deep-research

To ensure authoritative research before coding, you need a structured workflow that scopes knowledge gaps, searches Tier 1 sources, performs deep reads, and delivers a synthesis with implementation plans before writing any code.

The best way to perform a literature review for complex domains is a five-phase process: scoping the topic, searching a source hierarchy, deep reading, synthesizing alternatives, and gating execution until research is approved.

You need a knowledge synthesis workflow for statistical methods when you face unfamiliar concepts or algorithms that require expert-level understanding and evidence-based trade-off evaluation prior to implementation.

To evaluate sources and compare alternatives, execute a deep read of Tier 1 authoritative sources, then synthesize the findings by mapping explicit trade-offs and generating a recommended plan with rationale.

Yes, a structured research workflow prevents code-only approaches by enforcing execution gating and approvals, ensuring you cannot proceed to implementation when knowledge is insufficient.

Yes, this research-first approach works for unfamiliar concepts and algorithms by identifying knowledge gaps, sourcing authoritative evidence, and delivering expert synthesis to guide implementation.