Generation became cheap; acceptance did not. A working definition of AI-native engineering, four mental models for reasoning about it, and what it changes for teams and for individual engineers.
AI coding makes code abundant, but review capacity stays scarce. Here is a practical model for shifting from line-by-line review to risk-based change verification.
A practical look at orchestration patterns for agent systems, grounded in the live harness-engineering demo after adding workflow graph export for its approval-gated runner.
Function calling and MCP make tool interfaces more portable and legible, but they do not replace retries, approvals, state, tracing, or orchestration. A practical look at the live harness-engineering demo after adding an …
A comprehensive white paper on agentic harness engineering: the runtime, tooling, controls, evals, and governance patterns that make AI agents reliable in production.
A practical teardown of the live harness-engineering demo: runner, tool registry, persistent state, CLI surface, provider boundary, and traces—and why those parts matter more than agent theater.
Production-grade agent systems fail less because of clever prompts than because of the runtime around the model: typed tools, explicit workflow state, approvals, retries, traces, and resumable execution.
