AI Won’t Close The Ownership Gap In Software Delivery

Steve Taplin is CEO & founder of Sonatafy Technology, a software consulting & engineering firm focused on delivery, quality & accountability

​I have founded more than 30 companies over the past 25 years, and 20 of them failed. One lesson keeps showing up: companies are usually quicker to add people, tools and activity than to clarify who owns the result.

Generative AI is creating another version of that problem. I know because I have made the same mistake myself.

The Teams Were Busy, And The Results Were Not There

Inside my own company, I have run into what looked like a capacity problem more than once. The backlog was full. Tickets were moving. Releases were going out. Everyone looked busy, and the natural conclusion was that we needed more engineers.

Before approving more hires, I started asking questions I should have asked earlier: What was each team actually responsible for improving? Who owned that result from beginning to end? How would we know whether the software we released improved anything?

The answers were much less clear than the amount of activity would have suggested. That was when I started thinking about the problem as an ownership gap. Plenty of people are doing the work, but no one person clearly owns the outcome all the way through. On top of that, parts of our operating model were worsening the problem.

Infrastructure was one example. Only a couple of our teams could stand up environments, so everybody else had to wait on them before work could move. We reworked it so that more teams could build, test and deploy on their own rather than everything going through the same few people.

We had another problem between product and engineering. AI made it easy to create prototypes and move ideas forward quickly, but that also meant some work was reaching engineers before it had been properly vetted. In some cases, developers were still trying to figure out what the team actually wanted after the work had already reached them.