Stop Letting Technical Debt Slow You Down

[Akash1134]

TL;DR

Your backlog is full of tasks nobody wants to touch: duplicate code, missing tests, outdated dependencies, legacy patterns. These pile up because features always win the priority battle. GitHub Copilot (in your IDE and as a background agent) can automate the refactors and upgrades thus giving your senior engineers time back for the work that actually matters.

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The Problem Every Team Knows Too Well

You've seen this pattern before. Sprint planning starts with good intentions. Someone mentions the deprecated library that's three major versions behind. Another engineer brings up the duplicate authentication code living in five different services. The tech lead points to the test coverage gaps that make every deployment nerve-wracking.

Everyone nods. "We should really fix these."

Then feature requests land. Roadmap commitments loom. And those fixes get pushed to "next quarter." Again.

Meanwhile, the costs keep mounting:

• Your best engineers spend hours manually updating dependencies instead of designing new systems
• Code reviews turn into debates about inconsistent patterns because nobody documented the "right way"
• Onboarding new developers takes longer because the codebase is a patchwork of different eras
• Deploys get riskier as outdated libraries accumulate known vulnerabilities

Here's the reality: Technical debt isn't a weekend project anymore. For most teams, it's systemic. And the usual solutions - debt sprints, rotation assignments, dedicated cleanup quarters - only work if you can actually carve out the time.

What if you didn't have to choose between shipping features and maintaining your codebase?

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Two Ways Copilot Tackles the Work Nobody Wants

Your In-the-Moment Refactoring Partner

You're reviewing code and spot a pattern you've seen twelve times before. Or you're adding a feature and realize the surrounding code is a mess. Instead of opening a ticket that'll sit in the backlog for months, you can fix it now.

In your IDE (VS Code, Visual Studio, JetBrains, Xcode):

• Highlight the messy code
• Ask Copilot: "Extract this into a reusable helper and add error handling"
• Review the suggestion
• Apply it with one click

Real examples teams use daily:

• Standardizing logging formats across a service
• Adding the null checks that should have been there from the start
• Replacing deprecated API calls with current versions
• Generating the unit tests you've been meaning to write

The difference? You fix it while you're already in context, not months later when you've forgotten why it matters.

📖 More tips: Using GitHub Copilot in your IDE: Tips, tricks, and best practices

Your Background Cleanup Crew

Some refactors are too big to do while you're trying to ship a feature. Framework upgrades that touch 50 files. Removing feature flags from six months ago that nobody cleaned up. Migrating an entire codebase to strict TypeScript.

Copilot coding agent handles these asynchronously:

1. Create a GitHub Issue: "Remove all feature flags marked for cleanup in Q2"
2. Assign it to @github
3. Copilot spins up a development environment, makes the changes, runs your tests, and opens a pull request
4. You review it like any other PR - leave comments if changes are needed, approve when ready

The agent works in a sandbox with guardrails baked in:

• Can only push to its own copilot/* branches (your main branch stays protected)
• Every PR requires your approval before any CI/CD runs
• All commits are logged and auditable
• Your existing branch protections and security checks still apply

📖 Deep dive: GitHub Copilot coding agent 101: Getting started with agentic workflows

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What Actually Works (From Teams Doing This Now)

Start with the low-hanging fruit

Don't try to solve all your tech debt at once. Pick one or two concrete, annoying problems:

• That code duplication everyone complains about in reviews
• The dead imports and unused functions cluttering up files
• The missing tests on the most frequently changed modules

Run a pilot in 5–10 repos. Measure how long refactors actually take now versus before. Track merge rates and CI pass rates. Get a baseline.

Teach Copilot what "good" looks like for your team

Create .github/copilot-instructions.md in your repositories. Write down the standards that usually live in people's heads:

## Our Standards- Use structured logging, not console.log - Sanitize user input before database queries - Check for null/undefined on all optional parameters - Keep functions under 50 lines (extract helpers if needed) - Every public function needs a test - Flag any loops that might trigger N+1 queries

Now Copilot suggests code that matches your patterns automatically. No more "please use our logger" comments in every PR.

