roadmap-backcast
$
npx mdskill add lyndonkl/claude/roadmap-backcastTransforms fixed deadlines into actionable milestone sequences.
- Converts aspirational targets into sequenced plans with dependencies.
- Identifies critical path constraints and feasibility limits.
- Executes iterative milestone identification from end to start.
- Delivers structured checklists and feasibility assessments.
SKILL.md
.github/skills/roadmap-backcastView on GitHub ↗
--- name: roadmap-backcast description: Plans backward from a fixed goal or deadline to the present, identifying required milestones, dependencies, critical path, and feasibility constraints to transform aspirational targets into actionable sequenced plans. Use when planning with fixed deadlines, working backward from future goals, mapping critical path, or when user mentions "backcast", "work backward from", "reverse planning", "we need to launch by", "target date is", or "what needs to happen to reach". --- # Roadmap Backcast ## Table of Contents 1. [Workflow](#workflow) 2. [Dependency Mapping](#dependency-mapping) 3. [Critical Path Analysis](#critical-path-analysis) 4. [Common Patterns](#common-patterns) 5. [Guardrails](#guardrails) 6. [Quick Reference](#quick-reference) ## Workflow Copy this checklist and track your progress: ``` Roadmap Backcast Progress: - [ ] Step 1: Define target outcome precisely - [ ] Step 2: Work backward to identify milestones - [ ] Step 3: Map dependencies and sequencing - [ ] Step 4: Identify critical path - [ ] Step 5: Assess feasibility and adjust ``` **Step 1: Define target outcome precisely** State specific outcome (not vague goal), target date, success criteria. See [Common Patterns](#common-patterns) for outcome definition examples. For straightforward backcasts → Use [resources/template.md](resources/template.md). **Step 2: Work backward to identify milestones** Start at end, ask "what must be true just before this?" iteratively. Create 5-10 major milestones. For complex multi-year roadmaps → Study [resources/methodology.md](resources/methodology.md). **Step 3: Map dependencies and sequencing** Identify what depends on what, what can run in parallel. See [Dependency Mapping](#dependency-mapping) for techniques. **Step 4: Identify critical path** Find longest sequence of dependent tasks (this determines minimum timeline). See [Critical Path Analysis](#critical-path-analysis). **Step 5: Assess feasibility and adjust** Compare required timeline to available time. Add buffers (20-30%), identify risks, adjust scope or date if needed. Self-check using `resources/evaluators/rubric_roadmap_backcast.json` before finalizing. Minimum standard: Average score ≥ 3.5. ## Dependency Mapping **Dependency types:** **Sequential (A → B)**: B cannot start until A completes - Example: Design must complete before engineering starts - Critical path impact: Extends timeline - Mitigation: Start A as early as possible, parallelize where safe **Parallel (A ∥ B)**: A and B can happen simultaneously - Example: Backend and frontend development - Critical path impact: None (if resourced) - Benefit: Reduces overall timeline **Converging (A, B → C)**: C requires both A and B to complete - Example: Testing requires both code complete AND test environment ready - Critical path impact: C waits for slower of A or B - Mitigation: Monitor both paths, accelerate slower one **Diverging (A → B, C)**: A enables both B and C - Example: API contract defined enables frontend AND backend work - Critical path impact: Delays in A delay everything downstream - Mitigation: Prioritize A, ensure high quality to avoid rework ## Critical Path Analysis **Critical path**: Longest sequence of dependent tasks (determines minimum project duration) **Finding critical path:** 1. List all milestones with durations 2. Draw dependency graph (arrows from prerequisite to dependent) 3. Calculate earliest start/finish for each milestone (forward pass) 4. Calculate latest start/finish for each milestone (backward pass) 5. Milestones with zero slack (earliest = latest) are on critical path **Example:** ``` Milestone A (4 weeks) → Milestone B (6 weeks) → Milestone D (2 weeks) = 12 weeks (critical path) Milestone A (4 weeks) → Milestone C (3 weeks) → Milestone D (2 weeks) = 9 weeks (non-critical, 3 weeks slack) ``` **Critical path is 12 weeks** (A→B→D path) **Managing critical path:** - **Monitor closely**: Delays on critical path directly delay project - **Add buffer**: 20-30% to critical path tasks (Murphy's Law) - **Resource priority**: Staff critical path first - **Fast-track**: