Manjeet Singh lives where AI hype meets real enterprise reality. He is the Senior Director of Product Management at Salesforce AI and Agentforce, and previously led product teams at Iron Mountain and ServiceNow. He spends his days shipping AI products that millions of people actually use.

In this episode, Manjeet sits down with Ravi Belani to talk about what is really working in enterprise AI adoption, and where a lot of teams are still stuck in POC land.

They explore:

• The real state of enterprise AI and agentic adoption in 2025

• Why so many AI projects stall at proof of concept

• Where agents are already driving real KPIs, from software development to customer support

• How to tell if an AI opportunity is likely to deliver real ROI for an enterprise

• Why constrained, well defined workflows win first

• Vertical vs horizontal AI, and how to build more than “just an LLM wrapper”

• Why regulated and high cost of failure domains can be great markets for startups

• The missing “toolchain” for agents, from testing and evals to observability and tracing

• How to think about moats, domain expertise, and speed in the AI platform era

• Why Manjeet is excited about the intersection of AI, healthcare, and preventative fitness

If you are building, buying, or investing in enterprise AI, this conversation will give you a grounded view of what works, what does not, and where the next opportunities are likely to appear.

Marcelo Calbucci has been building tech for over 30 years. He’s a serial entrepreneur, multi patent holder, former engineering leader at Microsoft and Amazon, and someone known for having bold, contrarian takes on where AI is actually heading.

In this episode, Marcelo sits down with Ravi Belani to challenge some of the biggest assumptions people have about AI right now.

They dig into:

• Why layoffs and job freezes might have nothing to do with AI

• Why AI isn’t replacing software engineers anytime soon

• Where AI is being massively overused

• The areas where AI is actually underused and full of opportunity

• Why founders need to stop outsourcing strategy to LLMs

• How to use AI to disconfirm your ideas instead of chasing confirmation bias

• Why the next big wave of opportunities may come from “multiplayer AI”

• What roles AI is likely to replace, and which roles will remain essential

• Why adaptability will matter more than anything else in the next decade

Marcelo also shares which startup opportunities he’d pursue today, how he thinks teams will collaborate with AI agents in the future, and the one piece of advice he’d give founders in 6 words: We’re entering the world of adaptability.

If you want fresh, honest, and thought provoking perspectives on AI and the future of work, this conversation is a must watch.

Amr Awadallah has seen multiple waves of hype in tech and helped build real companies through it. He co founded Cloudera, took it public, watched it get acquired for 5.3 billion dollars, and is now building Vectara, a platform that helps enterprises ship AI apps that are accurate, safe and actually usable in production.

In this episode, Amr joins Alchemist Accelerator founder and CEO Ravi Belani to unpack a striking finding from an MIT report. An estimated 95 percent of enterprise AI projects are failing.

They dig into why that is happening and what to do differently:

• The real reasons enterprise AI fails in production
  

• Why “go do AI” from the board is not a strategy
  

• How fake exploration budgets create fake success stories
  

• The 3 whys every founder and buyer should test
  

• • Why do anything

  • Why now

  • Why this vendor
    

• How to tell a real business need from AI theater
  

• Why passion for the problem, not the tech, drives grit
  

• How cofounders, early hires and investors make or break your company
  

• What Vectara is building as an “operating system” for AI agents
  

• Why context, security, accuracy and cost control matter more than demos
  

Amr also shares raw, founder level advice. From firing fast in the first 50 hires, to choosing investors who have actually been in the trenches, to his simple test for whether you really love the problem you are working on.

If you care about building AI products that survive past the pilot stage, this conversation is a must listen.