Technical Debt Is Really Decision Debt

Note: The following contributions are personal impulses from Max Eckel. They represent individual reflections and are intended to stimulate discussion and further thought.

Technical debt is not just code debt. It is old business decisions becoming harder and harder to change. Conduct ’s new $60M Series A is a useful reminder for every business student who thinks tech debt is only for engineers.

Conduct, co-founded by WHU alum Jan Philipp Haas with Philipp Hoefer and Henry Thompson, just raised $60M from Index Ventures, ICONIQ, SAP, Creandum, Lucid Capital, (Srećko ) and BOOOM. The company helps large enterprises understand and change customized software systems: custom code, configurations, integrations, dependencies, and business logic.

That sounds abstract, but the customer list makes it concrete: Fraport, Daimler Truck, Heidelberg Materials, DHL. Conduct is also a strategic AI partner for transformation with SAP Cloud ERP applications.

The reason this matters is simple. Large companies often run on systems customized for decades: pricing rules, approval chains, procurement logic, manufacturing workflows, integrations. Every customization probably made sense at the time, but the logic often stays buried long after the business has moved on.

Over time, this becomes a sediment layer of old decisions. And suddenly a simple business decision is no longer simple: change pricing, open a new factory, migrate to SAP Cloud ERP, respond to regulation, or let AI agents work inside the business. The bottleneck is often that nobody fully knows what breaks if one field changes. 

Conduct is going into the messy core of enterprise reality and making old business logic legible again. They make these legacy enterprise software systems as agile as vibe coded software, to paraphrase JP in a chat with Paula. For aspiring founders and business students, the lesson is easy to underestimate:

Tech debt is not something only tech people should care about. Most technical debt starts as a business shortcut.

“We just need this custom workflow for one customer.”
“We can fix the data structure later.”
“Let’s ship it manually first and clean it up when we scale.”

All of these decisions can be rational. Startups need shortcuts. Large companies need pragmatism. But shortcuts compound. At some point, the company is no longer just carrying technical debt. It is carrying decision debt. Old trade-offs become invisible, temporary fixes become infrastructure, and a smart exception becomes a hidden dependency.

That is why business people should care. You don't need to review the codebase, but you should understand the long-term cost of the shortcuts you ask for. AI makes this even more important because an agent can only act on a system it understands. So the next enterprise AI bottleneck may not be model intelligence. It may be legibility.

Congrats to JP, Philipp, Henry, and the whole Conduct team.

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