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Spent the weekend wiring 4 different LLMs into one side project. The hardest part wasn't the prompts, it was juggling 4 API keys and 4 bills. Anyone else routing everything through one endpoint now?

I don't think AI apps fail on model choice. They fail on keys, bills, and a provider going dark mid-request. At FlatKey (@flatkey101): one OpenAI-compatible key, 100+ official models, 1,000+ tools. One balance. One invoice. flatkey.ai/?utm_source=x&utm…

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I don’t think model routers win by listing the most models. They win when developers trust three things: the request went where it said, the bill is explainable, and production does not die when one provider does.

The useful abstraction for AI apps is not “one best model.” It is: keep the workflow stable, swap the model behind it, measure cost/latency, and fallback when a provider breaks.

Unpopular take: the winning AI infra company won’t be the one with the longest model list. Lists are copyable. Trust, transparent routing, clean billing, and agent-native distribution are much harder to clone.

Everyone races to add more models. We think that's wrong. Developers don't need 300 choices — they need one key that never goes down. #AI #devtools

6 API keys. 6 dashboards. 6 billing cycles. One provider goes down, your agent goes down. There's a better way.

Everyone copies model lists. We don't compete there. We compete on trust: transparent routing, honest billing, verified outputs. That's the moat nobody talks about. #AIinfra

Swap base_url to router.flatkey.ai/v1. Zero code changes. Instant access to 200+ text, image, and video models — one key, one bill, auto-failover if any provider goes down.

Hot take: your AI cost problem isn't model pricing. It's that you have zero visibility into who's calling what, when, and why. Fix observability first. Everything else follows. #AIEngineering

One API key. One base URL. Every major AI model. Flatkey routes calls, tracks usage per team, and lets you swap providers without touching your code. #AI #DevTools

You have 6 AI providers, 6 billing dashboards, 6 API keys, and 6 places to check when something breaks. That's not a stack. That's a mess you built slowly enough it felt normal.

Every team we talk to manages AI providers the same way: • 3 separate API keys in .env files • No shared rate limit visibility • Manual fallback logic copy-pasted across services • One dev who "knows how it works" This is load-bearing tribal knowledge. It will break at 2am.

We built Flatkey after spending countless hours managing scattered API keys and fragmented usage tracking. We just wanted one flat rate and one dashboard. Simplify your stack, focus on building. 🛠️ #SaaS

Using multiple AI models? You don't need to rewrite your entire codebase when switching providers. Keep your existing OpenAI SDK, change one base URL, and route to any LLM instantly. True engineering efficiency. 💡 #AI

Building AI apps shouldn't feel like managing a vendor portal. Stop juggling 5 different API keys, billing dashboards, and SDK updates. One base URL. Every model. Ship faster. 🚀 #BuildInPublic

We built Flatkey because we were tired of juggling 5+ API keys and bills. \n\nOne key. Every model. Flat rate.\n\nBuilding AI apps should be about logic, not accounting.

Want to switch from OpenAI to Claude without changing your codebase?\n\nJust use an OpenAI-compatible router.\n\nKeep your SDK. Change the base URL. Ship features faster. #BuildInPublic