Tech Debt That Hurts Hiring More Than Performance

When most people talk about technical debt, they point at dashboards.

• Latency is creeping up.
• Error rates spike under load.
• Deployments are slow and flaky.

Those are real problems. But some of the most expensive technical debt does not show up in performance graphs at all.

It shows up in who is willing to work on your systems.

Senior engineers quietly withdrawing from your hiring process once they see the stack. Promising candidates saying "it doesnt feel like a place where I would grow". New joiners taking months to become productive because everything feels bespoke.

In this article, we look at the kind of technical debt that hurts hiring and onboarding more than it hurts raw performance  and how to deliberately pay that debt down.

The Debt Candidates Notice First

Experienced engineers have learned to read between the lines of a codebase, a repo layout, and a deployment story.

When we join an interview loop, pair on a task, or review a take-home, we are not just asking "can I ship a feature here next week?". We are also asking:

• Will I learn here?
• Will I be able to move things forward without constant permission?
• Will I be proud to attach my name to this stack?

Certain kinds of debt are loud signals that the answer is "probably not".

1. In-House Frameworks With No Exit

Many teams have a homegrown framework or internal platform layer that predates the current stack.

On paper, it does helpful things:

• "Simplifies" service creation.
• Wraps the web framework.
• Encodes cross-cutting concerns.

In practice, a candidate sees:

• A custom abstraction nobody outside your company has heard of.
• Sparse or outdated documentation.
• Behaviour that only a few long-tenured engineers fully understand.

For a mid-career engineer, that reads as career-narrowing debt:

• Skills developed on your stack do not transfer cleanly elsewhere.
• They may spend more time reverse-engineering legacy decisions than building new capabilities.

This can be true even if the system is relatively fast and stable.

2. Ancient Tooling Frozen in Time

Another pattern: a stack that is locked to old versions of core tools because upgrades are painful or "too risky".

Candidates quickly notice when:

• You are multiple major versions behind on the main framework.
• CI/CD tooling is brittle and cannot easily be improved.
• Local setup requires a long sequence of manual steps.

The message is not just "we have debt". It is "we do not make time to keep foundations healthy".

That is a warning sign for:

• How hard it will be to introduce new ideas.
• Whether leadership sees infrastructure and developer experience as strategic.

Again, your users may be happy. Performance might be fine. But strong candidates will hesitate to join a team that appears stuck.

3. Opaque Repos and Hidden Knowledge

Repo layout and documentation are surprisingly strong hiring signals.

Some clues that show up quickly:

• A tangle of partially documented services with unclear ownership.
• README files that mention tools or practices nobody uses anymore.
• Critical behaviour controlled by scripts in a personal directory or a long-forgotten wiki.

To an outsider, this suggests:

• They will depend heavily on a few "historians" for months.
• The organisation has not invested in making knowledge legible.

The real cost is not only onboarding time. It is the impression that change is fragile and tribal, not routine.

4. Hero-Driven Operations

Some organisations run on a small group of heroes who know how to work around every quirk.

Signals include:

• Complex releases that only a couple of people are trusted to run.
• Incident response that depends on paging specific names, not teams.
• A culture of "just ask X, they know how this works".

From the outside, this looks risky:

• Will I be able to make changes without becoming a hero myself?
• Will I be asked to carry a disproportionate share of on-call burden?
• Will the organisation ever make time to simplify?

If the honest answer is "we fix things when they are on fire", the message to candidates is clear.

Why This Debt Is So Expensive

Technical debt that hurts hiring is expensive for at least three reasons.

It Shrinks Your Candidate Pool

Strong engineers usually have options. When two offers are comparable on compensation and impact, the stack and ways-of-working become differentiators.

If your system feels like a narrow, inward-looking corner of the ecosystem, the people who are most serious about their craft are more likely to politely decline.

It Slows Onboarding and Momentum

Once someone joins, this kind of debt:

• Extends the time before they can safely ship changes.
• Increases the number of hidden dependencies they must internalise.
• Makes it harder to build confidence, because failure modes are surprising and poorly documented.

Even if they stay, they are likely to avoid touching the riskiest areas. Over time, your organisation quietly loses the ability to evolve its own core.

It Signals How You Make Trade-offs

Perhaps the deepest cost is what this debt says about decision-making.

