Perspectives / By Swapnil Upganlawar
How AI changes
the decisions we make.
How AI changes what we build, how we lead, and how organizations work.
01 / Leadership & Organizations
How should we lead?
Changing management roles, team design, accountability, and adoption.
Explore leadership →02 / AI Strategy & Economics
What makes AI worth doing?
Investment decisions, costs, and the difference between activity and useful outcomes.
Read about the economics →03 / Engineering Judgment
What should we trust?
Reliability, evaluation, and the tradeoffs behind putting AI into production.
Explore model evaluation →All perspectives
The AI score went up. What actually improved?
Four October studies show why a better AI score isn't always a reason to launch. Here's what I'd check about the measurement first.
By Swapnil Upganlawar
100 operations. 20 lost responses. What did the retries create?
A reproducible fault-injection experiment: both callers acknowledged 100 operations, but ordinary retries left 120 writes. Stable operation keys kept the ledger at 100.
By Swapnil Upganlawar
The cheapest AI attempt is not always the cheapest useful result
Compare the cost of acceptable outcomes, including failed attempts, retries, tools, and human review, with the task cost calculator.
By Swapnil Upganlawar
AI adoption starts with the customer problem
Reflections from the technology panel at WEMBA’s 50th anniversary: working backwards from customers, getting the data right, and making adoption a leadership responsibility.
By Swapnil Upganlawar
When faster AI work meets the organization
How to examine handoffs, architecture, review capacity, and incentives before turning task-level AI gains into claims about business performance.
By Swapnil Upganlawar
What changes when managers lead teams using AI?
A practical look at delegation, coaching, trust, and accountability as generative AI changes how a team gets work done.
By Swapnil Upganlawar
What changes when AI can do the work?
My perspective on the shift from generating answers to delegating work—and what it means for products, engineering teams, and business decisions.
By Swapnil Upganlawar
How to compare AI models for your application
Start with a real task and a clear definition of success. A useful comparison ends with a decision you can explain.
By Swapnil Upganlawar
The cost of a completed task
Token prices are only the beginning. Count the tools, retries, and failed attempts behind a useful result.
By Swapnil Upganlawar
Reading AI regulation as a builder
Start with jurisdiction, your role, and the intended use. Learn to separate binding rules, proposals, and voluntary guidance.
By Swapnil Upganlawar
When an agent retries a successful action
A missing response does not mean an action failed. Follow one request all the way to two tickets—and the repair that prevents it.
By Swapnil Upganlawar
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