Cognitive Refactoring: Rewriting Your Mental Codebase

How Modular Thinking Can Transform Your Mental Habits and Boost Focus

Lorenzo Bradanini

and

Lorenzo Tettamanti

Jul 18, 2025

When Your Mind Becomes Legacy Code

I know that every engineer perfectly understands the moment I’m about to describe.

You open a codebase, maybe it’s been six months, maybe a year, and your eyes squint involuntarily as you scroll through the first few files.

It's all vaguely familiar, yet it sounds strangely alien. The logic is entangled. The naming is awkwardly cryptic. Functions do too much or too little.

There's a fixLater() comment from a past self who never came back. And there are almost zero notes explaining why anything is the way it is.

At first, you’re very confused. Then you’re suddently becoming more and more frustrated. In the end you get that creeping, existential dread that something is terribly wrong.

And almost without fail, you mutter something like:

“Who the hell wrote this actual mess?”

You mean it. You really do.

Until you realize: it was you.
And no one else touched it.

You wrote this.

Maybe not in your best moment, but in one that made sense then. Maybe you were moving fast. Maybe the product was pivoting every other week. Maybe you were just trying to get something out the door.

You wrote it under pressure. You did your best with what you had.

And yet, today, it feels like trying to decipher someone else’s logic through a dusty pane of glass.

It’s a pretty much strange feeling; disowning your own work, then slowly, almost reluctantly, reclaiming it.

You begin to piece together what past-you was doing. The decisions. The trade-offs. You see the constraints you had forgotten, the rushed patches that somehow calcified into structure.

You don’t hate past-you anymore. You just see the cost of building under fire.

And here's the twist: our minds, I've come to believe, often operate the same way.

We build internal systems (thought patterns, routines, assumptions) in response to context. To survival. To pressure. We don’t always comment our logic. We rarely leave room for refactor.

And before long, we’re living inside a tangled maze of old rules that used to work. That once made sense. But don’t anymore.

Just like legacy code, they’re hard to understand, harder to debug, and downright terrifying to change.

I’ve seen it in myself. I’ve felt it.

For years, I operated on mental scripts I had outgrown. Belief systems optimized for a younger version of me. Productivity rituals that once helped me focus but eventually became cages.

Assumptions about who I was and how I worked that no longer held true: but still ran silently, like background daemons in my cognitive stack.

And like any good engineer returning to an old codebase, I didn’t spot it all at once. It took a few failed routines, some burnout cycles, and a sense of internal fragmentation I couldn’t quite name.

Until one day, I looked at the way I was running my life, and I saw it for what it was.

Legacy code.

Not bad. Not wrong. Just... out of sync with who I had become.

This article is about what happened next.

It’s the story of how I started applying the principles of software engineering, like modularity, decoupling, graceful failure, to my own mind.

How I moved from a brittle, monolithic system to a more resilient, loosely coupled one.

And how, in doing so, I found not only more productivity; but more peace.

Because here’s the truth no one tells you: your mind isn’t broken. But it might be overdue for a refactor.

Let’s dive in.

How Our Mental Systems Become Rigid

We don’t just engineer software. We engineer our lives.

We design intricate workflows for our days with the same mindset we bring to systems architecture: optimize for performance, reduce friction, minimize latency.

We read books on focus, build Notion dashboards like internal control panels, stack habit trackers like logs, and tinker endlessly with apps, calendars, and routines; all in pursuit of some higher-order clarity.

We craft rituals meant to anchor us. Morning routines. Evening reflections. Weekly planning blocks.

We tweak them like code, trying to compile the most productive version of ourselves.

And in the beginning, it feels clean. It feels intentional. Thoughtful.

But somewhere along the way, that elegant design starts to mutate. The routines get heavier. The assumptions pile up. A simple morning ritual becomes a chain of fragile preconditions.

You add one more habit, one more system, one more “non-negotiable”, and before you know it, you’re living inside an over-engineered mess.

That was me.

For years, my mental architecture was a tower of interdependencies. It looked something like this:

If I woke up early, I could meditate.
If I meditated, I’d feel clear enough to journal.
If I journaled, my thoughts would settle and I could start writing.
If I wrote, I’d feel purposeful and productive.
If any one of these failed, the whole thing fell apart.

