OpenAI just made Projects free for all 800M ChatGPT users. I like the move for a few reasons: 1. Projects is habit-forming. A place to keep stray notes about all the topics you care about. 2. Projects deepens usage. Adding instructions and context requires a level of depth beyond simple prompts. 3. This combo of stickiness and deeper usage should drive more upgrades. Stickier product + more sophisticated usage means users will hit their usage limits more often (and maybe using Projects makes them curious about Tasks and Custom GPTs?). Even if they don’t upgrade, they're less likely to leave ChatGPT. What do y'all think?

Hi Everyone, I'm Gary, based out of Connecticut, and I work with some of the Upper mid-market private equity funds to gather competitive information on pricing, product, packaging and positioning. It's been a long road getting to this point, but I'm pretty embedded in half a dozen funds, where we've turned elements of the traditional pricing consultancy model on its head. Essentially, we map the market, reverse engineer what best in class looks like, and spot the gaps in what's being offered to customers by the marketplace today. Look forward to getting to know you all, and happy to answer any questions if there are any. Cheers, Gary

Okay, so the Pokemon catchphrase 'Gotta catch 'em all' sums up this problem: Some pricing models inhibit the natural expansion volume of the customers - e.g.: - We sell factory locations, but customers start with 1 factory and grow slowly from there. - We sell 10 users... but every customer have 100+ potential users. - We price per patient... but only get to handle patients of type A, not types B and C. The simple example-fix is to price per number of employees (a volume outside the control of the customer) instead of per user (a volume controlled and reduced by the customer)... but what other ways have you guys used to solve the share-of-wallet problem? Asking for a friend 😉

Hey all! I’m looking for a small/boutique SaaS pricing consultant who can serve as an external ear on a monetization strategy I’m finalizing for FY26. This isn’t a “teach us pricing” project. The tactical stuff (user testing, billing experiments, packaging variants) is already underway. What I need is someone who can help stress-test the big picture and sanity-check the architecture. Specifically looking for help with: 1. Coherence check: does the strategy work as a system? 2. Blind spots: assumptions, hidden risks, unintended effects. 3. Pattern benchmarking: how our model maps to modern PLG + AI monetization patterns. 4. Narrative review - does it scale cleanly to C-level/board and down to PMs? 5. Sequencing risks - where rollout timing could break. 6. Edge-case audit - usage/plan boundaries, adoption cliffs, etc. If you know someone who fits this profile, or you’ve worked with a boutique firm that leans strategic (not just packaging projects), I’d love recommendations. Thank you!

I'm a consultant working with SaaS companies on pricing strategy and contract terms, predominantly in healthcare tech but now across other sectors. My clients operate in the $5-10-20k+ MRR minimum contract value space—basically, they're selling enterprise/mid-market deals rather than per-seat models. I'm curious whether the pricing frameworks and strategies discussed here translate to that higher-ticket tier, or if the dynamics are fundamentally different enough that the learnings don't carry over. Are there folks here working in that contract-value space who could speak to what's similar/different about pricing strategy at that level? Thank you!