AI Engineering
10 essays tagged with AI Engineering.
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.
AI Agent Memory Is Broken: Designing Multi-Layer Memory for Production AI Agents
A production guide to AI agent memory architecture: designing long-term memory for AI agents across working, episodic, semantic, procedural, and organizational layers. Why RAG is not memory, why vector databases are not memory, and how governed, situation-aware memory prevents memory poisoning in enterprise AI agents.
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.
Dataset-First Agent Engineering: The Golden Sets Behind Reliable Agents
A practical guide to golden sets, task distributions, corrected runs, held-out releases, and production slices for agent engineering.
How Great AI Engineers Build Agents: Datasets, Scores, and Harnesses That Improve
Why strong AI engineers build datasets, scorecards, traces, and improvement loops instead of treating agents as prompts plus tools.
Harness Candidates Are Model Checkpoints: How to Improve Agents Without Silent Mutation
How to treat every prompt, retrieval, tool, policy, and evaluator change as a scored, reviewed, reversible harness candidate.
Scorecards Over Vibes: The Five Metrics That Keep Agents Honest
The five metrics that keep agents honest: policy, utility, latency, safety, and economics.
Trace Review Is the Agent Debugger: Grade the Path, Not Just the Answer
How trace review grades the path, not just the answer, by inspecting context, plans, tools, guardrails, critic verdicts, and corrections.