What enterprise AI actually needs
A podcast conversation about why enterprise AI has to start from real workflows, controls, and operating constraints instead of abstract transformation talk.
Gaurav
I bring 15+ years of experience across product engineering, entrepreneurship, and enterprise architecture. Since 2025, I have been focused on designing, evaluating, and operationalising AI agents in real-world systems. I work with teams moving beyond demos into production.
Latest posts
Your Buyers Want AI-Era Pricing. You Still Have Pre-AI Costs.
Mid-sized services firms need to redesign their operating model before the market forces them to do it under margin pressure.
How I Checked My Mac After the axios npm Compromise
A practical incident-response walkthrough: exact-version scanning, temp-directory false positives, and the guardrails I added for npm and uv.
Why agents fail and how to debug them?
If you are building agents seriously, you should at least know how to diagnose them.
The Hidden Reason Most AI Projects Fail: Incorrect Caching
Why prompt caching is critical to your enterprise AI adoption
From Serverless Functions to Durable Agents
Why agent systems outgrow stateless request-response functions and push teams toward durable execution, memory, and long-lived workflows.
AI Case Study: Standardizing Logging Across a Large C# Codebase
Not every problem needs an autonomous agent. Sometimes orchestration is all you need.