Know your surface areas
Before you implement an AI-SDLC, understand how your people actually work. The technology gets easier with the right lens.
Surface areas of work are super important to understand when it comes to implementing an AI-SDLC.
As the rotation onto AI becomes standard, it can sometimes overlook how people actually operate.
It sounds so simple
Understanding:
- your testing strategy
- where work comes from
- where work is done
- how you qualify success
- who contributes (not just engineering)
- even why they contribute
That translates into a clear direction on how value is built.
Why it matters
It could make the difference in how you implement hooks, change how you govern marketplaces, and even shift adoption from being a number to collective innovation.
The technology gets easier with the right lens.