scientific-problem-selection

Scientific Problem Selection Skills A conversational framework for systematic scientific problem selection based on Fischbach & Walsh's "Problem choice and decision trees in science and engineering" (Cell, 2024). Getting Started Present users with three entry points: 1) Pitch an idea for a new project — to work it up together 2) Share a problem in a current project — to troubleshoot together 3) Ask a strategic question — to navigate the decision tree together This conversational entry meets scientists where they are and establishes a collaborative tone. Option 1: Pitch an Idea Initial Prompt Ask: "Tell me the short version of your idea (1-2 sentences)." Response Approach After the user shares their idea, return a quick summary (no more than one paragraph) demonstrating understanding. Note the general area of research and rephrase the idea in a way that highlights its kernel—showing alignment and readiness to dive into details. Follow-up Prompt Then ask for more detail: "Now give me a bit more detail. You might include, however briefly or even say where you are unsure: What exactly you want to do How you currently plan to do it If it works, why will it be a big deal What you think are the major risks" Workflow From there, guide the user through the early stages of problem selection and evaluation: Skill 1: Intuition Pumps - Refine and strengthen the idea Skill 2: Risk Assessment - Identify and manage project risks Skill 3: Optimization Function - Define success metrics Skill 4: Parameter Strategy - Determine what to fix vs. keep flexible See references/01-intuition-pumps.md , references/02-risk-assessment.md , references/03-optimization-function.md , and references/04-parameter-strategy.md for detailed guidance. Option 2: Troubleshoot a Problem Initial Prompt Ask: "Tell me a short version of your problem (1-2 sentences or whatever is easy)." Response Approach After the user shares their problem, return a quick summary (no more than one paragraph) demonstrating understanding. Note the context of the project where the problem occurred and rephrase the problem—highlighting its core essence—so the user knows the situation is understood. Also raise additional questions that seem important to discuss. Follow-up Prompt Then ask: "Now give me a bit more detail. You might include, however briefly: The overall goal of your project (if we have not talked about it before) What exactly went wrong Your current ideas for fixing it" Workflow From there, guide the user through troubleshooting and decision tree navigation: Skill 5: Decision Tree Navigation - Plan decision points and navigate between execution and strategic thinking Skill 4: Parameter Strategy - Fix one parameter at a time, let others float Skill 6: Adversity Response - Frame problems as opportunities for growth Skill 7: Problem Inversion - Strategies for navigating around obstacles Always include workarounds that might be useful whether or not the problem can be fixed easily. See references/05-decision-tree.md , references/06-adversity-planning.md , references/07-problem-inversion.md , and references/04-parameter-strategy.md for detailed guidance. Option 3: Ask a Strategic Question Initial Prompt Ask: "Tell me the short version of your question (1-2 sentences)." Response Approach After the user shares their question, return a quick summary (no more than one paragraph) demonstrating understanding. Note the broader context and rephrase the question—highlighting its crux—to confirm alignment with their thinking. Follow-up Prompt Then ask: "Now give me a bit more detail. You might include, however briefly: The setting (i.e., is this about a current or future project) A bit more detail about what you're thinking" Workflow From there, draw on the specific modules from the problem choice framework most appropriate to the question: Skills 1-4 for future project planning (ideation, risk, optimization, parameters) Skills 5-7 for current project navigation (decision trees, adversity, inversion) Skill 8 for communication and synthesis Skill 9 for comprehensive workflow orchestration See the complete reference materials in the references/ folder. Core Framework Concepts The Central Insight Problem Choice >> Execution Quality Even brilliant execution of a mediocre problem yields incremental impact. Good execution of an important problem yields substantial impact. The Time Paradox Scientists typically spend: Days choosing a problem Years solving it This imbalance limits impact. These skills help invest more time choosing wisely. Evaluation Axes For Evaluating Ideas: X-axis: Likelihood of success Y-axis: Impact if successful Skills help move ideas rightward (more feasible) and upward (more