Architecture & foundations
The five planes, why prompts alone do not scale, what context engineering means.
The State of AI Agents in 2026: Standards Converged, Models Improved, Production Moved to the Harness
A mid-2026 review of agentic AI: MCP, A2A and AP2 converged as standards and models got more reliable — yet the bottleneck moved to the governed agent harness.
SecondBrain: A Local-First Agent Operating System You Can Run, Inspect, and Trust
SecondBrain is an open-source, local-first agent OS: cognition, memory, governed tools, durable sessions, workflows, and bounded self-improvement in one inspectable runtime you run on your own machine. Here is how it works and how to run it.
Agent Harness: An Architectural Framework for Production AI Agents
A whitepaper on typed contracts, policy gates, traces, verification loops, and release control for production AI agents.
Antahkarana Stack: A Cognitive Layer for Local-First Agents
A builder-facing explanation of Antahkarana as an engineering layer inspired by the inner faculties of Manas, Buddhi, Chitta, and Ahamkara.
The Five Planes of Agentic Operating Systems
A working decomposition for production agent systems: Intelligence, Context, Decision, Action, and Trust.
ContextOS: A Research-Grounded Architecture for Governed Agent Runtimes
A research-grounded framing of ContextOS as a governed runtime for context, tools, memory, security, evaluation, replay, and optimization.
Beyond Prompts: The Architecture of Trust for Agentic AI
Building a governed decision runtime across Intelligence, Context, Decision, Action, and Trust — with evaluator scoring, approval tiers, and replay-bound audit.
Context Engineering in Production
Why most agent failures are not model failures — they are context failures — and what changes when context becomes a versioned, testable, replayable contract.
Context Packs in Practice: From Spec to Run
A practical walkthrough of Context Packs: buckets, policy bundles, evaluation gates, lifecycle, and the compile pipeline.