• Do you invest in developer experience, or only in visible features?
• Do you treat foundational work as an expense, or as an enabler of everything else?
• Do you create slack for upgrades and simplification, or only react under pressure?

Candidates are reading your codebase and tooling as a record of past choices. If it tells the story of a team that always chose "later" for anything internal, they will assume the future looks similar.

Finding the Tech Debt That Scares Candidates

Not all messy code is equal. Some debt is annoying but local; some is a systemic story about how you work.

A practical way to find the latter is to look through three lenses.

Lens 1: First Impressions

Ask recent joiners and candidates (where appropriate):

• What parts of our stack worried you during interviews?
• Which steps in the onboarding process felt most fragile or confusing?
• What surprised you when you first saw our repos and pipelines?

Their answers usually highlight the places where your mental model as insiders no longer matches reality.

Lens 2: Learning Curves

Look at:

• How long it takes a new engineer to ship their first meaningful change.
• Which systems they avoid touching in the first three months.
• Where they most often need pairing or escalation.

Hot spots are often areas where knowledge is concentrated in a few heads or where local complexity is much higher than the underlying business problem.

Lens 3: Upgrade Stories

Review the last few significant upgrades:

• How hard was it to move framework versions?
• How long did it take to introduce a new observability or testing tool?
• How often did "well do it later" become "we never did it"?

If every upgrade felt like a mini-migration project, that is a sign that your architectural seams are not set up for change.

Paying Down Debt for Hiring, Not Just Performance

You cannot fix everything at once. The goal is to deliberately target debt that:

• Affects how attractive your environment is to the people you want to hire.
• Blocks new joiners from gaining confidence.
• Tells the wrong story about your priorities.

A few pragmatic moves.

1. Make One Path Modern and Boring

Instead of trying to modernise everything, choose one path where you say:

"If you work here, this is what it feels like to build and ship software."

For example:

• A well-documented template for a new service.
• A straightforward CI/CD pipeline with clear stages and fast feedback.
• Built-in observability and simple runbook examples.

Use this as the default for new work. Over time, you can migrate high-value existing services into this path.

2. Put Documentation Where Candidates Look

Invest in making a few key artefacts excellent:

• A top-level README that explains how the system hangs together.
• A "new engineer" guide that covers local setup, first change, and how to get help.
• A short internal narrative about where you are coming from and where you are going architecturally.

Candidates and new joiners will read these as carefully as they read the code.

3. Create an Escape Hatch From In-House Frameworks

If you have a heavy internal framework, it may not be realistic to remove it quickly.

You can still:

• Document the architecture clearly, including why it exists.
• Define a path for new components to be built with more standard tools.
• Isolate the custom parts behind well-defined interfaces.

The message becomes: "We know this is complex, and we have a plan to simplify", instead of "this is just how things are".

4. Make Upgrade Work Visible and Regular

Schedule and track upgrade work like any other priority.

• Keep a small, recurring budget for dependency and tooling upgrades.
• Celebrate when foundational upgrades ship with minimal drama.
• Use incidents and friction as prompts to invest, not just to patch.

This signals that you are willing to pay down debt proactively, not only when forced.

Talking About Tech Debt Honestly in Hiring

Strong candidates expect some technical debt. What matters is whether you understand it and are actively working with it.

It helps to:

• Be explicit during hiring about where the debt lives and why.
• Share a realistic picture of the next 1218 months of improvement work.
• Invite candidates to ask hard questions about architecture, tooling and ownership.

This level of honesty filters in people who are motivated by improvement, not just by greenfield.

Questions to Ask About Your Own Stack

If you want to evaluate your tech debt through a hiring lens, you can start with a few questions:

• What parts of our system would we hesitate to show a strong candidate?
• Where does our stack feel most "career-narrowing" rather than "career-growing"?
• How long does it take a new engineer to ship a confident change?
• Which upgrades do we quietly avoid because they feel too risky?
• What small, concrete step could we take in the next quarter to make our environment more attractive to the people we want to hire?

Not all technical debt is created equal. Some slows page loads by a few milliseconds. Some quietly shapes who joins your team, who stays, and who feels able to change the system.

The second category rarely shows up in graphs, but it may matter more than anything else you ship.