AI Code Maintenance Intelligence

Your code is growing.
Your understanding of it
is not.

AI writes code faster than anyone can understand it. Endure captures intent, detects drift, and surfaces what's silently rotting — before it becomes a crisis.

6mo
half-life of code understanding
without active capture
10×
more code generated
since AI-assisted development
~60%
of maintenance cost attributed
to lost context
0
tools that track
why code exists

Code is easy to write.
Understanding it later is the hard part.

Linters catch syntax. Security scanners catch vulnerabilities. Tests catch regressions. Nothing catches the slow erosion of understanding — until a critical incident reveals it.

🌀

Intent is never captured

Every file was written for a reason. Those reasons live in Slack threads, PR descriptions, and the heads of people who left six months ago.

📉

Code drifts from its purpose

Each change made without understanding the original intent is a small bet against the future. Enough small bets compound into architectural collapse.

🔇

Degradation is invisible

Complexity scores tell you what. Churn tells you where. Nothing tells you why something is becoming fragile or what it's supposed to be doing.

AI makes it exponentially worse

AI-generated code appears without the context that would have existed if a human wrote it slowly. Velocity without understanding is just faster forgetting.


Your codebase, scored by what it knows about itself.

Endure analyzes every file — complexity, churn, staleness, duplication, and how much of its intent has been captured and understood.

endure analyze ./src — 257 files · Understanding Score 32/100 Grade D
src/api/services/debt-analyzer.ts
complexity 95 · churn 100 · 441 lines
CRITICAL · 65
src/core/complexity/technical-debt-scorer.ts
complexity 88 · churn 95 · 612 lines
CRITICAL · 59
src/core/intent/intent-extractor.ts
complexity 62 · churn 70 · 298 lines
HIGH · 41
src/cli/lib/formatter.ts
complexity 18 · churn 12 · 134 lines
LOW · 8
Captured Intent — debt-analyzer.ts · llm_auto · 93% confidence
Orchestrates technical debt analysis by wrapping TechnicalDebtScorer with API-level concerns (validation, error handling, filtering, pagination) and optionally enriching results with KB pattern warnings and intent extraction for high-debt files.
Extracted automatically · stored in Postgres · used for drift detection

Capture once. Detect drift forever.

Endure runs alongside your existing workflow — no new process, no mandatory annotations. It builds understanding progressively from what already exists.

1

Analyze your repository

Point Endure at any git repository. It scores every file on five dimensions: complexity, churn, staleness, duplication, and intent coverage — weighted into a single Debt Score and a Software Understanding Score for the whole codebase.

2

Intent is extracted automatically

For high-debt files, Endure asks an LLM: what is this file supposed to do? The answer is self-judged for quality, stored in a database, and attached to future analysis runs. No manual annotation required. 93% average confidence on the first pass.

3

Drift is detected on every change

As your code evolves, Endure compares what a file is now doing against what it was supposed to do. Drift surfaces as a severity score — not a guess, but a structured comparison against the captured intent.

4

The system gets smarter from every incident

Every maintenance event is a signal. Endure's Knowledge Base extracts patterns from real incidents, validates them against your codebase, and surfaces the ones with high precision — so the next team doesn't make the same mistake.


Not a linter. Not a metrics dashboard.
Something new.

P1

Persistent Intent

Intent is the invariant; code is the implementation. Intent must outlive any single file or function and be versioned as rigorously as code.

P2

Context as Dependency

Missing context causes maintenance failures, not compile failures. Context has a lifecycle: created, consumed, evolved, deprecated.

P3

Inevitable Drift

All systems drift from their original assumptions. Drift is not failure — blindness to drift is. Measurable drift enables corrective action.

P4

Earned Understanding

Understanding cannot be reconstructed from code alone. It must be captured at creation time. It degrades without active preservation.

P5

Antifragility

Systems should improve from maintenance stress. Each fix should reduce future failure probability. Learning must be structural, not just human.

P6

Maintenance as First-Class

Maintenance is not a cost — it's the product learning. Maintenance readiness is measurable. Maintenance velocity is optimizable.


"Code that passes all checks but fails maintainability is the most dangerous code in your system. It's invisible until it isn't."
— Vitor Lourenco, Founder, CodeSlick

Research Preview · Q2 2026

Be the first to run it
on a real codebase.

We're onboarding a small number of design partners who care deeply about code maintainability. No cost during the preview. White-glove setup. Your feedback shapes the product.

No spam. No sales calls. Just a conversation about your codebase.

TypeScript / JavaScript Python Java Go Any git repository Self-hosted or cloud