What's your biggest headache with LLM cost management in production?

Hey everyone 👋

I'm Bravolity — building AgentGate, a lightweight LLM gateway designed for small AI teams (5–50 people).

Before writing a single line of code, I spent a few weeks on Reddit and developer forums just listening. A few pain points kept coming up independently:

• Cost visibility — token-level costs exist, but teams can't tell which agent task or workflow run caused a spike

• Model lock-in — when a new model drops, teams are stuck waiting weeks for their gateway to support it

• Enterprise-gated basics — SSO, audit logs, cost controls... all locked behind $1,000+/month tiers

We're building specifically for the teams that fall through the cracks between "too small for Enterprise" and "too busy to self-host LiteLLM."

My question for you: what's the most frustrating part of managing LLM API costs in your current stack? Is it the observability, the tooling, or just the sheer unpredictability of agent-driven workloads?

Would love to hear what you're running into — this is exactly the kind of input that shapes what we build first.

🔗 Waitlist: https://agentgate-theta.vercel.app