Tools & Frameworks

Operating principles (my defaults)

  • Write to think. A one-page narrative beats a 40-slide deck.
  • Keep the toolkit small. A few repeatable artifacts create alignment faster than “the latest tool”.
  • Make trade-offs explicit. The job is not to avoid conflict; it’s to surface the real decision.
  • Measure outcomes. Shipping features is input; customer value and business impact are the output.

Core artifacts I reuse

  • Problem brief (1 page). Who has the pain, what job they’re trying to do, current workflow, constraints, success metric.
  • Decision memo. Options, pros/cons, risks, who disagrees and why, decision, and what would change my mind.
  • PR/FAQ or narrative. The “future press release” and the hardest FAQs from sales/support/security.
  • Beta charter. Entry criteria, what we’re learning, what we won’t do, timeline, and success thresholds.
  • Launch readiness checklist. Instrumentation, docs, enablement, support plan, rollback.

Strategy frameworks

  • Segmentation + ICP. Which customers get outsized value and why (budget, urgency, compliance, complexity)?
  • Positioning. Category, differentiated capability, and “why now”. (April Dunford’s style is practical.)
  • North Star metric. One metric that best represents delivered value; supporting metrics guard against gaming.
  • Portfolio thinking. How products reinforce each other (bundles, shared platform, shared data, shared workflow).
  • Strategic bets. A small number of explicit bets with hypotheses, investment level, and kill criteria.

Discovery frameworks

  • Jobs-to-be-done. The job, triggers, anxieties, and what “progress” looks like for the customer.
  • Journey mapping. Where the workflow breaks, where context is missing, and what’s manual.
  • Opportunity solution tree. Keeps ideation anchored to opportunities and evidence.
  • Continuous discovery cadence. Weekly touchpoints with users beat occasional “research sprints”.
  • Prototype tests. Cheap tests: concierge, Wizard-of-Oz, Figma flows, fake doors, limited pilot.

Prioritization

I avoid pretending prioritization is math. Frameworks are for clarity, not false precision.

  • RICE. Good for getting alignment on assumptions; I treat confidence as a forcing function.
  • Cost vs impact. The simplest chart often produces the fastest decision.
  • MoSCoW. Useful when scope discipline is the real problem.
  • Sequencing over ranking. “What must be true first?” is often more important than “what’s #1?”.
  • Strategic constraints. Security, compliance, platform readiness, and GTM capacity are real constraints.

Roadmapping & execution

  • Outcome-based roadmaps. Themes and outcomes, not an infinite list of features.
  • Dual-track. Discovery and delivery run in parallel with clear handoffs.
  • Definition of done. Includes instrumentation, docs, support readiness, and learnings captured.
  • Beta strategy. Start with friendly users who feel the pain and can give high-quality feedback.
  • Kill switches. Rollback paths and feature flags for safe iteration.

Metrics & experimentation

  • Metric hierarchy. North Star → input metrics → guardrails.
  • Cohorts. Always ask “for which users did this work?”
  • Experiment design. Start with the smallest test that can change a decision.
  • Qual + quant. A graph tells you what happened; interviews tell you why.

AI-augmenting tools (how I use them)

  • Drafting. First drafts for briefs, FAQs, and release notes — then edited to reflect customer truth.
  • Synthesis. Summaries of calls and tickets to speed up pattern finding (never as the sole source of truth).
  • Exploration. Competitive scans and “what would you ask next?” prompts to expand thinking.
  • Analysis. Help forming hypotheses and checking logic; still validate with data and domain experts.

Mini-templates (copy/paste)

Problem brief

  • User:
  • Job:
  • Current workflow:
  • Pain:
  • Constraints:
  • Success metric:
  • Non-goals:

Decision memo

  • Decision:
  • Options considered:
  • Trade-offs:
  • Risks:
  • What would change my mind: