Building a Sub-Millisecond AI Gateway in Go for Autonomous Coding Agents

Description and use

GoRoute reduces latency to <0.8 ms, uses <12 MB RAM, and provides dynamic failover routing for autonomous coding agents.

Problem

Agent execution loops issue dozens of rapid LLM calls per minute, and standard Python-based proxies add 40‑100 ms latency per hop, consume hundreds of megabytes of memory, and choke during parallel agent streaming.

Outcome

GoRoute reduces per‑hop latency to sub‑0.8 ms, keeps RAM usage below 12 MB, and supports dynamic failover and token pooling, improving scalability of autonomous coding agent workflows.

Workflow

• 1. Deploy GoRoute as a lightweight proxy between agents and LLM APIs.
• 2. Configure GoRoute to translate OpenAI format to Anthropic messages format.
• 3. Enable dynamic failover cascades to switch from Claude 3.5 Sonnet to DeepSeek‑V3 or GPT‑4o when needed.
• 4. Set up multi‑account token pooling to distribute requests round‑robin across API keys.
• 5. Route agent requests through GoRoute to achieve sub‑0.8 ms latency and reduced memory usage.

Evidence

Standard Python-based proxies introduce 40ms–100ms of latency per hop, balloon to hundreds of megabytes in memory, and easily choke during parallel agent streaming.

Source

I built GoRoute — an ultra-lightweight, high-throughput AI gateway and dynamic LLM router written in Go.

Source