👋 Hey — Egemen here.
A founder I know shipped an AI feature that does the work of three support reps.
Then he kept charging the same price per seat as before.
He built something three times more valuable, and his revenue did not move.
That mistake is everywhere right now, and the data on it just got loud.
Here’s a snapshot of what’s on the menu today:
💡 Spotlight: 200+ ways to profit from AI
🧠 Deep-Dive: Per-seat pricing is dying
🗺️ Method: Change your pricing without blowing up revenue
☝️ Scaled This Past Week: Scotch
💡 Spotlight
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🧠 Deep-Dive: Per-seat pricing is dying
For ten years, SaaS pricing was simple.
Charge per seat. More users, more money.
Clean, predictable, and it worked. AI just broke it.
Here is the problem in one line. If your software replaces human work, every seat your customer removes is revenue you remove from yourself.
The founder I mentioned shipped an AI agent that let a client cut support from 20 people down to 6. Great product but he got punished for being good. Pure per-seat pricing dropped from 21 percent of SaaS companies to 15 percent in a single year, while hybrid models, a base fee plus usage, jumped from 27 percent to 41 percent.
Bessemer said it flat out in their AI pricing playbook. AI-native companies are walking away from seats and moving to usage and outcome pricing that tracks the value actually delivered.
The smart money already moved. Intercom charges 99 cents for every support ticket its AI actually resolves. HubSpot dropped its version to 50 cents in April. You pay nothing when the AI fails, and buyers love that because their risk drops to almost zero.
There is a second reason seats are dying that nobody talked about for years. AI costs real money to run. Every query burns compute. Old SaaS ran 80 to 90 percent gross margins. AI products run 50 to 60. (Source: Bessemer.) If one heavy user on a flat seat hammers your model all day, that seat can cost you more than they pay. Per-seat does not just cap your upside anymore, it can quietly torch your margins.
👉 If your product does work a human used to do, stop selling seats. Pick the one outcome your customer actually pays you to create, and charge for that. If you are not sure which metric yet, go hybrid.
A small base fee plus usage protects your margin today and lets you find the real price while you learn.
🗺️ Method: Change your pricing without blowing up revenue
Changing pricing is scary because it touches money you can already count on. Here is how to move without setting your ARR on fire.
First, pick your unit. The right one depends on what you sell.
If you sell AI that resolves tickets or completes tasks, charge per outcome.
If you sell an API or a dev tool, charge for usage.
If you sell something humans still drive by hand, keep a seat and add usage on top.
If you genuinely do not know, go hybrid. A base fee plus a usage line is the safest bridge, and it is what most winning AI companies use while they figure it out.
Then move without breaking trust. 3 rules:
Grandfather your current customers. Put new pricing on new logos first, prove it works, then migrate everyone else with real warning. Surprise pricing changes burn goodwill faster than almost anything.
Bill on a proxy you can measure. Real outcomes are hard to track, so pick a near-outcome metric both sides trust. A resolved ticket is easier to agree on than customer happiness.
Run a pilot tied to one number. For bigger accounts, sell a short paid pilot against a single metric, like cutting resolution time by 30 percent. Hit it, and the pilot rolls into a contract anchored to a result instead of a guess.
👉Do not rip out per-seat overnight. Add a usage line on top of your current plan this quarter, watch what your heaviest users actually consume, and let that data tell you where the real price lives. You learn this by billing, not by guessing in a spreadsheet.
Quick one. The data in today's deep-dive came from Growth Unhinged, Kyle Poyar's newsletter on pricing and go-to-market.
Pricing is the most under-tested lever in most startups, and this is the one to read on it. Kyle publishes the actual numbers. What models are working, how fast companies are switching, where willingness to pay is moving. It is the closest thing to a live feed on how B2B software gets priced.
I do not agree with every take in it, and I still read every issue. Worth your inbox.
☝️ Scaled This Past Week: Scotch
Scotch just raised a $20 million Series A, led by VMG Partners, with First Round Capital and Lerer Hippeau along for it.
Scotch builds an AI-native operating system for liquor stores. Point of sale, payments, inventory, and the back-office mess of state-by-state alcohol rules, all in one place.
Here is the lesson worth stealing. The giant AI rounds grab the headlines, but some of the best businesses right now are unglamorous verticals nobody else wants to touch. Scotch is not chasing AGI.
It uses AI to delete entire weeks of manual invoice reconciliation and compliance work, then charges for the time it hands back.
Pick a real industry with real pain, build the operating system for it, and you have something no horizontal AI tool will ever bother to copy.