// Topic
AI Technical Debt
AI technical debt is harder to see than ordinary code debt. It hides in prompts nobody owns, evaluations nobody runs, stale embeddings, unpinned model behavior, and workflows where every small change feels risky.
This hub connects the older technical debt writing with the newer AI-specific debt pattern: invisible system behavior that keeps returning 200 OK while quality quietly degrades.
Start Here
- AI Technical Debt Is Eating Your Team Alive (And You Can’t Even See It) is the current canonical piece on prompt debt, eval debt, pipeline debt, and architecture debt.
- AI Technical Debt Is Eating Your Codebase (You Just Cannot See It Yet) explains the same failure mode from an earlier production AI perspective.
- The True Cost of Technical Debt gives the non-AI baseline: measure the pain before arguing about priority.
Common Debt Types
Prompt Debt
Prompts become legacy code when they are copied from demos, edited without review, and never tied to expected behavior.
Evaluation Debt
Teams without evals argue about quality using anecdotes. That makes every model, prompt, or retrieval change risky.
Data Pipeline Debt
Stale embeddings, missing documents, drifting labels, and weak source tracking create confident wrong answers.
Architecture Debt
Provider-specific logic and tool calls buried in application code make upgrades feel like surgery.
How to Pay It Down
Start with the highest-leverage stabilizers:
- Put prompts and retrieval configs in version control.
- Add a small evaluation set for the highest-risk workflow.
- Track model versions, prompt versions, and data freshness together.
- Add cost attribution by feature or workflow.
- Decouple model access from product logic before switching vendors.
Supporting Reads
- AI Production Governance: A Maturity Model
- RAG Retrieval That Actually Works
- How We Track and Prioritize Tech Debt at a Fintech Startup
- Stop Trying to Fix All Your Tech Debt
Related Hubs
References
6 posts
- AI Technical Debt Is Eating Your Team Alive (And You Can't Even See It)
AI debt doesn't look like normal tech debt. It hides in prompts nobody owns, evals nobody runs, and data pipelines nobody watches. By the time you notice, every change feels dangerous.
AI Technical Debt Is Eating Your Codebase (You Just Cannot See It Yet)
AI features create a new species of technical debt that hides in prompts, data pipelines, and model versions. By the time you notice it, the cleanup bill is brutal.
Most 'Technical Debt' Is Just Decisions You Disagree With Now
The term 'technical debt' has become meaningless. Everything inconvenient is debt. Here's what it actually is, when it matters, and why most teams handle it wrong.
How We Track and Prioritize Tech Debt at a Fintech Startup
A framework for cataloging technical debt, scoring it by impact and risk, and scheduling paydown without stalling feature delivery.
Stop Trying to Fix All Your Tech Debt
A two-number scoring system for tech debt that tells you what to fix now, what to schedule, and what to quietly accept.
The True Cost of Technical Debt
A pragmatic look at technical debt in 2016: what it is, how it shows up, how to measure it, and how to make a business case for paying it down without stalling delivery.