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Deep engineering writing on production AI systems, distributed systems, failure modes, and architecture judgment.
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16 essays
Why Google Built a Computer for Every AI Agent
Google gives AI agents isolated computers without keeping every computer running. A detailed engineering review of microVMs, checkpoint recovery, credentials, memory, and scale.
Read essayMCP vs Agent Skills vs A2A: What Each Does in a Real AI Agent
An AI agent finishes a database-migration review, but the dashboard says the migration ran. Understand how Agent Skills, MCP, A2A, and application state fit together.
Read essayHow Coding Agents Actually Work: Inside the Agent Harness
A technical look inside coding agent harnesses, covering context management, repository search, tools, sandboxes, subagents, durable sessions, recovery, concurrency, completion and evaluation.
Read essayOpenAI Decisions API vs Jev: Designing Systems Around Decisions Instead of Generation
A technical comparison of OpenAI Decisions API and Jev, and how to design a decision layer for routing, tool selection, risk, abstention, calibration and AI agent control.
Read essayDesigning Containment for Production AI Agents
Production AI agent containment needs more than a sandbox. It needs separate information, execution and effect boundaries, scoped capabilities, egress controls, quarantine, and independent runtime enforcement.
Read essayDesigning Continuous Evaluation for Production AI Agents
Production AI agent evaluation needs more than task success. It needs behavioral checks, trajectory analysis, outcome verification, failure lineage, repeated trials, statistical release gates, and production failures feeding new evaluation evidence.
Read essayDesigning Production AI Systems with Jev
Jev is useful when an AI system needs fast bounded decisions around generative work. The production design still needs state construction, versioned questions, policy, calibration, observability, and clear boundaries around when to act, escalate, or collect more evidence.
Read essayA Skill Is Not a File. It Is a Deploy: Designing Agent Skills Infrastructure
Production Agent Skills are deployments, not files. They need immutable versions, controlled rollout, revocation, trust boundaries, progressive resolution, and a runtime path designed for scale.
Read essayAn ALLOW Is Not a Permit: Designing Runtime Authorization for AI Agents
Runtime authorization for AI agents needs more than an ALLOW decision. Production systems need exact action identity, bounded permits, reservations, revocation, serialization, and reconciliation with the resulting business effect.
Read essayDesigning Identity and Delegation for Production AI Agents
Production AI agents need explicit human identity, managed agent identity, trusted workload identity, narrow delegation, and an evidence chain that survives every authorization hop.
Read essayStateless MCP Didn't Delete Your State: Designing Production MCP Infrastructure
Stateless MCP removes hidden protocol sessions, not application state. Production infrastructure still needs explicit interaction state, durable Tasks, identity, business effect tracking, routing, admission control, and failover.
Read essayDesigning Observability for Production AI Agents
Production AI agent observability needs more than traces. It needs stable run identity, context manifests, structured telemetry, failure-aware collection, and verified outcomes.
Read essayDesigning the Context Layer for Production AI Agents
Production AI agents need a context layer that assembles evidence, preserves authority and freshness, and separates model reasoning from durable workflow state.
Read essayDesigning Long-Running AI Agents That Survive Failures
Long-running AI agents need durable execution, explicit state, idempotent actions, bounded retries, recovery workflows, and operational control to survive real production failures.
Read essayThe Truth Is Not in the Docs
Production knowledge is not only in documentation. It is spread across code, tickets, incidents, ownership, permissions, dashboards, and the decisions engineers make under pressure.
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