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Dynamic Programming Analysis
ASecurityBreak overwhelming problems, decisions, or plans into DP-style sub-problems (base cases, dependencies, reused parts) and solve bottom-up. Use when user says "I don't know where to start", "break this down", "what's the best way to...", or asks for a step-by-step plan, decision matrix, project roadmap, or architecture decomposition.
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- Added November 6, 2026
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[](https://www.skillsdirectory.com/skills/ronnasayd-dynamic-programming-analysis)---
name: dynamic-programming-analysis
description: Break overwhelming problems, decisions, or plans into DP-style sub-problems (base cases, dependencies, reused parts) and solve bottom-up. Use when user says "I don't know where to start", "break this down", "what's the best way to...", or asks for a step-by-step plan, decision matrix, project roadmap, or architecture decomposition.
metadata:
author: Ronnasayd Machado - github.com/Ronnasayd
version: "1.1.0"
---
# Dynamic Programming Analysis
Breaks any complex problem into DP-style sub-problems: **optimal substructure** (solution depends on smaller solutions) + **overlapping sub-problems** (recurring parts, solve once, reuse). Applies to business, personal decisions, architecture, research, learning, projects.
## Protocol
| # | Step | Action | Gate |
| --- | ------------------- | ----------------------------------------------------------------------------------- | ----------------------------------------------------- |
| 1 | Define main problem | Restate precisely, final state, explicit/implicit constraints | — |
| 2 | Decompose | Break into smaller parts; recurse until **base cases** (directly solvable) | tree structure, see `references/response-template.md` |
| 3 | Identify overlaps | Which sub-problems recur across branches? Which partial solutions reuse? | mark explicitly — biggest efficiency win |
| 4 | Resolution order | Base cases first, then by dependency (prereq before dependent) | execution sequence |
| 5 | Solve each | Smallest → largest; compare options if multiple; note which parent problem it feeds | — |
| 6 | Compose | Combine sub-solutions into original problem; validate fit | — |
| 7 | Verify | Edge cases, external dependencies, optimal vs. good-enough | — |
Respond using the template in `references/response-template.md`.
## Adaptations by problem type
| Type | Sub-problem | Base case | Overlap | Composition |
| ---------------------- | -------------------------- | ------------------------------------ | ------------------------------------------- | ------------------------- |
| Decision | each criterion | verifiable facts, not opinions | criteria affecting multiple options | decision table/matrix |
| Planning/Project | each deliverable/milestone | atomic task (1 person, 1 day) | shared deps between phases | schedule/roadmap |
| Technical/Architecture | each component/module | primitive functions/services | reusable utilities/patterns | integration diagram |
| Learning | each prerequisite concept | needs-no-prerequisite knowledge | fundamentals unlocking multiple topics | ordered learning path |
| Business/Strategy | each strategic lever | observable metrics, concrete actions | capabilities supporting multiple strategies | integrated strategic plan |
## Quality principles
- Granular: each sub-problem has a clear, direct answer.
- No pseudo-decomposition: genuinely break down, don't just rename the problem.
- Name dependencies explicitly (what depends on what).
- Bottom-up only — solving big before small causes rework.
- State reuse explicitly when one solution supports another.
## Reference files
- `references/response-template.md` — verbatim markdown response template + sub-problem tree text format.
- `references/example.md` — worked example (career transition into AI).
Files in this skill
- SKILL.md
- references/example.md
- references/response-template.md
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