Why Foundation Comes Before Speed

Everyone ships fast. Few build to last. A practical guide to foundation-first engineering in an age obsessed with speed.

I’ve been building and leading engineering teams for 15 years. Over 50 projects. Startups, enterprises, legacy systems, greenfield builds. Some still live. Some failed. Some never shipped. Some are still in development.

And I keep seeing the same pattern.

Teams ship fast. Then they slow down. Not because the engineers got lazy. Because the foundation was never there.

At INNOMIZE, we used to maintain systems 20+ years old. No documentation. No standards. The original developers left years ago. When we ask stakeholders about business logic, they say “read the code”.

So my teams, sometimes decompiling binary files just to understand what’s inside. Debugging at runtime because that’s the only way to see how things actually work. Previous teams deployed code to AWS without committing the code to source control, and it was gone.

This is what engineering looks like for most of us. Not the AI demos. Not the apps shipped in a weekend. The behind-the-scenes work of understanding systems well enough to keep them running and make them better.

I’ve been thinking about why nobody talks about this part. Everyone is talking about greenfield projects, one-prompt demos, and “vibe coding”.

Why I Started Writing This

You’ll see posts about vibe coding, AI-augmented development, and shipping apps in hours. Everyone can build now. Engineering teams are obsolete.

I’m not saying AI isn’t real. I use these tools every day. The productivity gains are real.

But there’s a gap between what people post and what I see in actual projects.

The posts show demos that work. The reality is production systems that break. The posts celebrate shipping fast. The reality is that teams spend months paying back technical debt from shipping too fast.

The teams that chase speed without foundation always hit a wall. The teams that invest in clarity first end up moving faster in the long run.

I’m living this right now.

I have a team working on a project that I believe could become a foundation. Something we could bootstrap and reuse across many projects. I shared my ideas, the references, the vision, feature list. The team executed and built it.

A few months later, I looked at the results. And I saw the gaps.

Lack of architecture. Missing best practices. No standards. The code was messy. Not because the team was bad. Because I hadn’t given them enough clarity upfront. Because we don’t have a proper review process in place. We believe team understand our intent, our goals.

So now I’m fixing it. Not by rewriting everything. By building the foundation that should have been there from the start. Writing documentation. Defining standards. Creating references that both AI agents and humans can understand.

Maybe I’m overthinking it. But I believe this work matters. At minimum, it helps our team understand why foundation is important. At best, it becomes something we can build on for years.

This is the work nobody posts about. But it’s the work that makes everything else possible.

The industry is obsessed with speed. I think we’re missing something more important.

The demo works. The demo always works. It’s what comes after that separates software that lasts from software that collapses.

The Iceberg Problem

This is the iceberg problem.

What you see is 20% above the water. The shiny demos. The fast shipping. The everyone can build apps now narrative. Vibe coding, agentic AI, context engineering, apps built in hours.

What you don’t see is the 80% below. The maintenance. The technical debt. Engineers connecting systems that were never meant to work together. Data inconsistencies that accumulated over years. Teams spending days just to understand what the previous developer was thinking. Edge-case or abnormal behaviors from external system that could harm your system.

That 80% is where my teams and I spend most of our time. And I think it’s where the real lessons are.

People say “build the 20% that matters” But what about the trade-offs and risks that come with the other 80%? Nobody talks about that part.

The Speed Trap

I see this pattern repeat across projects.

A team starts fast. AI tools, modern stack, motivated engineers. The first version ships in weeks. Everyone celebrates.

Then users show up. Edge cases appear. The payment flow breaks. The data sync fails silently. Features that worked in demo crash under real load.

Suddenly the team that was moving fast is spending months fixing things. Not building new features. Just paying back the debt from shipping without foundation.

Leadership gets frustrated. “Why is the team slow now?”

The team isn’t slow. They’re doing the work that should have been done upfront.

I’ve had this conversation dozens of times. With founders, with CTOs, with project managers. The pattern is always the same:

Speed without foundation creates the illusion of progress. Then reality catches up.

Every shortcut has a cost. You just don’t see it until later.

Maintenance Costs More Than Building

Here’s something most people don’t think about until it’s too late.

Maintaining software costs more than building it from scratch.

Think about repairing a house. You don’t just fix the broken part. You investigate the structure. You remove old materials. You work around things that can’t be changed. Then you build the new thing. The investigation and removal often cost more than the construction itself.

Software is the same.

When you inherit a system without documentation, without standards, without clarity, every change becomes an archaeology project. You spend more time understanding than building. More time removing than adding.

This is why teams eventually face the rebuild or refactor question. Sometimes it’s cheaper to start over than to keep fixing what was built without foundation.

I’ve seen teams spend months refactoring systems that took weeks to build originally. The original build was fast. The maintenance became slow and expensive.

The time you “save” by skipping foundation gets paid back with interest during maintenance. Every shortcut in building becomes a tax on every future change.

Foundation isn’t just about building faster today. It’s about maintaining sanity for years to come.

The AI Paradox

Here’s something interesting I’ve noticed.

AI makes code generation 10x faster. That’s real. I’ve seen it in my own work.

But AI also increases cognitive load by 30-40%.

Wait, what?

Think about it. When AI generates code, someone still needs to verify it’s secure, check for edge cases, understand the logic before shipping, and maintain it when something breaks.

AI doesn’t eliminate this work. It just changes who’s responsible for catching problems.

I read that Anthropic’s CEO said 90% of their internal code is now AI-generated. But the follow-up quote was more interesting: “We’re not replacing engineers”.

The 10% that humans still handle? That’s the leverage zone. Architecture decisions. Debugging complex problems. Understanding why something should work a certain way, not just what it should do.

AI is a turbo, not a robot.