📖 Guide: 5 tips for writing better custom instructions for Copilot

Keep the safety nets in place

Automation doesn't mean turning off your brain:

• Copilot PRs go through the same review process as human PRs
• Your CI/CD pipeline still runs all tests and checks
• Branch protections, required approvals, security scans - everything stays on
• Use staging environments and canary deploys for risky changes

Measure what you care about

After a month, ask:

• How much faster are refactor PRs getting merged?
• How many review rounds do they need now versus before?
• Which Copilot suggestions did people accept? Which did they reject?
• Are lint warnings going down? Duplicate code shrinking?
• Most importantly: Are your senior engineers spending less time on grunt work?

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What This Looks Like in Practice

One team had a backlog of 40+ dependency update tickets. Some were over a year old. Risk was piling up—known vulnerabilities, incompatible versions, the works.

They started assigning update tasks to Copilot coding agent. The agent would:

• Update the package version
• Fix breaking API changes
• Run the test suite
• Open a PR with clear before/after context

What used to take an engineer 2–4 hours per update (researching changes, updating code, fixing tests) now took 15 minutes of review time. They cleared 30 updates in two weeks - while shipping features at the same pace.

Another example: A team spent months trying to standardize error handling across their microservices. Every PR had "use the error handler" review comments. They added a custom instruction to Copilot about their error handling pattern. New code started following the standard automatically. Review time dropped. Consistency went up.

📖 Real story: How the GitHub Billing team uses coding agent to continuously burn down technical debt

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Getting Started This Week

Week 1: Set up and measure

• Make sure everyone has Copilot (both IDE and coding agent access)
• Count how many "tech debt" or "chore" PRs are sitting in your backlog
• Track how long refactors usually take from "started" to "merged"
• Write your first .github/copilot-instructions.md with 3–5 rules

Weeks 2–4: Run a small pilot

• Pick 5–10 repositories
• Choose 1–2 annoying problems (duplicate code, missing tests, old dependencies)
• Use Copilot in the IDE for quick fixes as you go
• Assign bigger sweeps to coding agent
• Watch the PRs come in, review them, give feedback

Week 5: Check the results

• Did refactors get faster? By how much?
• Are PRs cleaner? Fewer review cycles?
• What suggestions worked well? What needed tweaking?
• Update your custom instructions based on what you learned
• Decide which repos to expand to next

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Common Questions

"Will this break things?"
Copilot doesn't bypass your review process. Every change goes through PR review, automated tests, and whatever gates you already have. You're still in control.

"Is it secure enough for production code?"
Coding agent runs in an isolated environment with limited permissions. It can't merge its own PRs. All changes are logged. Your security scanning (CodeQL, Dependabot, etc.) still runs on every PR. You set the policies.

"What if the suggestions are wrong?"
That's what reviews are for. Accept the good ones, reject the bad ones. Over time, your custom instructions get better and suggestions get more relevant. It's a learning process.

"Can we make it focus on what matters to us?"
Absolutely. Custom instructions let you steer it toward your priorities—security patterns, performance considerations, accessibility requirements, whatever your team values.

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Further Reading

Documentation:

• About GitHub Copilot coding agent
• How to assign an issue to Copilot
• Adding custom instructions for Copilot

Practical guides:

• 5 ways to integrate coding agent into your workflow
• Tips and tricks for using Copilot in your IDE
• Level up your code reviews with Copilot

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Try It Today

Pick one task from your tech debt backlog. Something concrete and annoying. A dependency that needs updating. Duplicate code everyone complains about. Missing tests on a critical path.

Hand it to Copilot. See how long it takes. See how clean the PR is. See how much time you saved.

Then ask yourself: What else could you automate so your team can focus on building instead of maintaining?

What's the first piece of tech debt you'll tackle? Drop a comment below 👇