Debugging in Production: The Most Stressful Thing We’ve Done - and Why It Built Our Strongest Client Relationship

What happens when “good enough now” beats “perfect later” - and how to survive it

There are experiences in client work that you wouldn’t wish to repeat and wouldn’t trade for anything. This is one of them.

A few months into a complex AI implementation, our client found themselves in a difficult position. Their existing system was struggling under increased workload. Additional development they had contracted elsewhere was running behind schedule. The pressure on their operations was real and growing. And our system - still being refined, still being tested, not yet where we wanted it to be - was the most capable option they had available.

They asked us to go live on their actual production process.

Every instinct in a developer says no to this. You test in controlled environments. You stage releases. You verify before you deploy to anything that touches real operations. The protocols exist for good reason, and we knew exactly what we were being asked to set aside.

We said yes anyway.

What followed was among the most intense periods of work I can recall. We were processing real workload while simultaneously identifying and resolving issues that only surface under real conditions. Problems that testing had never revealed appeared immediately in production. We were debugging, fixing, and redeploying while the system was in active use - a situation that is exactly as uncomfortable as it sounds.

The honest account is that it was stressful, it was not something we would choose, and there were moments where the risks felt very present. But there is also an honest account of what it produced.

Because we were working on live processes, feedback was immediate and unambiguous. Issues that might have taken weeks to surface in controlled testing appeared within hours, were resolved, and made the system measurably stronger in ways that a more cautious approach might never have achieved on the same timeline.

The client’s team, working alongside us through this period, developed a relationship with the system - and with us - that would have taken much longer to build any other way. They saw exactly how we worked under pressure. They saw problems handled transparently rather than hidden until they were resolved. They saw a team that stayed in the room when things were difficult rather than retreating to safer ground.

The trust that came from that experience is qualitatively different from the trust that comes from a smooth delivery. Smooth deliveries are professional. Shared difficult experiences are something else - they’re the foundation of a genuinely collaborative relationship where both sides understand each other’s capabilities and character.

There is a version of this story where it ends badly, and I want to be honest that we knew that risk was real. Going live before you’re ready is not a strategy I would recommend as a first resort. The conditions that made it the right call here were specific: a client facing genuine operational pressure, a system that was functional if imperfect, a team capable of rapid response, and a relationship with sufficient trust on both sides to navigate problems transparently when they arose.

For any CEO thinking about AI implementation partners: the question isn’t just whether they can deliver when conditions are ideal. It’s whether they stay in the room when conditions aren’t.

Have you experienced a situation where going live before you were fully ready turned out to be the right call?