It speeds up what you already have. Good foundation? AI makes you faster at building good software. Bad foundation? AI makes you faster at building bad software.

This is the paradox nobody wants to talk about.

AI is typing. Engineering is thinking.

What I Learned the Hard Way

Early in my career, I thought engineering was about writing code fast.

It took me years to realize engineering is actually about understanding systems deeply.

Code is just how we express that understanding. Speed without understanding is just organized chaos.

I learned this through painful experience. Projects where we shipped features nobody fully understood. Every time, those features came back to haunt us. Bugs that took weeks to debug because nobody knew how the code actually worked. Changes that broke things in unexpected ways because dependencies were never mapped.

Now, when I lead teams, I push for one thing above all else: clarity before speed.

If the team doesn’t understand what they’re building, we slow down until they do. If the documentation doesn’t exist, we create it. If the standards aren’t clear, we define them.

This feels slow in the moment. It’s actually faster in the long run.

The teams I’ve seen succeed aren’t the ones that ship fastest at the start. They’re the ones that build understanding into everything they do.

The Foundation Problem

Everyone asks me: “How do I use AI better?”

I think that’s the wrong question.

The right question is: “What foundation do I need before AI can actually help?”

Let me explain what I mean.

AI generates code based on patterns. It doesn’t know your business logic. It doesn’t know why your team made certain architectural decisions. It doesn’t know that this particular integration breaks if you call it more than twice per second.

When your foundation is strong (clear standards, documented decisions, consistent patterns), AI has context to work with. It becomes a genuine multiplier.

When your foundation is weak (scattered knowledge, no documentation, tribal wisdom in people’s heads), AI just generates plausible-looking code that might or might not fit your system.

Same tool. Completely different outcomes.

This is why I keep saying: foundation first, speed follows.

Real speed comes from clarity, not from typing faster.

What This Means for Engineers

If you’re an engineer reading this, here’s what I want you to take away:

The fundamentals matter more than ever.

Everyone has access to AI now. The differentiator isn’t who can prompt better. It’s who understands what they’re building deeply enough to know when AI is helping and when it’s hurting.

Own your code.

The AI wrote it isn’t an excuse when something breaks at 2am. You shipped it. You’re responsible for it. Read the code. Understand the logic. Then ship with confidence.

Be curious.

The engineers I see thriving with AI aren’t the ones accepting every suggestion. They’re the ones asking why did it do that? and what would happen if...? Curiosity is your edge.

The 80% below water is where you build real skills.

Legacy systems, maintenance, debugging. This isn’t glamorous work. But it’s where you learn how software actually behaves in the real world. Don’t avoid it. Embrace it.

What This Means for Leaders

If you’re a founder or engineering leader, here’s what I want you to hear:

You’re only seeing 20% of what your team deals with.

The demos work. The sprint reports look fine. But your team might be drowning in the 80% you don’t see. The legacy code. The missing documentation. The tribal knowledge that walks out the door when someone leaves.

Talk to your team. Ask about their pain points. Not in a status meeting. In a real conversation.

Buying tools is easy. Training is hard.

I’ve seen teams adopt AI tools expecting 10x productivity. Most see modest gains at best. The difference? The teams that succeed invested in foundation first: standards, process, documentation. Then they added AI.

The teams that struggle just added tools to existing chaos. Now they have faster chaos.

Remove friction before adding speed.

This is counterintuitive. When you want to go faster, the instinct is to add more. More tools, more people, more pressure.

Usually, the answer is to remove things. Remove blockers. Remove unnecessary process. Remove the friction that’s slowing your team down.

Foundation first. Then speed follows naturally.

Why I’m Writing This

Most engineering advice sounds good in theory. It falls apart when you’re shipping under pressure.

I’ve spent 15+ years learning what actually works. Not from books or Medium posts. From building things that had to work.

I’m calling this publication Builds That Last because that’s what’s missing in the conversation.

Everyone’s focused on shipping fast. But fast to where? Fast toward what?

Building things that last means knowing what you’re building and why. It means understanding the system well enough to change it confidently. It means creating something that your future self (or the engineer who inherits your code) can actually maintain.

In the AI era, shipping is easy. Building to last is what matters.

This is for engineers and founders who want to build things that last, not things that break. No frameworks copied. No theory without proof. Just what I’ve learned building things that had to work.

What’s Coming

This is the first post, so I want to be honest about what I’m planning.

What you’ll get: Engineering leadership lessons from real projects. Product development principles that survive contact with reality. Honest takes on architecture, teams, and shipping. And yes, how to actually use AI for building products that last (not just demos that impress).

I’ll share stories from real projects (anonymized, but real). The successes. The failures. The lessons that only come from doing this work for 15 years. I’ll also share how we’re designing workflows, standards, and foundations that make AI a genuine multiplier rather than a source of faster technical debt.

Who this is for: Engineers becoming leaders. Founders building technical teams. Anyone tired of advice that doesn’t ship.

Some posts will be practical. Approaches you can apply immediately. Others will be more philosophical. How to think about problems, how to make decisions, how to build things that last.

One Last Thing

Those legacy systems I mentioned at the start? The ones with no documentation, no standards, where read the code is the only specification?

They taught me more about engineering than any greenfield project ever did.

Not because they were well-built. Because they showed me what happens when foundation is missing. What teams inherit when previous developers didn’t invest in clarity. What it actually costs to maintain software over decades.

Every time I help a team build something new now, I think about the engineer who will maintain it in 10 years. Will they understand why we made these decisions? Will they be able to change things confidently? Or will they be stuck doing archaeology, hoping to understand what we were thinking?

That’s what foundation means to me. Building for the people who come after.

That’s what I want to explore in this publication.

Welcome to Builds That Last!

What’s your experience with the 80% below water? I’d love to hear your stories in the comments.