Untangling the spaghetti: How we decoupled our legacy codebase

June 27, 2025
3 min read
Abstract diagram of modular software architecture representing the decoupling of a legacy codebase.

How we decoupled TechWolf’s legacy codebase

At TechWolf, we recently took on a critical engineering milestone: untangling and decoupling our monolithic legacy codebase. What started as a tightly woven backend had become a barrier to scale, testing, and independent development. Over time, growing feature needs and tight timelines had led to what we affectionately called "spaghetti code."

This post shares how we:

  • Mapped dependencies and domain boundaries
  • Used event-driven architecture to break tight coupling
  • Introduced modular services without pausing feature delivery
  • Made cultural shifts to support better ownership and velocity

We also share real-world lessons from balancing technical debt, migration risk, and momentum: the kind of hard-won insight only a live product can teach.

Read the full breakdown on Medium

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Using AI while interviewing at Techwolf

At TechWolf, we see generative AI as part of the modern toolkit — and we expect candidates to treat it that way too. We love it when people use AI to take their thinking to the next level, rather than to replace it.You are welcome to use tools like ChatGPT, Claude, or others during our interview process, especially in take-home assignments or technical exercises. We encourage you to bring your full toolkit — and that includes AI — as long as it reflects your own thinking, decisions and creativity.We don’t see AI as replacing your skills. Instead, we’re interested in how you use it: to brainstorm ideas, speed up iteration, validate your thinking, or unlock new ways of approaching a challenge. Great candidates show judgment in when to rely on AI, how to adapt its output, and where to go beyond it.

What we’re looking for:

Our interviews are designed to understand how you think, solve problems, and express ideas. Using AI in a way that amplifies those things — not masks them — is encouraged.

What to avoid:

We ask that you don’t submit AI-generated work without review, or present answers that you can’t fully explain. We’re not testing the model — we’re getting to know you, your skills, and your potential. If there are cases where we don’t want you to use AI for something, we’ll tell you ahead of the interview being booked.In short: use AI as you would on the job — as a smart assistant, not a stand-in.

Example: Programming with AI

In a coding challenge, you’re welcome to use generative AI to support your workflow — just like you might in a real development environment. For instance, you might use AI to quickly generate boilerplate code, look up syntax, or get a first-pass solution that you then adapt and debug collaboratively. What we’re interested in is your ability to reason through trade-offs, communicate clearly, think about complexity and iterate effectively — not whether you memorized the syntax perfectly. If using AI helps you stay in flow and focus on higher-level problem-solving, we consider that a strength. There could be some challenges where we won’t allow you to use AI - in that case we’ll tell you in advance, and will tell you why.

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