Insights
Applied research from delivery, staffing, and AI engagements.
Specific, technical write-ups on problems we've actually worked through: how they showed up, what we did about them, and what it cost.
Staffing
Workforce planning needs a new question
Headcount planning built around 'how many engineers do we need' is the wrong question when capacity depends on how well a team uses AI tooling.
AI & DataAI doesn't eliminate architecture: it raises the cost of getting it wrong
A model can generate a plausible implementation for almost any component. It has no opinion on whether that component belongs in the architecture at all.
AI & DataDon't ask whether AI is accurate enough
"Is the model accurate enough" is usually the wrong question: accurate enough for what, and what happens when it's wrong?
GovernanceTechnology leaders need to become workflow architects
As AI tooling absorbs more individual tasks, a leader's highest-value work shifts to designing the workflow tools and people operate inside of.