Can non-critical work be delayed to help critical path? - **Crash**: Add resources to shorten critical path (diminishing returns, Brook's Law applies) ## Common Patterns **Pattern 1: Product Launch with Fixed Date** - **Target**: Product live by date, serving customers - **Key milestones (backward)**: GA launch, beta testing, feature freeze, alpha testing, MVP, design complete, requirements locked - **Critical path**: Usually design → engineering → testing (sequential) - **Buffer**: 20-30% on engineering (unknowns), 20% on testing (bugs) **Pattern 2: Compliance Deadline (Regulatory)** - **Target**: Compliant by regulatory deadline (cannot slip) - **Key milestones**: Audit passed, controls implemented, policies updated, gap analysis complete - **Critical path**: Gap analysis → remediation → validation - **Buffer**: 40%+ (regulatory risk intolerant, build extra time) **Pattern 3: Strategic Transformation (Multi-Year)** - **Target**: Future state vision (e.g., "Cloud-native architecture by 2027") - **Key milestones (annual)**: Year 3 (full migration), Year 2 (50% migrated), Year 1 (pilot complete), Year 0 (strategy approved) - **Critical path**: Foundation work (pilot, learnings) enables scale - **Buffer**: 30%+ per phase (unknowns compound over time) **Pattern 4: Event Planning (Conference, Launch Event)** - **Target**: Event happens on date, attendees have great experience - **Key milestones**: Event day, rehearsal, content ready, speakers confirmed, venue booked, date announced - **Critical path**: Venue booking (long lead time) often on critical path - **Buffer**: 10-20% (events have hard deadlines, less flexible) ## Guardrails **Feasibility checks:** - **Available time ≥ required time**: If backward timeline reaches before today, goal is infeasible - **Buffer included**: Add 20-30% to estimates (Hofstadter's Law: "It always takes longer than you expect, even when you account for Hofstadter's Law") - **Dependencies realistic**: Can dependent work actually be done in sequence (handoff time, rework)? - **Resource constraints**: Do we have people/budget to parallelize where needed? **Common pitfalls:** - **Optimistic sequencing**: Assuming perfect handoffs, no rework, no blockers - **Ignoring dependencies**: "We can start everything at once" → actually highly sequential - **No buffer**: Plans with 0% slack fail on first hiccup - **Scope creep**: Target outcome expands during execution, invalidates backcast - **Sunk cost fallacy**: When backcast shows infeasibility, adjust scope or date (don't plow ahead) **Quality standards:** - Milestones have clear deliverables (not "working on X") - Dependencies explicitly mapped (not assumed) - Critical path identified (know what determines timeline) - Feasibility assessed honestly (not wishful thinking) - Risks documented (what could extend timeline?) - Owners assigned to each milestone (accountability) ## Quick Reference **Resources:** - **Quick backcast**: [resources/template.md](resources/template.md) - **Complex roadmaps**: [resources/methodology.md](resources/methodology.md) - **Quality rubric**: `resources/evaluators/rubric_roadmap_backcast.json` **5-Step Process**: Define Target → Work Backward → Map Dependencies → Find Critical Path → Assess Feasibility **Dependency types**: Sequential (A→B) | Parallel (A∥B) | Converging (A,B→C) | Diverging (A→B,C) **Critical path**: Longest dependent sequence = minimum project duration **Buffer rule**: Add 20-30% to estimates, 40%+ for high-uncertainty work **Feasibility test**: Required time ≤ Available time (with buffer)
More from lyndonkl/claude
- abstraction-concrete-examplesBuilds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels. Bridges communication gaps, reveals hidden assumptions, and tests whether abstract ideas work in practice. Use when explaining concepts at different expertise levels, moving between abstract principles and concrete implementation, identifying edge cases by testing ideas against scenarios, designing layered documentation, decomposing complex problems into actionable steps, or bridging strategy-execution gaps.
- academic-letter-architectGuides the creation of evidence-based academic recommendation letters, reference letters, and award nominations that combine concrete examples, meaningful comparisons, and genuine enthusiasm. Use when writing recommendation letters for students, postdocs, or colleagues, or when user mentions recommendation letter, reference, nomination, letter of support, endorsement, or needs help with strong advocacy and comparative statements.
