A draft invoice can match a usage export down to the cent and still miss billable activity if an account, meter, or event category never made it into that export. For teams using usage-based pricing, what do you check the export against before invoices go out? Source-system event counts, active accounts and meters, or something else? I’m curious about what actually happens in practice, even if it’s a manual spreadsheet check.

Hey everyone, I’m Anuj from Anrotex. We’re building Venpalo, a read-only way to check whether a draft usage-based invoice matches the customer’s agreed terms and the usage behind it. I’m interested in what happens after a pricing model is designed. Negotiated rates, discounts, allowances and tiers can make sense on paper, but someone still has to make sure they show up correctly on the invoice. We’re pre-pilot, so I’m here to learn from people who’ve handled these pricing and billing changes in practice, and to contribute where I can. Glad to be here.

Howdy pricing people! On October 8th we've got two special guests: Ulrik Lehrskov-Schmidt, CEO of Willingness to Pay, and Emil Eriksson, CPO of DigitalRoute. We're going to talk about AI margins, and how to stop them from slipping away as usage grows. The pairing gives both sides: - Ulrik works on strategy: credits, packaging and how to capture value. - Emil works on the technical side: how usage actually gets metered and turned into revenue. We're increasingly seeing a gap in communication between these two groups, and believe tighter collaboration is key for the next phase of AI monetization. A few things we're going to dig into: - How to set credit burn rates when your model costs keep moving - When sending work to cheaper models makes sense, and when it just makes the product worse - What your usage setup needs to track now so you can change pricing later without a rebuild Details below: Thursday, October 8th @ 11am ET Register here 👉 https://luma.com/qdlmss76 Hope to see you there! Rob

There's so much AI news every day that I can't tell what actually matters and what's just hype. Right now I have a little automated workflow on my MacBook that runs around 8am and pulls trending GitHub repos, Hacker News, some AI subreddits and about 26 AI lab and founder accounts on X, then ranks what's blowing up on a simple dashboard. Does anyone have a setup like this, or sources you trust to separate signal from noise?

When do you think a CRM actually becomes worth using? I’ve found that setting one up too early can sometimes create more work than value if you’re still just trying to get deals in the door. Do you use one from the start, when you’re juggling potential leads, or wait until you have a few clients/leads to manage after closing? And which CRM do you recommend?