Blog
Essays and release notes from Doug Fir Labs on neuro-symbolic AI, reasoning protocols, and the infrastructure that lets agents reason verifiably.
Scholialang helps agentic systems preserve reasoning state, use tools without quality loss, and reduce context cost across long-horizon work — a durable protocol for claims, evidence, decisions, contradictions, and verification across agents.
Large language models are powerful pattern matchers, but pattern matching alone doesn't constitute reasoning. We explore how composing symbolic reasoning primitives with neural inference creates models that are more capable, auditable, and trustworthy.