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.
14 articles
Scope Creep in AI Projects: How I Manage It
How I handle mid-sprint additions in AI development without damaging client relationships. Includes the 3-question script and sprint structure I rely on.
Dharini S
How a Finished Project Turned Into a Second One
What actually happens after a project closes, why some clients come back, and what delivery trust looks like in practice.
Dharini S
Discovery Call Checklist: Scoping AI Projects in 30 Min
How our PM structures a 30-minute discovery call for AI projects, what questions are unique to AI, and what the brief looks like after.
Dharini S
SEO for Therapists: Your Expertise Should Rank on Google
Most therapists rent their Google presence through Psychology Today. Here's how owned SEO works and why clinical expertise is the differentiator.
Abraham Jeron
SEO for Doctors: How We Got a Practice to #2 on Google
How we took a women's health practice from zero Google presence to 5,000 weekly impressions and 109 consultation clicks in 5 weeks. No ad spend.
Dharini S
Conversation Intelligence Software in 2026: Build vs Buy
Gong, Chorus, Observe.ai, or a custom build. How to decide which conversation intelligence software fits your team, from someone who's built it.
Abraham Jeron
How We Run Weekly Demos (And Why Clients Love Them)
The 30-minute weekly demo format we use for every AI project: structure, prep, and why live software beats status updates every time.
Dharini S
What Clients Underestimate About AI Product Costs
Token bills, API charges, and the hidden costs that surprise first-time AI builders. A PM's breakdown of what shows up on the invoice at scale.
Dharini S
Why I Don't Commit to Timelines on New Requirements
Why our PM refuses to give same-day estimates on unfamiliar AI work, the 24-hour analysis she runs instead, and how to keep client trust during the wait.
Dharini S
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