Came across this HubSpot piece on credit-based pricing. The article was published yesterday - suspiciously timely after last night's conversation on credits and transparency :-) @Rob Litterst , were you behind this one? https://blog.hubspot.com/website/why-ai-usage-based-pricing Found it quite insightful. I particularly liked the screenshots showing in-product cost labels at the point of action. HubSpot uses a credit badge on the data agent, whereas Airtable gives you a breakdown of what exactly your credits buy you. It's the difference between getting a surprise bill at the end of the cycle and watching the meter tick as you are using the product (so that you know when to stop spending). Great for building trust.

I talked to an engineering manager today about monitoring issues in production. He mentioned an open-source platform his company uses to increase reliability: Temporal. I went to check it out and realised how hugely popular it's become. Long story short, it lets you define workflows that automatically survive crashes, restarts, and network failures: without you writing retry or recovery logic yourself. It made me realise how easy it is to take reliability for granted when dealing with pricing / billing complexities. Every major billing platform - Stripe, Chargebee, Metronome, Polar etc. is reliable on its own. None of them, however, owns the layer between your CRM, your usage events, invoices, and your warehouse in a way that survives failed event delivery, events arriving out of order, and missed reconciliations. That layer is yours to build. If you or your team have never explicitly built this layer, it's most likely not there. This is most likely quietly costing you money in ways your dashboard won't show. PS: You don't have to use Temporal. Inngest, Restate, AWS Step Functions, Kafka, or even a well-behaved queue with idempotency keys can get you there. The pattern matters more than the tool. PPS: This is the work I do. Happy to nerd out in the comments or DMs.

Hi everyone, great to be here. I'm Tomas, an independent billing advisor focused on helping SaaS companies turn pricing ideas into repeatable billing systems. My work sits in the layer that comes after pricing strategy, and that's where things can get messy :-) - subscriptions + usage-based hybrids - plan changes, proration, and edge cases - global sales (MoR vs direct payments) - making sure the billing setup doesn't break product experience or reporting I've spent the last few years working heavily with Stripe and similar platforms, helping teams implement flexible pricing without locking themselves into brittle setups. More recently, I've been building Billing Atlas – a structured advisory service that helps SaaS teams make and execute billing decisions with clarity. I joined this community because pricing and billing are tightly connected, but often discussed separately. I'm particularly interested in how pricing decisions hold up once they hit real systems and customer expectations. Happy to share practical insights from the implementation side, compare notes, or help validate ideas when useful. Looking forward to learning from all of you.

For the past month, a handful of users have been beta testing PricingSaaS Pulse. The feedback has completely reshaped how I think about the Pulse product. When @John Kotowski and I started PricingSaaS, the goal was to make pricing expertise accessible to the average product team. We'd both witnessed our own versions of pricing paralysis. As a consultant, I watched clients struggle to drive consensus. As a Chief Product Officer, John lived the pain firsthand. Often, when teams are staring down a new launch, they freeze. Not because the team isn't smart. Because there are just so many options, and its hard to cut through the noise and figure out what makes the most sense. Pulse is solving that. The clearest pattern from beta: Pulse works as a pricing intelligence layer that plugs in alongside a team's own internal context. The combination of internal context, and our structured market data is the unlock. On one side: Their documentation, their data, their customer transcripts. On the other: A clean, objective view of what companies are actually doing. The most interesting thing we're seeing: a handful of beta users have started using Pulse to build their own pricing agents. The recommendations those agents are producing are sharp. Specific. Grounded in what's actually shipping. It's the closest thing to a real pricing copilot I've seen. We soft launched last week. If you're a SaaS operator or pricing consultant and you want to take it for a spin, comment here or shoot me a DM and I'll get you squared away.

I wonder what you think about this "new" pricing model promoted by Nue. It feels like it's supposed to solve a very real shift: - "Old Saas" sold entitlements: licenses, seats, subscriptions - "New SaaS" increasingly sells committed spend against flexible consumption. Simply put: As a vendor, how do I give my customers flexibility without destroying (the predictability of) my revenue? I like the direction, but I wonder where it might break in practice. A few things that can go wrong in my mind: - it's difficult for customers to understand, because it's complex. - AI usage volatility is still crushing margins. - Frequent disputes about overage and unexpected credit burn. - Prone to metering inconsistencies = even more disputes. - Revenue still unclear + accounting complexity (taxes, compliance). - Product behaviour drifts away from the commercial intent over time (the entitlements become a bit fuzzy). Curious what people here actually think of this model. Have you seen it succeed or fail?