Solvimon

OpenAI and Anthropic ship new products every few weeks. And every update is steering the product roadmap for the SaaS companies downstream. Here's the problem: Most teams can't move that fast — not because they don't know what to charge, but because changing pricing feels slow, risky, and hard to reverse. That's why we're running an office-hours session with two people who live on opposite ends of that problem: ▶ Ulrik Lehrskov-Schmidt (WillingnessToPay.com) on the strategy side, and ▶ Arnon Shimoni (Solvimon) on the technical side A few things we're going to unpack: → How do you read willingness to pay fast enough to actually act on it? → What used to take months of pricing deliberation that should now ship in minutes? → When does building your own billing stack make sense? → How are teams pricing AI products when "usage" itself keeps changing definition? We'll collect questions in advance, then shift to open Q&A. 📅 Wed August 12 | 11:00 AM EST Small group, approval required (this isn't a webinar.) If you're wrestling with a pricing change right now — comment "join" and I'll send the details. 👍

The current AI pricing was always going to go away because it just doesn't make sense Microsoft canceled internal Claude Code licenses this week. Uber blew its 2026 AI budget in four months and GitHub is dropping flat-rate plans across its products You may see "the AI subsidy era is ending" which is a poliate way of saying that every B2B company shipped AI features into every tier of their product on a bet that inference costs would keep falling. They didn't, because the appetite grows. Induced demand and all that. Anthropic's CFO testified under oath this March that the company spent $10 billion on compute and made $5 billion in revenue. The labs are underwater on inference. Prices keep going up because they have to. Memory is getting more expensive, GPUs are getting 400% more expensive. Companies that sold flat-rate AI-everywhere products are now sitting on a margin problem they architected themselves into and what changes from here is what gets shipped... the product question shifts from "where can we add AI?" to "which use cases earn the inference cost they burn?" Split the field - your pricing can move with cost (per-action, credits, hybrid) so that you get to keep building. If you are locked into per-seat you pick between margin collapse and stripping AI out of your cheaper tiers. Neither one of that looks fun.

Getting usage-based pricing right is four different decisions in a trenchcoat you gotta structure true-ups, true-downs, commits, and obviously the base usage - but picking the right metric sits at the core of everything. pick the wrong one, and you end up alienating your users SO QUICKLY. getting the balance between the value you provide and the cost is crucial - so i put together a little guide on how to think about UBP design

Thinking about hybrid pricing but not sure what to meter? I agree - "API calls" is a lazy infrastructure metric that usually carries no value to the customer. Anyways, I've got you covered with a guide - here's what to think about on your path! https://lnkd.in/evu5KrvD

It's now plain to see how AI buys you margin and time - so that you can invest in that thing that differentiates you with your customers. That means I'm also happy to see the AI doomerism (AI IS TAKING OUR JOBS) finally die down a bit and become a bit more realistic. Lots and lots of open engineers roles in companies also doing AI agents because there is still very much a need for talent. 2nd order thinking is required: yes, humans may be doing less of the menial "put this in a google sheet" work, but that's not a job still. Agents automate tasks and thoes tasks then need to be steered, reviewed, and executed on. To me that still sounds like a job. Companies will continue to automate what they can, free up time and money, and move to the next thing that matters most.

Announcing headless monetization with Solvimon. While lots of billing systems were built for humans operating a dashboards, that meant pricing changes and usage configurations had to be checked in a browser, by a person. That's changing, with agents now a first-class citizen of Solvimon. Every billing operation in Solvimon is now accessible via API, MCP, or CLI. Engineers, your agents, and most IDEs can now configure pricing, check entitlements, and meter usage without touching a dashboard. * Our MCP server makes actual changes to your billing configuration - it isn't just read-only. * Our CLI that scaffolds your entire monetization layer in one command. SDKs in every major language. A billing system that the next generation of AI agents can discover, evaluate, and integrate without a human in the loop. We built Solvimon so that billing is never the bottleneck, and as the monetization layer becomes the core, everything else gets built on top of it. https://lnkd.in/em7rqTTJ