Amit Godbole
Chief Product Officer
Bengaluru, India
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Amit Godbole is a sharp product leader and pricing strategist who helps SaaS, fintech, and e-commerce teams turn strategy into serious business growth. With 15 years of global experience, he has launched products, scaled teams, and built pricing models that drive both adoption and revenue.
He operates at the intersection of product and profit, helping companies treat pricing as a growth engine rather than an afterthought. Amit also leads ProductTank across APAC, building one of the most active product communities in the world.
He brings clear thinking, fast execution, and a belief that pricing should be your boldest product decision.
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Why AI Fails First in Pricing and Distribution
Agentic coding delivers impressive local gains. Agents refactor faster, generate cleaner code, and close tickets that used to take days. At scale, however, teams discover a different problem: systems remain technically correct while business behavior quietly degrades.
Pricing and distribution are where this failure shows up first.
In this session, I share hands-on experience applying agentic coding to monetization logic in large B2B systems. Agents performed well at refactoring rules, reducing duplication, and improving test coverage. Yet subtle semantic drift emerged: temporary discounts hardened into entitlements, regional constraints leaked across markets, and experiments became policy. Nothing failed loudly. Tests passed. Revenue numbers looked plausible. The system had simply stopped behaving as intended.
The root cause was not agent quality. It was missing context.
This talk explores why pricing and distribution are uniquely vulnerable under agentic coding and what actually works to scale AI-powered development safely in these domains. We will look at how weak domain boundaries give agents too much freedom, why feedback loops fail to catch semantic errors, and how to design context that constrains agents without killing autonomy.
You will leave with practical patterns for context engineering in agentic workflows, including separating pricing intent from execution, defining agent-safe surfaces, and building feedback loops that detect meaning loss rather than just correctness. This is not a tools talk. It is about making agentic coding reliable in the places where it matters most.
Why Agentic Coding Breaks First in Pricing and Distribution
Agentic coding delivers impressive local gains. Agents refactor faster, generate cleaner code, and close tickets that used to take days. At scale, however, teams discover a different problem: systems remain technically correct while business behavior quietly degrades.
Pricing and distribution are where this failure shows up first.
In this session, I share hands-on experience applying agentic coding to monetization logic in large B2B systems. Agents performed well at refactoring rules, reducing duplication, and improving test coverage. Yet subtle semantic drift emerged: temporary discounts hardened into entitlements, regional constraints leaked across markets, and experiments became policy. Nothing failed loudly. Tests passed. Revenue numbers looked plausible. The system had simply stopped behaving as intended.
The root cause was not agent quality. It was missing context.
This talk explores why pricing and distribution are uniquely vulnerable under agentic coding and what actually works to scale AI-powered development safely in these domains. We will look at how weak domain boundaries give agents too much freedom, why feedback loops fail to catch semantic errors, and how to design context that constrains agents without killing autonomy.
Building AI products
Building Products that involve ai agent. Focus on copilot and Microsoft Power Platform usage
What if Pridicng was your best Product Feature
Pricing isn’t just about revenue; it’s your product’s most visible, most emotional, and often most misunderstood feature.
In this session, we’ll challenge the traditional silos between product, finance, and sales by rethinking pricing as part of the product experience itself. Drawing from real-world cases across SaaS, fintech, and e-commerce, we’ll explore how strategic pricing decisions can outperform even the most ambitious feature releases.
You’ll learn:
1. How to treat pricing as a product surface and make it testable, iterative, and UX-aware
2. When to rethink your monetisation model (before your market does it for you)
3. Practical ways to align product, GTM, and finance on pricing decisions
4. Why your pricing page deserves as much love as your homepage
This talk is for product leaders who want to drive growth not just by building more, but by communicating value more effectively, especially if you’ve ever launched a great feature that no one paid for.
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