Jake Saper on Why Fast Growth Might Be a Trap
There's a failure mode common enough that Jake Saper, general partner at Emergence Capital, gave it a name: mirage product market fit. It looks identical to the real thing, and most founders won't know they have it until it's too late to fix.
This episode of Recall Sessions, a Village Global Podcast series hosted by Somrat Niyogi, follows Emergence's thesis on AI-native services: why software companies that are built to sell tools are structurally unprepared to sell outcomes, why the businesses growing fastest right now may be in the most danger, and the three metrics Jake tells every founder in this category to track.
Key Insights
Mirage product market fit is the biggest risk in AI-native services
A founder raising a Series A can point to fast growth and strong retention and call it product-market fit. In AI-native services, that signal can lie. "That's a world where you are growing quickly and your customers are renewing. You've got good NDR, but you don't actually have product market fit, because the service you're providing is not being done by AI. It is being done by people," Saper says.
The company in that position isn't a successful AI business. It's a traditional services business that raised money on AI-company terms. The growth and retention numbers look identical either way. The only way to tell the difference is to look at who (or what) is doing the work.
Selling a tool and selling an outcome are different businesses
SaaS was built to sell software that helps someone do their job. Saper's framing for the AI era: the product now has to do the job itself. "If you have built your entire organization around the idea that we are building this widget to sell to someone on a per seat basis and help them do their job, and you have to shift to a world where you are building something that does the job, it has huge implications on product development, go to market, certainly on pricing," he says.
A former colleague of Saper's built a two-by-two for what it actually takes to get to outcomes-based pricing: the product needs high autonomy (it acts without constant human input) and high attribution (the outcome can be credited specifically to it). Most SaaS products sold today clear neither bar. Changing the pricing model without changing what gets delivered doesn't solve anything.
The company growing fastest may have the most to lose
Saper is working with a company that grew 4.5x last year, has capital, and is not in trouble by any conventional measure. It's also in the middle of rebuilding what it sells from the ground up, because its buyersmay not exist much longer.
"The absolute worst thing you can do right now is say 'I grew 3x last year and therefore I'm safe,'" Saper says. He argues the opposite is closer to true: a company with strong SaaS-era momentum has more revenue to protect, more culture built around the old model, and more reason to avoid the leap. A business that only grew 30% has less to lose by reinventing itself, and less room to avoid doing so.
AI turned a bad venture category into a good one
Services businesses were historically avoided by venture investors because their costs scale linearly with revenue. Close a new client, hire more people to deliver the work. Gross margins stayed capped around 10 to 30%.
A services business where AI performs the core work with a human layer for judgment and accountability can run at 50 to 60% gross margins. The addressable market is also larger than software's ever was; "The dollar budget you're going after is much larger in AI native services because you're going after the labor spend," he says.
Building AI-first beats buying legacy services businesses and retrofitting them
Saper deliberately named the category "AI-native services" to draw a line against roll-ups: firms that acquire existing services businesses and try to layer AI on top of them afterward. His view is that the sequencing is backwards. A company that starts by acquiring a legacy business starts, by definition, as a service, and hopes to migrate toward AI native later.
The better path, in his experience, is to build the AI product first, with no legacy systems or staff to work around, get customers organically, and only later consider acquisitions to extend into new markets. He points to Hanover Park, a fund administration company that built its own accounting system from scratch rather than buying an existing provider and adapting it. Owning the core system, he argues, is what let the company deliver something a retrofitted legacy business couldn't match.
Three metrics matter more than growth right now
Saper's advice runs counter to the standard venture playbook: grow slower, and get the fundamentals right first. "I would rather see a business grow more slowly but really perfect the AI product... than grow super quickly and figure out the AI later," he says.
The three numbers he tells founders to track:
1. A north-star product metric specific to the service being delivered (for one portfolio company, it's the time a human spends reviewing a contract before it ships)
2. Revenue per employee, which should rise as the AI does more of the work
3. True gross margin, calculated honestly, with both human labor and the token costs of actually delivering the service counted as COGS rather than filed under R&D.
Founders chasing growth over these fundamentals, in his view, are building a worse services business that happens to carry a worse financing structure.
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About the Guest
Jake Saper is a general partner at Emergence Capital, where he has invested for over a decade in companies including Assembled, Unifi, and Ironclad. Emergence was the first institutional investor in Zoom and an early investor in Salesforce, Veeva, Bill.com, and Together AI. He leads the firm's research into AI native services, a business model he argues represents the most significant structural shift in enterprise software since the move to the cloud.
About the Host
Somrat Niyogi is the founder and GP of Recall Capital and a Village Global Network Investor, writing first-checks at the pre-seed and seed stage into B2B SaaS companies. He previously served as General Manager and Head of Business Development at Gusto, with earlier operator roles at Clari, Miso, Stitch, and Salesforce. Together, Village Global and Somrat back early-stage founders across AI, fintech, and B2B SaaS.
