Greetings friends,

AI assistants and agent tools increasingly include web search and page-reading capabilities. For many everyday questions, those built-in tools are entirely sufficient.

More demanding research can involve several different jobs, however: discovering relevant sources, reading a JavaScript-heavy page, mapping or crawling a website, applying the same fields across a list, retrieving specialized data, or producing a cited research synthesis.

Treating all of these as simply “web search” can result in duplicated work, unnecessary complexity, and less clarity about where an answer came from.

I have therefore published a new practical guide:

Choosing External Research Tools for AI Agents

The guide is intended to help readers:

• decide when the search and page-reading tools already available in an AI application are sufficient;

• distinguish retrieval from research or synthesis performed inside an external provider;

• choose tools according to the desired outcome rather than a provider’s name;

• avoid sending the same search or page to several providers without a useful reason;

• verify important claims against opened sources; and

• understand what an AI agent should report about the tools, sources, failures, and evidence gaps involved.

It uses Octen, Exa, Perplexity, Parallel, Firecrawl, and TinyFish as practical examples. It is not a ranking or a suggestion that everyone should connect every provider. The central idea is to use the minimum set of tools that genuinely improves the evidence available for the task.

The guide is fairly detailed, so I have included a “Choose your path” section near the beginning for readers who want to go directly to provider selection, installation, ready-made prompts, or the reusable routing skill.