deep-research

Iterative research uses progressive deepening and evidence grading to build comprehensive, validated knowledge. It guides you through multi-stage search rounds, from broad landscape scans to targeted adversarial checks, ensuring conclusions are stress-tested with disconfirming evidence.

Evidence grading works by evaluating information sources using an A-D reliability scale during information synthesis. This mechanism filters source credibility, ensuring that conclusions are built on progressively validated data before integrating findings into a detailed report.

The best way to investigate a new technology stack is using iterative search combined with deep thinking reasoning loops. This approach performs structured framing and evidence assessment to analyze architecture, trade-offs, and potential pitfalls, producing a validated detailed analysis for your recommendation.

Yes, deep thinking reasoning loops stress-test conclusions with disconfirming evidence. The process mandates structured reasoning pauses between search phases to synthesize information, refine understanding, and adversarially check findings before finalizing validated reports.

You should not use an iterative search process for knowledge acquisition when you need a quick, superficial answer or lack time for multi-stage investigation. This approach requires structured framing, deep thinking pauses, and evidence grading, which are unnecessary for simple, single-query lookups.