Agents From First Principles 08: AI Agent Picks the First Solution? Add Search Instead of One-Shot Generation

Sat, 08 Aug 2026 17:26:00 +0100

An AI agent often fails for a surprisingly ordinary reason:

it commits too early.

It finds one plausible next action, follows it, and then spends the rest of the run trying to make that first choice work.

That can look intelligent because the agent keeps reasoning, calling tools, revising plans, and explaining itself.

But underneath, the trajectory may be almost completely determined by an early mistake.

A coding agent chooses the wrong implementation strategy and spends twenty tool calls repairing it.

Agents From First Principles 02: AI Agent Gives Inconsistent Answers? Generate Multiple Candidates and Rank Them

Sat, 08 Aug 2026 15:54:00 +0100

One of the first things you notice when you build anything around a large language model is that the same prompt does not always produce the same quality of answer.

Sometimes the first response is excellent.

Sometimes it is merely acceptable.

Sometimes it misses the point entirely.

That creates a very common agent-engineering question:

If the model is inconsistent, should the agent trust the first answer it gets?

Often, no.

Best-of-N on Programmer.ie: Modern AI programming

Agents From First Principles 08: AI Agent Picks the First Solution? Add Search Instead of One-Shot Generation

Agents From First Principles 02: AI Agent Gives Inconsistent Answers? Generate Multiple Candidates and Rank Them