Podium hit $150M ARR in 8 years. Then they rebuilt around AI agents and got to $150M again in 2.5.
Most companies facing disruption choose to "play" at transformation: new frameworks, new titles, same company.
I've been part of a few "transformations" myself, and I learned there's another path: build the new thing outside, or at the edge of your organization, and disrupt your own business before someone else does.
Transforming from the inside is slow. Your competitors don't wait.
Podium didn't transform. They started over.
Would your company dare to disrupt itself?
We built a $150M ARR business twice.
The first time took 8 years. The second took 2.5.
Today, Podium crossed $150M in AI annual recurring revenue.
Three years ago, we already had a great software business. Well over $100M in revenue, tens of thousands of customers, and a product we'd spent nearly a decade building.
And we decided to start over.
The business was performing well. But we believed AI was going to fundamentally change the software industry and make much of traditional software obsolete.
As a founder, you pour your life into what you're building. An insane amount of time, sacrifice, and effort. The hard part is not getting too attached to it.
When we started building our first AI agents, we had to confront the possibility that much of what we'd built might not be that valuable in the future. That's a tough pill to swallow.
But we also realized those same 10 years had put us in a unique position to take advantage of what AI could do for our customers.
Instead of protecting what we'd spent a decade building, we decided to bet the future of the company on AI employees that actually do the work for our customers.
We massively underestimated what we'd signed up for.
We ended up building entirely new operating systems for the industries we serve, from the AI agents all the way down to the systems of record. Now customers run their entire businesses on Podium.
Reinventing our product wasn't even the hardest part. We had to reinvent how the entire company operated.
When you've been running a company for over a decade, the operational inertia is incredibly powerful. We had to rethink how we build products, how we sell, how we serve customers, and how we run the business.
We effectively started a second startup inside an already successful company. And we're still at the very beginning.
Today, we have 20,000 AI agents working for our customers. They've helped generate more than $13 billion in revenue for those businesses. And we're barely scratching the surface of what AI will be able to do for them.
And we've done all of this while becoming profitable and generating free cash flow. We're building Podium to be around for decades.
Huge credit to our team for having the guts to make this bet and the ability to actually pull it off. We still have a long way to go and tons of problems to solve, but it's so damn fun to be winning when the opportunity ahead is this big.
In the age of AI, you can either disrupt your own company or wait for somebody else to do it.
I'd rather do it ourselves.
Vibe coding isn't the problem. Unreviewed code is.
A friend asked me to build him an app (with payments, among other things). It's live in production, built with Claude Code. Before trusting it, I had Codex audit the entire codebase. Then I had a second model try to break it (Codex adversarial review).
It found real holes: a removed admin who could still call the backend. Loose storage rules.
Writing code is cheap now. Reviewing it is the job. And knowing what to review is the moat.
Who reviews your AI's code?
@liorpesoa For example, handling the time and date when the clocks change for daylight saving time in Chile. Claude hadn't included this in his plan, but Codex added it. And many others
Your agile team can be incredibly efficient and still ship garbage.
I've seen it firsthand:
→ 4 months to build push notifications. An email would have solved it in days.
→ 3 months building a shopping cart to sell a ~$5 product to 20 customers.
Velocity: great. Impact: zero.
Frameworks don't protect you from building the wrong thing. Hypotheses and real customers do.
I've shipped a few of these failures myself.
What's the most "efficient" waste you've seen?
Hot take: the MVP as we knew it is becoming obsolete.
It was invented when building was expensive. With AI, you can build an entire product in days, not months.
Building isn't the expensive part anymore. Learning what customers actually want is. We will probably keep building products in an iterative, incremental way.
@ericries, time for Lean Startup 2.0? 👀
1 guerra necesita 2 bandos y acá somos 1 solo pueblo que quiere igualdad 🇨🇱. No queremos + violencia. Necesitanos q autoridades digan q van a cambiar para resolver los problemas sociales. hablan de delitos y no de soluciones al problema de fondo 🤷♂️🤷♂️
#chiledesperto#nomasabusos