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Stigg @GetStigg

Building the future of software monetization, delivered in one powerful API

Joined March 2022
  • Tweets 427
  • Following 101
  • Followers 139
136 Photos and videos
We're coming to the @aiDotEngineer World Fair 👀 Something massive is dropping, and AIE is where it goes live first. Come see it for yourself at booth LG3. Football fans: we've got you too. ⚽
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We'll get into the real stuff: → Why metering and decisioning are different problems → How the decision waterfall works under the hood → The trade-offs behind provably correct billing at scale → What AI companies building usage-based products should know now
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This isn't a polished talk. It's a live AMA. Start thinking about your questions. This will be an honest conversation, not a presentation. Register here: luma.com/gaj3eim4

Inside OpenAI's Real-Time Access Engine · Zoom · Luma

Provably Correct, Impossibly Fast In February 2026, OpenAI published "Beyond Rate Limits" - a deep dive into how they rethought access control for Codex and…

luma.com
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You're mid-flow in Codex. It's working. Then: rate limit hit. Hard stop. Come back later. That experience is what pushed OpenAI to rethink access control entirely. We got the engineer who built it to come talk to our community. 🧵 luma.com/gaj3eim4
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Jonah Cohen, Tech Lead for Financial Engineering at OpenAI, designed and built this system. He published a rare honest write-up about it in February. And now he's joining HTTP 402 for a live AMA.
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And they built it entirely in-house. Not because they couldn't afford a metering platform. Because no third-party tool could give them real-time correctness AND full auditability at the same time. When both matter, you own it.
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They built a real-time access engine that makes a single per-request decision: How much usage is allowed? From where? Rate limits, credits, entitlements, evaluated together, synchronously, in milliseconds. They called it the decision waterfall.
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The problem wasn't just UX. Raise rate limits → lose fairness and capacity control. Switch to usage billing → introduce lag, overages, reconciliation debt. Neither worked for products people were actually using and loving. So they did something harder.
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At Stripe Sessions, Miro's session drew more people than the room could fit. Engineers on the floor, others crowded at the entrance. Here's what they shared 🧵
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So they brought in Stigg as a single entitlement layer, and shipped in six weeks. ✅ Hybrid seat usage AI model live in production ✅ 5,000 engineering hours saved ✅ Pricing changes: months → days ✅ 4 major monetization changes shipped in a single 4-month window
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All monetization logic - entitlements, credits, metering, enforcement, plan management - moved into one place. Instead of being scattered across the codebase, it became a single layer that every system could rely on. Clean. Auditable. Easy to change. stigg.io/blog-posts/how-miro…

How Miro Shipped AI Credits in Six Weeks and Cut Pricing Changes from Months to Days | Stigg

A Stripe Sessions recap: how Miro's Growth Engineering Lead revealed the architecture shift that cut pricing changes from months to days.

stigg.io
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Outreach just moved from seats to credits. One of the first established software companies to actually do it. @robbylit has been tracking this shift across hundreds of companies. Here's what the data is showing right now 🧵
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"People don't talk about your pricing page anymore. They talk about pricing.md." - @Dor If an AI agent evaluates your product and your pricing isn't machine-readable, it routes to a competitor whose is. Visibility isn't a nice-to-have. It's infrastructure.
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The real bottleneck when shipping AI monetization isn't the strategy. It's that the systems can't keep up with it. Rob sees a new role emerging to bridge that gap. Like GTM engineering, but for AI usage and control. Full recap: stigg.io/blog-posts/the-grea…

The Great Packaging Rebuild: What's Actually Changing in SaaS Monetization Right Now | Stigg

The rules of software pricing have changed, and the companies winning aren't just tweaking price points, they're redesigning how value is packaged, sometimes multiple times a year.

stigg.io
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Something happened at Stripe Sessions that doesn't usually happen at conferences. People actually talked to each other.
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Same question kept coming up everywhere: we're shipping agents fast. But who consumed what, at what cost, attributed to which team or user, nobody has a clean answer. And nobody wants to add 200ms to every inference call to get it.
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That's exactly what we build for. Real-time usage control across every entity in your stack. Zero latency. Your cloud. Audit trail included. Good few days.
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