ultra-think

# Ultra Think — Deep Analysis Mode Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation. **Use when**: facing architectural decisions, complex trade-offs, strategic technology choices, system design problems, scaling challenges, migration decisions, or any question that deserves more than a quick answer. Attach this skill when you want rigorous, first-principles thinking. --- ## When This Skill Is Activated Do NOT jump to a solution. Follow every step below in order. Think deeply at each stage before moving on. --- ## Step 1: Parse the Problem Before analyzing, make sure you understand what's actually being asked. - Extract the core challenge from the user's message - Identify all stakeholders and constraints (stated and implied) - Surface hidden complexities and implicit requirements - Question assumptions — what is the user taking for granted? - Name the unknowns explicitly --- ## Step 2: Multi-Dimensional Analysis Analyze the problem from four perspectives. Do not skip any. ### Technical Perspective - Feasibility and constraints - Scalability, performance, maintainability - Security implications - Technical debt and future-proofing - Integration complexity ### Business Perspective - Business value and ROI - Time-to-market pressure - Competitive advantage - Risk vs. reward trade-offs - Cost (development, operational, opportunity) ### User Perspective - User needs and pain points - Usability and accessibility - Edge cases and failure states from the user's point of view - User journeys affected ### System Perspective - System-wide impacts and ripple effects - Integration points and coupling - Dependencies (upstream and downstream) - Emergent behaviors and unintended interactions --- ## Step 3: Generate Multiple Solutions Brainstorm **at least 3 distinct approaches** — not variations of the same idea. For each approach, evaluate: - Pros and cons - Implementation complexity (T-shirt size: S/M/L/XL) - Resource requirements (people, time, money) - Key risks - Long-term implications (what does this look like in 2 years?) Include at least one unconventional or creative solution. Consider hybrid approaches that combine strengths of different options. --- ## Step 4: Deep Dive on Top Candidates For the 1–2 most promising solutions: - Sketch a detailed implementation plan (phases, milestones) - Identify pitfalls and mitigation strategies - Consider a phased approach or MVP path - Analyze **second-order effects** — what changes because of this change? - Think through failure modes — what happens when this breaks? - Estimate reversibility — how hard is it to undo if wrong? --- ## Step 5: Cross-Domain Thinking Look beyond the immediate domain for insight: - Are there parallels from other industries? (e.g., how did logistics solve this? Healthcare? Finance?) - Do design patterns from other contexts apply? (e.g., circuit breakers from electrical engineering → software resilience) - Are there natural system analogies? (e.g., biological redundancy, evolutionary pressure) - Can existing solutions be combined in a novel way? --- ## Step 6: Challenge and Stress-Test Play devil's advocate against every solution, including the one you favor. - What's the strongest argument against each option? - What blind spots might you have? - Run "what if" scenarios (what if traffic is 10x? what if the team halves? what if requirements change?) - Stress-test assumptions — which ones, if wrong, would invalidate the whole approach? - Look for unintended consequences --- ## Step 7: Synthesize and Recommend Combine all insights into a structured deliverable. Use this exact format: ``` ## Problem Analysis - **Core challenge**: [one sentence] - **Key constraints**: [list] - **Critical success factors**: [what must be true for any solution to work] - **Assumptions**: [what we're taking as given] ## Solution Options ### Option 1: [Name] - **Description**: [2-3 sentences] - **Pros**: [list] - **Cons**: [list] - **Complexity**: [S/M/L/XL] - **Risk level**: [Low/Medium/High] - **Best when**: [conditions that make this the right choice] ### Option 2: [Name] [Same structure] ### Option 3: [Name] [Same structure] ## Recommendation - **Recommended approach**: [which option and why] - **Rationale**: [the decisive factors] - **Implementation roadmap**: [phases with rough timelines] - **Success metrics**: [how we'll know it's working] - **Risk mitigation**: [top 3 risks and their mitigations] - **Reversibility**: [how hard to undo if wrong] ## Contrarian View - **The case against this recommendation**: [strongest counterargument] - **What would change our mind**: [signals that we chose wrong] - **Areas of uncertainty**: [what we don't know yet] ## Confidence Assessment - **Overall confidence**: [High/Medium/Low] — [why] - **What would increase confidence**: [additional research, prototyping, data needed] ``` --- ## Step 8: Meta-Reflection End with a brief reflection: - Where is the analysis weakest? - What biases might be influencing the recommendation? - What additional expertise or data would improve the analysis? - What's the one thing most likely to be wrong? --- ## Thinking Principles Apply these mental models throughout the analysis: | Principle | Application | |-----------|-------------| | **First Principles** | Break down to fundamental truths, don't reason by analogy alone | | **Systems Thinking** | Consider interconnections, feedback loops, emergent behavior | | **Probabilistic Thinking** | Work with ranges and likelihoods, not certainties | | **Inversion** | Ask "what should we avoid?" not just "what should we do?" | | **Second-Order Effects** | Consider the consequences of consequences | | **Reversibility** | Prefer reversible decisions; be extra careful with irreversible ones | | **Occam's Razor** | Among equally valid solutions, prefer the simpler one | --- ## Output Expectations - Comprehensive analysis (typically 2–4 pages of insight) - Multiple viable solutions with honest trade-offs - Clear reasoning chains — show your work - Explicit acknowledgment of uncertainties - Actionable recommendation with next steps - At least one novel insight or non-obvious perspective