Problems / Multi-agent and harness, medium
The harness compacts context on every turn with a summariser that has 4 slots.
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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 4; 1 of them are hidden until then.
3 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 harness.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 harnessAgent harness | Agent API calls it.Calls Model, Context compactor.A harness is everything around the model in an agent: context management, tools, checkpoints, retries and evaluation. | 400 slots · 6 steps |
| ModelLLM endpoint | Agent harness calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second. | 1000 streams |
| Context compactorContext compactor | Agent harness calls it.Compaction summarises a long context so the agent can keep going without hitting the window limit. | 4 slots |