Hey all, I'm new to the community and interested to hear if anyone else has successfully used Claude Skills to augment/influence sellers during the sales cycle. I've built a few skills that are showing some promise but I haven't asked my team to adopt them yet. I am just running the skills against deals in hubspot to spot check their quality. Curious if anyone has and if it worked well.

Curious to hear how other pricing strategists and operators are using AI in their workflows. Are you just getting started, or do you have a full flow built? What tools do you like vs. which tools are causing you the most trouble? I'm especially curious if anyone has developed a way to leverage AI to refine ICPs?? Or if anyone has found any good Claude skill files specific to pricing? I'll kick off! Some context: We're refining our sales-led pricing model at the moment and need to move quickly, so I don't have the support to run formal research. I'm also a team of one at a Series A company that just underwent a massive change in how we deliver our product 😅 I've been using Claude to refine new pricing structures and develop HTML pricing calculators for sales-led deals. I've been funneling context to Claude using our product's MCP server, knowledge files, and more, which have allowed me to develop and pressure-test various pricing strategies that I have then vetted with cross-functional leadership and sales as viable to test. My sales team now has a self-service hub they can rely on to run with these new models for certain deals. The hub provides guidance on choosing a model, the value story for the chosen model, pricing, and ROI calculations. Would love to hear what everyone else is doing!

I just added this to a comment so sharing for visibility: The SaaS Monetization Tech Stack Billing has Stripe. Analytics has Amplitude. Feature flags have LaunchDarkly. Etc. But the system that decides when to upsell a user, what usage limit to enforce, or which paywall variant to show? That usually lives in a tangle of product code, feature flags, and duct tape... A few things that have came up: - The fragmentation problem is worse than most teams realize. Entitlement logic ends up duplicated across billing, product code, and feature flags. A simple pricing test that should take a day takes weeks because three systems need to stay in sync. My CTO (ex-Atlassian, Dropbox) is really good at explaining the risks/headaches from this "brittleness" to technical folks! - Mobile solved this years ago. RevenueCat and Superwall own the monetization layer for iOS/Android apps. Web SaaS has no equivalent — most teams are still stitching it together manually. The above content is really resonating with an ex-Revenue Cat guy who is now Head of Product at a web SaaS business. - The main benefit of getting it right (in-house or via tooling) is experiment velocity

Hi all, I'm a technical product manager for Usage Cloud at DigitalRoute, based in Sweden. Been working with real-time prepaid credits and batch-based pricing, charging and billing since 2004 at scale - also deep knowledge of usage data mediation (the stuff that happens to get the messy real-life operational system events data in shape so it _can_ be priced). I have a fairly solid grasp of the entire quote-to-cash process. I co-host DigitalRoute's invite-only Usage Unlocked roundtable every month or so, where we discuss all things related to usage and pricing. I'm also a Wardley mapping nerd building the collaborative mapping SaaS https://mapaware.io (feel free to try it out), and I co-founded the Blockchain Sweden industry association. And overall tech nerd.

Hi all, Curious who/job-titles in your companies actually tactically execute price changes, especially those that have systems of record or "list prices" in a CPQ system. Are they pricing strategists/managers? operations professionals or system administrators? engineering? Curious the level of technical fluency of the operators as pricing mechanics can be complex, who is responsible that the configuration of systems match desired outcomes?