Deep Analysis and Problem Solving

Analyze problems and questions from multiple angles, generate several solution options with trade-offs, then provide structured recommendations and a clear rationale.

When to Use

• User asks for "ultra-think", "deep analysis", or thorough reasoning
• Architectural or technology decisions (e.g. migrate vs improve, stack choice)
• Complex problem solving (scaling, cost, compatibility, design)
• Strategic or product decisions needing trade-off analysis
• When the problem has many stakeholders, constraints, or unknowns

The Process

1. Parse the problem: Extract the core challenge from the user’s input; identify stakeholders, constraints, implicit requirements, and unknowns; question assumptions.
2. Multi-dimensional analysis: Analyze from technical (feasibility, scale, performance, security, debt), business (value, ROI, time-to-market, risk/reward), user (needs, UX, edge cases, journeys), and system (integration, dependencies, coupling, emergent behavior).
3. Generate 3–5 solutions: For each option: pros/cons, complexity, resources, risks, long-term impact; include conventional and creative or hybrid options.
4. Deep dive: For the most promising options: implementation outline, pitfalls and mitigations, phased/MVP approach, second- and third-order effects, failure modes and recovery.
5. Cross-domain: Draw parallels from other domains; apply patterns from other contexts; consider analogies and combinations.
6. Challenge and refine: Stress-test each option; play devil’s advocate; surface weaknesses, "what if" scenarios, and unintended consequences.
7. Synthesize: Combine insights; identify key decision factors and critical trade-offs; summarize novel insights.
8. Structured output: Present using the output structure below.
9. Meta-analysis: Note uncertainty, biases, limitations, and confidence levels; suggest further expertise or research if needed.

Output Structure

Use this structure for the final response:

## Problem Analysis
- Core challenge
- Key constraints
- Critical success factors

## Solution Options
### Option 1: [Name]
- Description | Pros/Cons | Implementation approach | Risk assessment

### Option 2: [Name]
[Same structure]

[Option 3, 4, 5 as needed]

## Recommendation
- Recommended approach and rationale
- Implementation roadmap
- Success metrics
- Risk mitigation plan

## Alternative Perspectives
- Contrarian view
- Future considerations
- Areas for further research

Key Principles

• First principles: Break down to fundamental truths.
• Systems thinking: Consider interconnections and feedback loops.
• Probabilistic thinking: Work with uncertainties and ranges.
• Inversion: Consider what to avoid, not only what to do.
• Second-order thinking: Consider consequences of consequences.

Output Expectations

• Substantial analysis (typically 2–4 pages of insights when appropriate).
• Multiple viable options with clear trade-offs.
• Clear reasoning and acknowledgment of uncertainty.
• Actionable recommendations and, where useful, novel perspectives.

Reference

• reference.md: Full step-by-step checklist, extended output template, and usage examples. Read when applying the full process or validating structure.