Problems / AI products, medium
A revenue-ops agent runs CRM reports through an MCP server. The CRM allows 25 report queries at once and rejects the rest immediately, with no queue. Each report takes about 2.4 s, and the agents ask for 12 a second.
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Success ≥ 95% of tasks, p99 ≤ 90 s.
Like a coding problem, a solution has to pass every case, not just the one it was built for. Submit in the lab runs all 3; 0 of them are hidden until then.
4 requests a second for 45 seconds: 100% task (writes).
What each component does in this design, and what calls it. The simulator mimics each one from these settings.
| Component | Its job here | Settings |
|---|---|---|
| Load balancerLoad balancer | Traffic enters here.Calls Agent API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| Agent APIApp service | Load balancer forwards to it.Calls Agent orchestrator.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 3 replicas × 500 slots · timeout 180 s |
| Agent orchestratorAgent orchestrator | Agent API calls it.Calls Model, Report cache (off).An agent loops: think, call a tool, read the result, repeat until done. | 400 slots · 3 steps |
| ModelLLM endpoint | Agent orchestrator calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second. | 2000 streams |
| Report cache (off)Tool result cache | Agent orchestrator calls it.Calls CRM API (25 at once, no queue).Agents often repeat the same read-only tool call within and across tasks. | 2000 slots · 0% hit rate |
| CRM API (25 at once, no queue)External API (mock) | Report cache (off) calls it.Third-party APIs have their own rate limits and outages that you cannot fix. | 25 slots · 60,000 calls/min |