Tech Debt

# Tech Debt Management

Systematically identify, categorize, and prioritize technical debt.

## Categories

| Type | Examples | Risk | |------|----------|------| | **Code debt** | Duplicated logic, poor abstractions, magic numbers | Bugs, slow development | | **Architecture debt** | Monolith that should be split, wrong data store | Scaling limits | | **Test debt** | Low coverage, flaky tests, missing integration tests | Regressions ship | | **Dependency debt** | Outdated libraries, unmaintained dependencies | Security vulns | | **Documentation debt** | Missing runbooks, outdated READMEs, tribal knowledge | Onboarding pain | | **Infrastructure debt** | Manual deploys, no monitoring, no IaC | Incidents, slow recovery |

## Prioritization Framework

Score each item on: - **Impact**: How much does it slow the team down? (1-5) - **Risk**: What happens if we don't fix it? (1-5) - **Effort**: How hard is the fix? (1-5, inverted — lower effort = higher priority)

Priority = (Impact + Risk) x (6 - Effort)

## Output

Produce a prioritized list with estimated effort, business justification for each item, and a phased remediation plan that can be done alongside feature work.