It was a beautiful system on paper. In practice, it was a tightly coupled nightmare.

One broken link, like a bad night of sleep, a last-minute call, a moment of internal resistance, and the entire structure collapsed.

No meditation? Then no journaling. No journaling? Then no writing. No writing? Then a vague fog of guilt and inertia for the rest of the day.

It was brittle. Linear. Rigid. And completely dependent on ideal conditions.

Like any monolith, it worked impressively well, just until it didn’t. And when it didn’t, there was no fallback. No modularity. No redundancy. Just failure, cascading downward through every layer of my day.

And I didn’t even notice it at first, because from the outside, it looked like discipline. Like structure. Like the right way to live.

But the truth is, just like legacy systems in software, these mental routines had silently grown outdated.

The architecture no longer fit the demands of my life. It was opaque; I couldn’t even remember why I’d structured things a certain way.

It was hard to debug, I didn’t know which habits were helping and which were just decorative.

It was resistant to even the smallest change: every attempt to update one part disrupted something else. And most dangerously, it seemed fine… right up until the moment it completely failed.

That’s the danger of good intentions crystallized into rigid design: what starts as structure can quickly become constraint. What begins as clarity can become calcified.

Eventually, I had to face the truth: I wasn’t evolving. I was just maintaining a fragile system that no longer served me.

And that’s when I realized: it wasn’t just my schedule that needed work.

It was the whole cognitive architecture.

Life Throws an Exception

The first sign of trouble wasn’t dramatic. No catastrophic failure, no deep existential crisis. Just… I overslept.

One day.

No big deal, right?

Except it was. That small deviation from the plan triggered a full-blown cascade failure.

My usual meditation window? Gone. No journaling, either. No clarity. No writing. By 9 a.m., the whole morning routine had crumbled, and with it came a familiar, creeping sense of guilt.

Not the acute kind: more like a slow, systemic dread. The kind that seeps into everything else you try to do, like a silent memory leak slowly eating up your focus and morale.

That day, I wasn’t just off schedule. I was down. Systemically.

And that’s when the architecture analogy hit me.

I hadn’t built a resilient system. I had built a fragile one; optimized not for adaptability, but for control. Every part of my mental routine depended on every other part working exactly as planned.

There was no redundancy. No fault tolerance. No graceful fallback. Just a brittle stack of assumptions waiting to fail.

In software terms, I was still running a tightly coupled monolith. And now that it had broken, I had a decision to make:

Patch it again? Or rewrite it?

I chose the rewrite.

Microservices of the Mind

In modern software engineering, we’ve learned the cost of monoliths. They’re powerful in theory, but bloated and brittle in practice. So we break them down.

We build microservices: small, self-contained components that each handle one responsibility. They communicate via APIs, fail gracefully, and can be updated independently.

So I asked myself:

what if I treated my mind the same way?

I stopped thinking in terms of a singular, precious morning ritual.

Instead, I began decomposing it, mentally and behaviorally, into discrete “services” with clear scopes, triggers, and outputs.

The Writing Service

A 90-minute deep work block. No calendar invites, no notifications. Triggered by placing my phone in another room and brewing a cup of oolong tea. Backed by soft jazz, a clean desk, and (almost) zero distractions.

The Reset Service

A 3-minute breathing protocol (inhale 4, hold 4, exhale 6). Deployed after cognitively demanding work or emotional friction. A lightweight service to clear RAM and re-center. It’s super important to take some time for this, because after that you’ll feel very powerful and fully energic.

The Switch Gateway

A transition layer. I never jump straight from email to deep work. I insert a 5-minute buffer; sometimes it’s just stretching, sometimes silence, sometimes just staring out the window or thinking a bit about random things. The goal is to prevent cognitive collisions.

Each of these had its own logic, and most importantly: they could operate independently.

Writing didn’t require journaling. Journaling didn’t depend on meditation. I let go of the brittle "if-this-then-that" structure and replaced it with swappable components; each one meaningful, each one loosely coupled.

