Hey @OfficialLoganK , can you please explain why Gemini AI Studio "spend caps" don't actually work? I set a spend cap at $80 for a project; an unexpected event blew past this and now it's over $200 owed. What is the point of setting a "spend cap" that doesn't cap anything?

+5

These days going into Friday demos at @polar_sh feels like time traveling far into the future. I fucking love my team, company and having the privilege of doing this for a living, and at this stage in evolution.

Undersold it btw. This is metering in production across Vercel Functions (lambda) at 5,000 requests/s. Within 3ms events are ingested, reduced to their meter, pushed across subscribing nodes and read to protect guardrails and balance checks 🏎️ … and we’re just getting started

Welcome @polar_sh as a Gold Sponsor of FastAPI Conf! 🎉 Polar handles payments, subscriptions, and sales tax so you can focus on building. Thank you for being part of the inaugural FastAPI Conf! 🤝 Oct 28, Amsterdam fastapiconf.com/#supported-b…

Introducing: The next evolution of Polar ✨ We’re building the most ambitious metering & billing substrate for AI software. — Events as the core primitive. A blazing fast, local-first reducer architecture to achieve zero latency metering & entitlement resolution. — Your business as a definition, version controlled & native to agentic workflows. — Definition branching for simulating pricing changes, model forecasts & easy deployment to production. — Signals as business guardrails. Switch to a cheaper AI model when customer’s credits run below a threshold. — Identities as nested entities under the Customer model. Built for agents & services acting on behalf of the customer. Coming soon. Learn more → polar.sh/blog/building-the-n…

thanks for making my life so much easier love the new stripe migration process it was so smooth and the developer working on it was even able to add a new feature that i needed within a few hours

Migrate your entire Stripe catalogue, recurring subscriptions & customers to Polar ✨ Today, we're happy to announce our Private Beta of a new Platform Migration feature. Learn more → polar.sh/docs/migrate

Hi, Tomorrow we are re-opening the Pro $200 subscriptions to new subscribers, but together with it we are also changing how we calculate the usage for it. In effect, if you do the math, it will net out at half the dollar in API spend compared to the old Pro $200 plan. Now that it's said, let me explain why this is happening and why you will still get more work done than if you were on the Pro $200 subscription one month ago. (a) We didn't want to compromise in other ways and are committing to not reintroducing the 5h limit, so that you can fully use the weekly usage when you want. (b) On the subscription, we guarantee that over time you always get more work done and with an increasing level of quality. This means that you will continue to get more value per dollar spent as a result of models getting more efficient and us passing down the improvements in the form of API price reductions. (c) We don't want to put an incentive on ourselves to artificially inflate the API list prices to make it look like you are getting a lot (and workaround it through discounts, etc). Instead we want to continue to both rapidly reduce prices and increase capabilities of models on the API. This week we introduced GPT-6 Sol and GPT-6 Luna at 50% of their previous price. Over time, we see prices go low enough that it makes sense for most to buy usage as needed without there being a significant gap between what you get in a subscription and what you get in the API for a dollar spent. (d) Tomorrow, we are adding more things to the subscription that won't draw on the usage, I won't reveal what that is yet. I wanted to be transparent before all the big announcements tomorrow. Lots of new exciting things are coming to the subscriptions that will make it super compelling, but I wanted to make sure to share this change ahead of time so you can all understand it before we shower you with good news. Codexingly, Tibo

damn I never thought about the possibility that a lot of AI startups only have good margins until people REALLY start using them as models get better, users burn more token evaporating your margins so you can only limit them hardcore or switch to open weight models