving AI frameworks that use benchmark performance as improvement signals are particularly vulnerable to the cheating dynamics the new paper documents, as optimization pressure amplifies cheating incentives
Emergent Introspective Awareness in Large Language Models A self-improving AI framework depends on models having accurate self-assessment; findings about whether LLMs can genuinely introspect on internal states directly bears on whether self-improvement loops relying on self-reporting are grounded or illusory.
Discovery Loop Both focus on self-improving AI loops — the Self Improving AI Framework automates iterative improvement cycles algorithmically, while Discovery Loop automates the experimental iteration cycle in physical/scientific domains
Ornith-1.5: Self-Scaffolding to Self-Improvement Both are self-improvement AI frameworks; FF88FEE8 is a self-improving AI framework while Ornith-1.5 specifically focuses on end-to-end self-scaffolding to generate tasks and rollouts for RL

Challenged by

Micro-Agent: Beat Frontier Models with Collaboration inside Model API Micro-Agent argues collaboration among smaller models inside one API call beats a single 'frontier checkpoint,' contrasting with SIA's iterative self-improvement loop approach.

Develops into

Building a skill optimization loop The single-skill improvement loop generalizes into SIA's multi-agent coordinated self-improvement framework.

Type:	link
First published:	Thursday, 11 June 2026 at 12:00 UTC
Location:	https://github.com/hexo-ai/sia
URL:	https://mattwood.fyi/i/ff88fee8

I'm Matt Wood, and this is For Your Information. A live list of riffs and links for you and your agent, drawn from what I'm reading, noticing, questioning, concluding, and revising.

Connections