How to Fix 'cold start latency during development' in AutoGen (TypeScript)

When you see cold start latency during development in AutoGen TypeScript, it usually means your agent graph is paying the startup cost on every request instead of reusing initialized state. In practice, this shows up when you create agents, models, or runtime objects inside a request handler, test case, or hot-reloaded module.

The fix is usually not in AutoGen itself. It’s in how you instantiate and cache your agents, model clients, and runtimes.

The Most Common Cause

The #1 cause is recreating the AutoGen runtime and model client on every call.

That pattern forces repeated initialization of AssistantAgent, OpenAIChatCompletionClient, tool registration, and sometimes plugin loading. In development, especially with hot reload or serverless-style handlers, that looks like “cold start latency.”

Broken vs fixed

// ❌ Broken: cold start every request
import { AssistantAgent } from "@autogen/agent";
import { OpenAIChatCompletionClient } from "@autogen/openai";

export async function POST(req: Request) {
  const modelClient = new OpenAIChatCompletionClient({
    model: "gpt-4o-mini",
    apiKey: process.env.OPENAI_API_KEY!,
  });

  const agent = new AssistantAgent({
    name: "support_agent",
    modelClient,
    systemMessage: "You are a support assistant.",
  });

  const result = await agent.run("Summarize this ticket");
  return Response.json({ output: result });
}

// ✅ Fixed: initialize once at module scope
import { AssistantAgent } from "@autogen/agent";
import { OpenAIChatCompletionClient } from "@autogen/openai";

const modelClient = new OpenAIChatCompletionClient({
  model: "gpt-4o-mini",
  apiKey: process.env.OPENAI_API_KEY!,
});

const agent = new AssistantAgent({
  name: "support_agent",
  modelClient,
  systemMessage: "You are a support assistant.",
});

export async function POST(req: Request) {
  const result = await agent.run("Summarize this ticket");
  return Response.json({ output: result });
}

If you’re using Next.js, Express, or a worker process with dev reloads, this matters even more. The module-level instance survives between requests in the same process; local variables do not.

Other Possible Causes

1. Tool registration is doing expensive work at startup

If your tools load schemas, connect to databases, or fetch metadata during registration, that cost gets paid before the first token is generated.

// ❌ Bad: expensive setup during import/init
const tools = await loadAllBankingSchemas();
agent.registerTools(tools);

Move that work behind lazy initialization or cache it:

// ✅ Better
let toolsPromise: Promise<Tool[]> | null = null;

function getTools() {
  if (!toolsPromise) toolsPromise = loadAllBankingSchemas();
  return toolsPromise;
}

2. You’re creating a new OpenAIChatCompletionClient per message

This often looks harmless but adds repeated config parsing and connection setup.

// ❌ Bad
for (const message of messages) {
  const client = new OpenAIChatCompletionClient({ model: "gpt-4o-mini" });
  await agent.run(message);
}

Reuse one client:

// ✅ Better
const client = new OpenAIChatCompletionClient({ model: "gpt-4o-mini" });

for (const message of messages) {
  await agent.run(message);
}

3. Hot reload is rebuilding your whole graph

In dev servers, file changes can trigger full module reloads. If your AutoGen setup lives in a file that changes often, every save becomes a fresh cold start.

// config/autogen.ts gets reloaded constantly in dev
export const agent = new AssistantAgent(...);

Keep stable initialization in a dedicated singleton module and avoid importing it through frequently edited files.

4. Your runtime is waiting on network-bound secrets or config

A common hidden cause is fetching credentials from Vault, AWS Secrets Manager, or an internal config service before building the agent.

// ❌ Bad
const apiKey = await secrets.get("OPENAI_API_KEY");
const client = new OpenAIChatCompletionClient({ apiKey });

Cache the secret locally for the process lifetime:

// ✅ Better
let apiKeyCache: string | null = null;

async function getApiKey() {
  if (!apiKeyCache) apiKeyCache = await secrets.get("OPENAI_API_KEY");
  return apiKeyCache;
}

How to Debug It

1. •

   Measure where the time goes

   • •Add timing logs around each step:

   console.time("client");
   const client = new OpenAIChatCompletionClient(...);
   console.timeEnd("client");
   
   console.time("agent");
   const agent = new AssistantAgent(...);
   console.timeEnd("agent");
   

   If construction time dominates, you’ve found your cold start source.

2. •

   Check whether initialization happens per request

   • •Log a module-load marker:

   console.log("autogen module loaded", Date.now());
   

   If this prints on every request in dev, your bundler or framework is reloading the module.

3. •

   Strip the graph down

   • •Remove tools first.
   • •Then remove memory/state.
   • •Then remove custom middleware.

   Reintroduce them one by one until latency spikes again.

4. •

   Look for async work before first run

   • •Search for await in setup code:
     • •schema loading
     • •DB connections
     • •secret fetches
     • •file reads

   Anything awaited before agent.run() can become part of your “cold start” path.

Prevention

• •Keep OpenAIChatCompletionClient, AssistantAgent, and tool registries in module scope when running in long-lived Node processes.
• •Cache expensive setup behind singleton helpers instead of rebuilding per request.
• •Separate development-only hot reload code from production initialization paths so you can spot real startup costs early.

If you still see cold start latency during development after fixing instantiation patterns, inspect your framework first. In most TypeScript AutoGen projects, the problem is not generation speed — it’s lifecycle management around the agent runtime.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.