Governance
30 essays tagged with Governance.
Proof-Carrying Context: Why AI Agents Need More Than a Context Window
A research-grounded revision of context engineering: from relevant tokens to a replayable view of evidence, conflicts, omissions, and decision sufficiency.
Persistent Memory Poisoning: The Attack That Outlives the Session
A production security architecture for attributable, revalidated, authority-bounded, traceable, and selectively reversible agent memory.
Multi-Agent Consensus Is Not Correctness: How Debate Manufactures Confidence
Why agent agreement can hide correlated error—and how to build governed deliberation with effective agent count, independent verification, and release gates.
The Glass Runtime: Keeping Humans Close to the Material in an Agentic World
As AI makes output abundant, the central design challenge shifts to preserving human judgment, understanding, intervention, and agency. The Glass Runtime is an architecture for progressive autonomy, inspectable decisions, material-native interaction, reversibility, governed authority, and accountable learning.
OpenWorker Review: A Real Desktop Coworker With an Unfinished Trust Runtime
OpenWorker already owns the agent loop, approvals, connectors, and desktop UX. Its next leap is containment, durable effects, replay, budgets, and evals.
OpenAI's Frontier Stack: Long-Horizon Safety, Stargate, and Custom Silicon
Why OpenAI is scaling trajectory-level safeguards, cyber containment, data centers, and custom inference hardware alongside frontier models.
Agent Memory Should Be Compiled at Recall, Not Replayed From Storage
What MemHarness teaches us about reconstruction, negative transfer, source state, and compiling production agent memory against current evidence, policy, and authority.
Human Oversight for Agent Fleets: Confidence Is Not an Audit Policy
A new audit-allocation paper shows that self-reported confidence can make limited human review worse than random and that tiny audit budgets can become rubber-stamping. Production oversight needs risk gates, stratified random coverage, correlation-aware learning, and a measured non-vacuity test.
What Production Agent Runtimes Actually Teach ContextOS: Twelve Laws of a Governed Harness
The strongest production agent runtimes converge on twelve architectural laws: compile context, persist state, separate authority from containment, make side effects resumable, treat approvals as typed interrupts, and promote learning only through evidence and replay.
Adaptive Agent Harnesses: Learn From Experience Without Letting Production Rewrite Itself
MemoHarness shows that execution experience can improve the control layer around an LLM. Production systems need a stricter pattern: adaptive performance inside an immutable safety envelope.
Agent Memory Is a Systems Workload: What SelfMem Changes—and What It Does Not
SelfMem improves long-horizon recall by letting an agent optimize its memory strategy. New systems and security research shows the production contract must also cover cost, freshness, provenance, and poisoning.
Threat-Model an AI Agent: Sources, Sinks, Authority, and Blast Radius
A practical AI agent threat-modeling method that maps untrusted sources to dangerous sinks, then constrains identity, authority, data, and blast radius at deterministic runtime boundaries.
The AI Software Delivery Squad: From Ticket to Proof-Carrying Pull Request
A production blueprint for coding agents that scope, patch, test, review, and open pull requests without inheriting merge or deploy authority.
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.
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.
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.
Agent Identity Is the New Trust Boundary
A practical model for separating agent identity, workload proof, user delegation, scoped authority, and audit across MCP and A2A.
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.
Financial Crime Operations: Agentic AI Needs Evidence, Not Autonomy
How KYC, AML, sanctions, and fraud casework can use agentic workflows while preserving evidence, policy gates, and human adjudication.
The Identity Layer: Agents Need Two Identities, Not One
Why governed agent runs need entity identity, delegated user identity, and workload identity in the same RunContext.
Trusting AI at Work: Approvals, Boundaries, and Receipts
A plain-English guide to agent trust: what AI can read, draft, send, change, approve, and how receipts make decisions accountable.
AI Agents for Business Leaders: Build the Airport, Not Just the Plane
A practical executive playbook for agentic AI: define the work, evidence, authority, scorecards, approvals, security, observability, and improvement loop.
Trust Is a Product Surface: Approval Modes and Human Control for Agentic Products
How PMs should design trust for real agentic products: approval modes, human roles, evidence snapshots, DecisionRecords, policy gates, and graceful failure.
From PRD to Intent Catalog: The PM Spec for Agentic Products
How PMs turn vague agent ideas into intent catalogs, task templates, authority models, DecisionRecords, and launch criteria.
Agentic AI Systems Before and After ContextOS
A table-first guide to why agentic systems need bounded context, governed tools, typed decisions, replay, evaluation, and controlled improvement.
Approval Gates in Code: The Destructive-Mode Handshake
A build-along for approval gates: frozen evidence, human signatures, gateway redemption, and replayable destructive-action handshakes.
The Five Planes of Agentic Operating Systems
A working decomposition for production agent systems: Intelligence, Context, Decision, Action, and Trust.
Context Packs in Practice: From Spec to Run
A practical walkthrough of Context Packs: buckets, policy bundles, evaluation gates, lifecycle, and the compile pipeline.
Approval-Mode Tiers: A Risk Taxonomy You Can Actually Ship
Why ad-hoc approval gates rot in production, and how five canonical risk tiers turn governance from a meeting into a contract.
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.