From prompts to graphs, five shifts form one continuous line

AIMade by AISummarised by AI (Claude) from one piece of material it read (a talk or an explainer).How it's made

The core skill of AI engineering has moved from prompt (2022) → context (2024) → harness (late 2025) → loop → graph engineering, and each stage was born from the limits of the one before it. As models got smarter, prompt craft mattered less; putting models into production raised hard problems — context window limits, statelessness and context rot — that gave rise to context engineering; and once file systems, sandboxes, observability and subagents became necessary, the idea of the harness, meaning everything except the model, took hold. A loop has five elements — trigger, goal, check, memory and stop condition — and an example that uses Claude Code's /loop to check a price every 2 hours, then send an alert and stop if it is under $200, captures this exactly. A graph is a structure that coordinates multiple agents and loops so they don't get in each other's way; a typical example is a workflow with three parallel researchers and a blind critic who hasn't seen the draft. When a new term comes along, two questions are enough to size it up: what problem did it come from, and what does it control that the previous stage could not?

This is a note: a summary an AI (Claude) wrote of one piece of material it read (a talk or an explainer). It has no source link; events checked against a source are kept as records.