Arvind Jain Argues AI Projects Need Builders Close to Real Work
Arvind Jain endorses pairing technical builders with domain experts and grounding AI initiatives in a company's real workflows, arguing that projects stall when builders are removed from daily friction. He quotes Uber's Agentic Pods approach as the right model.
Original post · 1 min read
Most AI initiatives don't stall for a lack of ambition or model capability, but because the people building the tools or workflows are too far removed from the friction of the actual work.
The breakthrough happens when you combine technical builders, domain experts, and the scattered knowledge, workarounds, context behind the workflow itself.
You can’t redesign the future if you’re too far removed from the friction of the present.
Praveen Neppalli @praveenTweetsAgentic AI adoption is on fire at @Uber, and it's changing the way we build, not just in engineering, but across the entire company.
Today, 99% of our engineers use AI tools. More than 70% of pull requests are attributed to local or cloud agents. And our engineers have built 2,500+ agent skills across the software development lifecycle.
Those numbers are exciting, but they led us to a much bigger question:
How do we bring agentic AI beyond engineering?
Finance. Legal. Operations. Marketing. Customer Support. HR. Procurement.
These functions run on complex workflows that are often manual, h…