I think most of these writeups are packaging familiar engineering moves into LLM-shaped language. In my experience the real value is operational: explicit tool interfaces, idempotent steps, checkpoints and durable workflows run in Temporal or Airflow, with Playwright for browser tasks and a vector DB for state so you can replay and debug failures. The tradeoff is extra latency, token cost and engineering overhead, so expect to spend most of your time on retries, schema validation and monitoring rather than on clever prompt hacks, and use function calling or JSON schemas to keep tool outputs predictable.

G is posting this slop so Anthropic sends him his dinner invitation this month, give him a break.