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AI is making engineering faster. So why is enterprise ROI still so hard to prove?
Enterprises are investing heavily in AI. Engineering teams are shipping more. But more output doesn't necessarily mean more business value. Rework, inconsistency, review overhead, & production risk can quietly eat into those gains.
So where does the value get lost?
General-purpose AI is increasingly capable, but enterprise engineering isn't just about generating code.
It requires context: your architecture, systems, standards, dependencies, workflows, & business priorities.
During SF Tech Week, CTOs & senior engineering leaders will come together for a closed-room discussion about where AI creates value, where it gets lost, & how to measure the difference.
We call that gap drift: the distance between what the business sets out to build, what engineering actually produces, & what ultimately creates value.
What we'll cover
Where is the ROI actually coming from?
Where does AI-driven productivity get lost?
Are general-purpose tools enough, or does enterprise context really matter?
How do you measure drift & the hidden cost of engineering?
What changes as AI agents become more autonomous?
No panels. No pitches. No product demos.
Who is in the room
Just senior technology leaders comparing notes on what they're actually measuring, testing, & changing, & whether their AI investments are really paying off.
CTOs, VPs & Heads of Engineering, AI Platform & Developer Productivity leaders, Enterprise Architects, Platform Engineering, & AI Governance & Security leaders.
Request a seat below. Part of #SFTechWeek.
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