Critique on AIBussin — AI applications, systems and books

Critique, Revision, and Acceptance

Sat, 08 Aug 2026 16:23:00 +0100

Selection can only choose among the candidates it is given. A strong evaluator may recognize that every available candidate is poor, but it cannot select a correct answer that the generator never produced.

That limitation becomes practical because the candidates usually come from one model answering one prompt, and such samples correlate. When four candidates share the same misreading of the evidence, ranking them can still produce a confident winner while leaving the shared defect untouched.

The Thinking Agent

Mon, 01 Jan 0001 00:00:00 +0000

In the last chapter, you built a small agentic workflow in conversation. It had roles, visible state, a tool boundary, and a review loop.

Now we can strengthen the idea that made it useful.

generate
 ↓
critique
 ↓
revise
 ↓
compare
 ↓
accept, reject, or roll back

This is the architecture of a thinking agent: not because the system has private consciousness, and not because a model’s self-critique is automatically reliable, but because the system can externalize an attempt, inspect it, produce a candidate improvement, and decide whether the candidate deserves to replace the current version.

Agents From First Principles 03: AI Agent Keeps Making the Same Mistake? Add a Critique-and-Revision Loop

Sat, 08 Aug 2026 16:23:00 +0100

An AI agent can fail in a particularly frustrating way: it produces an answer that is almost right, you ask it to improve the answer, and it produces another answer with the same underlying defect.

Sometimes the wording changes. Sometimes it adds more explanation. Sometimes it becomes longer and more confident. But the important mistake survives.

That usually means the system is doing this:

prompt
 ↓
model
 ↓
answer

or this: