Debt is meant to be managed, not feared
How to Deal With Technical Debt While Shipping New Features (Without Losing Your Mind)
Every product builder knows that moment.
You’ve just specced a new feature. It’s slick. It’s high-impact. The team’s excited. Then someone says:
“Uh… we’re gonna have to refactor this part of the codebase first.”
And just like that, you’re staring into the abyss of technical debt.
Welcome to one of the trickiest balancing acts in product development: shipping new features while not letting the foundations rot. Here's how to think about managing tech debt when resources are tight, timelines are tight and the roadmap keeps marching forward.
1. Tech Debt Is a Strategic Problem, Not Just an Engineering One
First, let’s reframe. Technical debt isn’t just a pile of code sins—it’s a reflection of tradeoffs you made to move fast at some earlier point. That’s not inherently bad. In fact, most debt was probably the right call back then.
The real danger is when it goes unmanaged. Like financial debt, tech debt needs a strategy:
What’s accruing interest?
What’s blocking growth?
What’s just sitting there, annoying but harmless?
Treating tech debt as a core part of your product strategy—not just engineering hygiene—changes the conversation. It becomes part of prioritization, not an afterthought.
2. Decision-Making with Limited Resources: Pick Your Battles
If you had infinite engineers, sure, you’d rebuild everything and ship new stuff all the time. But you don’t. So how do you decide what to clean up?
Here’s a framework that’s worked for many teams:
Filter debt through the lens of feature delivery.
Ask:
Is this debt actively slowing down our ability to ship new features?
Will tackling this area enable more capabilities in the next 6–12 months?
Is there a compounding cost to letting this sit?
If yes to any of the above: raise its priority. If not, maybe it can wait.
Bundle debt cleanup into roadmap work.
Let’s say you’re building a new analytics dashboard, and the old data pipeline is... fragile, to say the least. That’s the perfect moment to wrap in debt payoff: you’re already in the code, you already have context, and the improvement ties directly to a product goal.
Debt cleanup with product ROI? That’s the dream.
3. Use a “Debt Budget”
Every sprint or cycle, carve out a small, consistent slice of engineering capacity—maybe 10–20%—for paying down debt. Don’t wait for “clean-up weeks” that never come.
This forces prioritization. It also gives engineers room to proactively flag improvements instead of duct-taping things forever.
If leadership asks, “Why are we spending time on this instead of features?”—have clear answers:
“This will reduce dev time by 30% over the next three sprints.”
“This unlocks the new API we need for that customer request.”
Make the ROI visible.
4. When to Consider Adding AI to the Mix
AI isn’t a magic wand, but it can help with both tech debt and new features—if used thoughtfully.
Here’s when it’s worth bringing into the conversation:
✅ You’re dealing with repetitive code changes or migrations.
AI-assisted tools (like GitHub Copilot or Codemod tools) can accelerate cleanup tasks that would normally suck up weeks of dev time.
✅ You’re rebuilding internal tooling.
Want to enhance a support dashboard with smart summarization? Add autocomplete to an admin tool? AI can breathe new life into systems that were previously too annoying to overhaul.
✅ You’re building new user-facing features.
Sometimes the best reason to not tackle certain debt is because AI allows you to leapfrog it. For example, adding an LLM-powered search may reduce your need to rebuild a custom query engine—for now.
Just make sure you’re not layering complexity on top of already bad foundations. AI should simplify or accelerate. If it’s doing the opposite, pause.
The TL;DR
Tech debt isn’t failure—it’s a reflection of past choices. What matters is how you manage it.
Align debt cleanup with product outcomes. If it blocks velocity or feature quality, it’s a priority.
Carve out a recurring “debt budget” so you’re not always putting it off.
Use AI when it reduces effort, unlocks new value, or replaces brittle systems—not just for the hype.
You don’t have to pick between moving fast and building well. The magic is in doing both—intentionally.
Got a favorite approach for balancing debt and features? Or horror stories of when you didn’t? Hit reply or DM me on Twitter—I’d love to hear how your team tackles it.