It wasn’t about hacking productivity anymore. It was about building a mental infrastructure that could scale with me and not collapse under pressure.

Graceful Degradation, Not Perfection

The biggest shift? Psychological stability.

Before, if one part of my routine failed, the whole system crashed. It was binary: success or failure, no in-between.

But once I modularized, I started thinking in terms of graceful degradation, which happens to be the same principle we use in distributed systems. If a component fails, the whole application doesn’t need to go offline. It just runs with reduced capability.

Couldn’t do a full 90-minute writing block? Okay, fine. I ran a 30-minute Lite version with lower expectations.

Struggling to focus at my desk? I’d go for a walk and maybe record voice notes. Context switched, but the core outcome persisted.

Feeling emotionally scattered in a specific moment? I’d call the Diagnostic Service:

“What am I avoiding right now?”

Just that one prompt would clear surprising amounts of mental cache.

This wasn’t about doing less. It was about doing smarter. It was about letting the system adapt to its real-world operating conditions: sleep, energy, emotion, chaos.

Just like resilient systems adjust to load and latency, my cognitive structure started adapting to life.

I no longer needed ideal conditions to feel functional. The system didn’t have to be perfect. It just had to degrade gracefully.

Building APIs for Behavior

But even microservices need effective ways to communicate. They don’t run in a vacuum. In software, we build APIs, standard interfaces that allow systems to talk to each other predictably.

In cognitive architecture, I found that environmental triggers worked the same way.

Physical, tangible, often sensory cues that signaled what behavior should be called next, all with minimal friction.

Noise-canceling headphones on? → Deep Work Mode booted
Candle lit on my desk? → Slack is now read-only
Tea in hand? → Begin writing

These weren’t habits. They were interfaces. They required no thought, no willpower. Over time, they became known as stateless switches: behavioral function calls that bypassed internal debate.

And the beauty of these interfaces was consistency. They lowered the cognitive cost of transition.

Rather than burning mental energy deciding whether I “felt like writing,” the tea had already made the call. The headphones had already returned the payload.

The more I tied meaningful behaviors to physical triggers, the more seamless my day became. I wasn’t trying to control everything, I was building protocols. Lightweight, reusable, and context-aware.

A Version Control for the Mind

And finally, no architecture, no matter how elegant or efficient, evolves well without version control.

In software, we track changes. We test. We document. We iterate a lot. That’s how we move forward without breaking the whole system.

So I brought that mindset into my own life, with a few changes.

Every Sunday evening, I ran a cognitive retrospective. Nothing fancy. Just a 20-minute check-in:

What routines worked smoothly this week?
What felt brittle?
What silently failed and needs attention?

I started keeping changelogs in my journal. I labeled experiments. I ran A/B tests:

“Does writing before exercise give me more clarity or less?”
“What if I move planning to the evening? Does that reduce anxiety in the morning?”
“Should this service even exist anymore, or can I deprecate it?”

I treated behavior much more like software, in some senses. Mutable. Testable. Reversible.

No more dogmatic systems. No more clinging to rituals because “they worked once.” I gave myself the freedom to commit small, observe outcomes, and roll back if needed.

What emerged was a mind that no longer felt like a brittle machine, but a living system.

Not perfect, but fully maintainable and ready for updates. Not rigid, but resilient.

Final Thoughts: Maintainable Minds

In the end, this isn’t just about routines or productivity. It’s about reclaiming authorship over the architecture of your own life.

For a long time, I thought I needed to fix myself. That if I just built the right habits, in the right order, with enough discipline, I’d finally arrive at some optimized, failure-proof version of me.

But I was wrong.

What I needed wasn’t perfection. It was hyper-adaptability. Observability. Grace. Modularity.

Because life, like code, breaks in unexpected places. It drifts. It accumulates technical (and, of course, even emotional) debt. But that doesn’t mean you start over from scratch. It means you refactor. You test. You learn.

The truth is, we’re all running legacy logic, a.k.a. patterns written in old contexts, with outdated assumptions. But unlike a machine, you get to question your architecture. You get to change it.

And the moment you do, you’re no longer just operating within the system.

You’re the one designing it from scratch.