Best Perplexity primary source: Perplexity Agent API models. Official Perplexity model table for grounded search and agent workflows. Start here when you need the current Perplexity search and research stack rather than a marketing summary.
Best Google deep-research source: Gemini Deep Research Agent. Official Google AI for Developers guide to long-running research agents. Use it to understand cited reports, background execution, and research-agent behavior.
Best retrieval foundation: OpenAI Retrieval guide. Official OpenAI guide to retrieval and grounded answers. Use it to understand grounding patterns that apply beyond one search provider.
Deep research depends on source discipline
AI search is useful only when it makes sources inspectable. A good research workflow separates the question, source discovery, extracted claims, synthesis, citations, and uncertainty.
Perplexity, Gemini, and OpenAI docs are the right starting points because search and research products change quickly. Check current Agent API model tables, deep-research docs, and retrieval guidance before trusting a course or newsletter summary.
Test with questions you can verify
Before trusting a deep research workflow, run it on topics where you know the answer or can check the sources. Look for unsupported claims, stale evidence, citation mismatch, and missing counterarguments.
A useful resource should teach verification habits, not just polished reports. The report is the output; the source trail is the product.
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