Over the years, my opinion on technical debt has changed a lot. Earlier, I used to think technical debt meant bad engineering decisions.
Now I think differently.
In product companies, especially fast-moving SaaS and AI products, some level of technical debt is unavoidable. If teams try to make everything perfect from day one, they usually move too slowly.
The real problem is not technical debt.
The real problem is when nobody knows:
- why the shortcut was taken
- how long it can survive
- what impact it will create later
Personally, I look at technical debt in 3 broad categories:
- Strategic debt : Shortcuts taken consciously to move faster, validate ideas, or release quickly.
- Operational debt: Things that slowly start hurting deployments, production stability, debugging, support effort, and developer productivity.
- Architectural debt: This is the one that becomes dangerous over time. Scaling becomes harder, integrations become messy, releases become slower, and every new feature starts feeling more expensive to build.
I feel AI products make this even more complicated. In normal SaaS systems, debt usually impacts engineering speed. But in AI systems, technical debt can directly affect:
- response quality
- hallucination handling
- latency
- observability
- model cost
- evaluation consistency
And because AI systems are probabilistic, debugging becomes much harder compared to traditional software.
I’ve also seen SaaS platforms suffer heavily from invisible debt because of:
- multi-tenant complexity
- customer-specific customizations
- integrations
- deployment dependencies
- security and compliance requirements
One weak architectural decision early on can create pain for years.
That’s why I personally prefer making technical debt visible and measurable instead of treating it as a future problem.
Some of the signals I usually watch:
- deployment friction
- rollback frequency
- incident trends
- onboarding difficulty for new engineers
- release confidence
- overall engineering velocity
One pattern I’ve noticed repeatedly:
When team size keeps increasing but delivery speed keeps dropping, technical debt is already affecting the organization.
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