Insights
Patterns from building AI products across industries. What works, what doesn't, and why most AI projects fail at the system level — not the code level.
5 articles
5 Questions I Ask Every Client Before We Write a Single Line of Code
The five questions our PM asks every client before engineering starts. They reveal scope, data readiness, and whether the project will succeed.
Dharini S
The Handoff Document We Send After Every Sprint
The exact handoff document Kalvium Labs sends clients after every sprint: five sections, a real example, and the 15-minute rule.
Dharini S
First 48 Hours of an AI Build: The PM Perspective
From 'let's go' to first sprint: what actually happens in the first 48 hours of an AI development project, hour by hour.
Dharini S
200 AI Engineers: What It Means for Delivery Speed
What 200 AI engineers and 6,000 engineering hours per week actually means for your project. How pods work, trade-offs to know, and the honest version.
Dharini S
Why Most AI Products Fail: It's Not a Technology Problem
The pattern behind AI product failures isn't technical. It's structural. Here's the systems-level view from building across startups and enterprises.
Rajesh Kumar