- adr-architectureDocuments significant architectural and technical decisions with full context, alternatives considered, trade-offs analyzed, and consequences understood. Creates a decision trail that helps teams understand why decisions were made. Use when choosing between technology options, making infrastructure decisions, establishing standards, migrating systems, or when user mentions ADR, architecture decision, technical decision record, or decision documentation.
- adverse-selection-priorProduces a Bayesian prior probability that an offered transaction is +EV for the recipient, given that the counterparty chose to propose it. Applies Akerlof market-for-lemons logic -- if they offered it, they believe it is +EV for them, so the prior that it is +EV for us is materially below 50%. Reusable across trade evaluation, waiver drops (another team dropping a player is also adverse selection), job-offer analysis, M&A, and any "someone offered me this" situation. Use when you receive an unsolicited trade/offer/proposal, analyzing incoming trade prior, evaluating why a counterparty proposed a deal, or when user mentions adverse selection, market for lemons, why did they offer this, incoming trade prior, they proposed it, Bayesian adjustment on received offer.
- alignment-values-north-starCreates actionable alignment frameworks that give teams a shared North Star (direction), values (guardrails), and decision tenets (behavioral standards). Enables autonomous decision-making while maintaining organizational coherence. Use when starting new teams, scaling organizations, defining culture, establishing product vision, resolving misalignment, creating strategic clarity, or when user mentions North Star, team values, mission, principles, guardrails, decision framework, or cultural alignment.
- analogy-weight-checkFor every analogy in a substacker draft, verifies it carries mechanical weight — the analogy does real work explaining the mechanism, not merely decorates it. Cross-references analogy-catalog.md for novelty (is this analogy reused from a prior post?) and domain fit (biology > organizational > sports preferred; physics/military disfavored). Use whenever an analogy appears in the draft. Trigger keywords: analogy weight, decorative, mechanical weight, reused analogy, catalog check, metaphor check.
- answer-uncomfortable-questionTakes one strategic question about substacker ("should we launch paid?", "is this section dead?", "are we writing for the wrong audience?") and produces the mandatory evidence + reasoning + downside triad plus a recommendation. Used 3 times per Growth Strategist review. Trigger keywords: uncomfortable question, strategic question, evidence reasoning downside, triad.
- attribute-performanceFor each substacker post that materially over- or under-performs the rolling baseline (|z| ≥ 1.0), produces a plain-English attribution paragraph with calibrated confidence (high / medium / low / unexplained). Considers subject-line effect, topic zeitgeist, external share, day-of-week, length effect, and audience-notes signals. Labels unexplained outliers explicitly rather than fabricating a story. Use after compute-baseline when outlier posts exist. Trigger keywords: attribution, why did this post work, outlier explanation, performance analysis.
- auction-first-price-shadingComputes the optimal shaded bid for a first-price sealed-bid auction given a true private value, an estimate of the number of competing bidders N, and a value-distribution assumption. Implements the `(N-1)/N` equilibrium shading rule for uniform private values, adjusts for log-normal or empirical value distributions, layers a risk-aversion adjustment, and caps output against the bidder's remaining budget. Domain-neutral auction theory reusable across fantasy sports (baseball FAAB, NBA/NHL waiver auctions), prediction-market limit sizing, sealed procurement bids, and any blind-bid context. Use when user mentions "first-price auction bid", "sealed bid shading", "(N-1)/N", "FAAB bid amount", "auction shading", "optimal bid first-price", "bid for sealed-bid", "blind bid sizing", or when downstream logic needs a principled shade factor rather than an ad-hoc heuristic.
- auction-winners-curse-haircutApplies a Bayesian haircut to a bid valuation for common-value auctions where winning is itself evidence the bidder over-estimated. Takes a raw valuation, a value-type classification (common_value / private_value / mixed), the number of informed bidders N, and a signal-dispersion estimate, and returns an adjusted valuation. Domain-neutral and reusable across fantasy FAAB, prediction markets, M&A bids, ad-auction budgets, and any generic bidding context. Use when user mentions "winner's curse", "common value auction", "valuation haircut", "adverse valuation", "Bayesian bid adjustment", or "over-paying in auction".