What’s Inside
SaaS hits its “fast fashion” era as moats collapse
Gainsight pivots from selling software to selling outcomes
Jevons’ Paradox: why AI creates more work, not less
I first met Chuck Ganapathi more than a decade ago. It was 2014, and Satish Dharmaraj of Redpoint Ventures introduced us at an event. At the time, Ganapathi was building Tech.ai, and I was leading a different publication covering venture capital.
Ganapathi and I talked about his startup, and like a lot of those conversations at events, we connected on LinkedIn afterward and I filed it away in memory as a meeting with a founder who I may reconnect with later.
Fast forward to today, and Ganapathi just stepped into the CEO role at Gainsight, succeeding Nick Mehta, who spent 13 years building the company into what many call the godfather of the customer success movement.
Because of our previous meeting and because I am curious how Gainsight will adapt amid agentic tech, I jumped at the chance to hear how Ganapathi envisions the next chapter for the company and for SaaS itself.
What followed was a pair of Zoom conversations last week, in which we discussed everything from Sarah Tavel’s Sell Work, Not Software blog post to the looming “fast fashion” collapse of SaaS, to an 1865 paradox about coal burning that may explain more about AI than the hype cycles ever will.
Sam Altman called it the “fast fashion era” of SaaS, and Ganapathi doesn’t shy away from the phrase. His point: the old software moat is collapsing.
Not long ago, building enterprise software required a team of engineers, years of work and millions of venture dollars. Today, a solo founder can log into Cursor or Windsurf on a Friday night and ship a minimum viable product by Sunday. Klarna recently went further, canceling its Salesforce and building its own internal CRM because it was faster and cheaper.
That ease is thrilling and dangerous. Thrilling because barriers to entry are lower than ever. And as I often argue, agentic AI and automation are lowering the cost and ease of startup formation even more dramatically than AWS and cloud computing ever did.
It’s dangerous because customer loyalty evaporates. If the next shiny app is cheaper and good enough, switching costs are next to nothing.
“Retention is going to become existential,” Ganapathi told me. “Gross retained revenue is under attack. Boards are already seeing it.”
This is where Sarah Tavel’s framework comes in. In her post, from nearly two years ago, she urged AI startups to stop selling tools and start selling the work itself. Instead of charging per seat, price against the outcome.
Ganapathi echoed this idea, noting that traditional software vendors capture only a fraction of the value they create. A tool might make each member of a team more productive, but the vendor only charges a license fee. By contrast, an AI agent that can actually do the work can justify capturing a much larger share of the value.
“It’s the difference between selling a tool that helps a human work faster and delivering the work itself,” he said. “The economics change dramatically.”
That’s why Gainsight is moving from being a vendor of SaaS to RaaS, Retention-as-a-Service. With its Atlas AI agents, the company can replicate what a human CSM might do for a million-dollar account and scale that behavior down to the long tail of $2,000-a-year customers.
The outcome delivered is retention.
That shift also explains why Ganapathi is drawn to Jevons’ Paradox, an idea published in 1865. Economist William Stanley Jevons observed that more efficient steam engines didn’t reduce coal consumption, they increased it. As coal became cheaper to use, demand soared.
We may be seeing the same dynamic play out now for AI and agentic tech, which is improving efficiency and reducing costs, but is also expanding where and how software gets used.
“The naive interpretation is that agents will replace customer success managers,” Ganapathi said. “But Jevons would say: no, the new Technology will create use cases you never thought possible before. Work expands.”
In practice, agents aren’t taking away high-touch accounts; they’re unlocking the long tail of customers who previously got little to no attention. What looked like a threat to jobs becomes, paradoxically, an expansion of work.
It doesn’t solve every concern. Ganapathi acknowledged that there’s a real risk around entry-level roles, such as junior engineers. But he’s convinced that more opportunity will be unlocked than destroyed.
In other words, making something more efficient often leads to it being used in more places, not fewer, a paradox first observed with coal in 19th century England and just as relevant in the AI era.
For Ganapathi, the agentic shift isn’t just another software cycle. Having lived through mainframe, client-server, cloud and mobile, he believes this one is bigger than all of them combined.
And it’s arriving just as he takes the reins at Gainsight.
Mehta’s Legacy was to build the customer success profession. Ganapathi’s challenge will be leading it into an era where retention is a survival strategy and where selling outcomes, not software, becomes the norm.
As I finished our second call, I told him I wished I had recorded this as a podcast. He laughed, but I wasn’t wrong. The conversation was that educational.
For me, the debate over fast fashion and whether it’s real isn’t the most urgent question. It’s this: as AI agents change what we think is possible and retention becomes the new battleground, will tomorrow’s market leaders be the ones that simply automate work, or the ones — like Gainsight — redefining what productive work actually means?
As Ganapathi leans into his new role, the next era of SaaS and AI will be all about who thrives amid the disruption taking place.
Feature art generated in collaboration with ChatGPT.