impactful). The Risk Paradox Don't avoid risk—befriend it No risk = incremental work But: Multiple miracles = avoid or refine Balance: Understood, quantified, manageable risk The Parameter Paradox Too many fixed = brittleness Too few fixed = paralysis Sweet spot: Fix ONE meaningful constraint The Adversity Principle Crises are inevitable (don't be surprised) Crises are opportune (don't waste them) Strategy: Fix problem AND upgrade project simultaneously The 9 Skills Overview Skill Purpose Output Time 1. Intuition Pumps Generate high-quality research ideas Problem Ideation Document ~1 week 2. Risk Assessment Identify and manage project risks Risk Assessment Matrix 3-5 days 3. Optimization Function Define success metrics Impact Assessment Document 2-3 days 4. Parameter Strategy Decide what to fix vs. keep flexible Parameter Strategy Document 2-3 days 5. Decision Tree Navigation Plan decision points and altitude dance Decision Tree Map 2 days 6. Adversity Response Prepare for crises as opportunities Adversity Playbook 2 days 7. Problem Inversion Navigate around obstacles Problem Inversion Analysis 1 day 8. Integration & Synthesis Synthesize into coherent plan Project Communication Package 3-5 days 9. Meta-Framework Orchestrate complete workflow Complete Project Package 1-6 weeks Skill Workflow SKILL 1: Intuition Pumps | (generates idea) v SKILL 2: Risk Assessment | (evaluates feasibility) v SKILL 3: Optimization Function | (defines success metrics) v SKILL 4: Parameter Strategy | (determines flexibility) v SKILL 5: Decision Tree | (plans execution and evaluation) v SKILL 6: Adversity Planning | (prepares for failure modes) v SKILL 7: Problem Inversion | (provides pivot strategies) v SKILL 8: Integration & Communication | (synthesizes into coherent plan) v SKILL 9: Meta-Skill (orchestrates complete workflow) Key Design Principles Conversational Entry - Meet users where they are with three clear starting points Thoughtful Interaction - Ask clarifying questions; low confidence prompts additional input Literature Integration - Use PubMed searches at strategic points for validation Concrete Outputs - Every skill produces tangible 1-2 page documents Building Specificity - Progressive detail emerges through targeted questions Flexibility - Skills work independently, sequentially, or iteratively Scientific Rigor - Claims about generality and feasibility should be evidence-based Who Should Use These Skills Graduate Students (Primary Audience) When: Choosing thesis projects, qualifying exams, committee meetings Focus: Skills 1-3 (ideation, risk, impact) + Skill 9 (complete workflow) Timeline: 2-4 weeks for comprehensive planning Postdocs When: Starting new position, planning independent projects, fellowship applications Focus: All skills, emphasizing independence and risk management Timeline: 1-2 weeks intensive planning Principal Investigators When: New lab, new direction, mentoring trainees, grant cycles Focus: Skills 1, 3, 4, 6 (ideation, impact, parameters, adversity) Timeline: Ongoing, integrate into lab culture Startup Founders When: Company inception, pivot decisions, investor pitches Focus: Skills 1-4 (ideation through parameters) + Skill 8 (communication) Timeline: 1-2 weeks for initial planning, revisit quarterly Reference Materials Detailed skill documentation is available in the references/ folder: File Content Search Patterns 01-intuition-pumps.md Generate research ideas Intuition Pump # , Trap # , Phase [0-9] 02-risk-assessment.md Risk identification Risk.1-5 , go/no-go , assumption 03-optimization-function.md Success metrics Generality.Learning , optimization , impact 04-parameter-strategy.md Parameter fixation fixed.*float , constraint , parameter 05-decision-tree.md Decision tree navigation altitude , Level [0-9] , decision 06-adversity-planning.md Adversity response adversity , crisis , ensemble 07-problem-inversion.md Problem inversion strategies Strategy [0-9] , inversion , goal 08-integration-synthesis.md Integration and synthesis narrative , communication , story 09-meta-framework.md Complete workflow Phase , workflow , orchestrat Expected Outcomes Immediate (After Completing Workflow) Clear project vision Honest risk assessment Contingency plans Communication materials ready Confidence in problem choice 6-Month Faster decisions (have framework) Productive adversity handling No existential crises (risks mitigated) 2-Year Published results or strong progress Avoided dead-end projects Career aligned with goals Time well-spent (ultimate measure) Foundational Reference Fischbach, M.A., & Walsh, C.T. (2024). "Problem choice and decision trees in science and engineering." Cell , 187, 1828-1833. Based on course BIOE 395 taught at Stanford University.