Conductor Rewrite Performance

When to use this skill

• You're building a local-first desktop application with React and experiencing performance bottlenecks
• Navigation or route changes trigger cascading re-renders across multiple mounted components
• You have a chat interface or long list that streams content and re-renders become sluggish
• You're using Tauri and need to profile React performance but can't access Chrome DevTools
• Multiple heavy views are mounted simultaneously (sidebar, nav, chat, terminal, editor) and all re-render on state changes
• You need to manage multiple heavyweight child processes without exhausting system memory

Core principles

1. Local-first eliminates an entire category of performance problems. When SQLite is your source of truth and the UI never waits on the network, the bottleneck moves up into the rendering layer—every unnecessary re-render becomes the slowest thing users feel.

1. Unstable references cascade re-renders through the entire component tree. When router hooks return fresh objects on every render, every component reading them re-renders even when values haven't changed, and those re-renders propagate to all children.

1. Virtualization plus memoization is the only way to make streaming lists fast. Render only what's on screen (15 messages instead of 500), and ensure only the actively changing item re-renders while the rest stay memoized.

1. The fastest operation is the one the user never waits on. Move expensive synchronous work (like git checkpoints) off the critical path so the first token arrives immediately.

Tactics

Shim the Tauri bridge to profile in Chrome

When you can't use Safari's Web Inspector to debug React performance in a Tauri webview, create a development shim that lets the same client run in Chrome with full DevTools access.

// Conductor's UI reaches the Rust core through Tauri's invoke() bridge.
// In a real browser there's no Tauri runtime: __TAURI_INTERNALS__ is
// undefined and every invoke() throws. So in dev we shim that single
// entry point and boot the exact same client in Chrome, where the
// Chrome profiler AND the React DevTools profiler both work.

import { invoke as tauriInvoke } from "@tauri-apps/api/core";

export function invoke(cmd: string, args?: Record): Promise {
  // Packaged app: use the native bridge.
  if ("__TAURI_INTERNALS__" in window) return tauriInvoke(cmd, args);

  // Dev in Chrome: stand in for the Rust backend. Proxy to a dev server
  // running the real commands, or return canned data for the surface
  // you're profiling.
  return fetch(`/__backend__/${cmd}`, {
    method: "POST",
    body: JSON.stringify(args ?? {}),
  }).then((r) => r.json());
}

Steps:

1. Identify the single bridge function your UI uses to talk to the native layer (e.g., Tauri's invoke())
2. Check for the presence of the native runtime object (__TAURI_INTERNALS__)
3. In production, call through to the real bridge
4. In development, proxy to a local server or return mock data
5. Boot the client in Chrome and use React DevTools Profiler to identify bottlenecks

Replace react-router with TanStack Router for stable references

When navigation produces fresh param/search references that cascade re-renders, switch to a router that provides structural sharing and stable references.

Before with react-router:

// Before with react-router

import { useSearchParams } from "react-router-dom";

function WorkspaceView() {
  const [searchParams] = useSearchParams();

  // useSearchParams() returns a NEW URLSearchParams every render,
  // and this parsed object is a new reference every render too.
  const filters = {
    agent: searchParams.get("agent"),
    status: searchParams.get("status"),
  };

  useEffect(() => {
    refetchAgents(filters);
  }, [filters]); // new object each render → fires on EVERY render

  return ; // child re-renders every time
}

After with TanStack Router:

// After with tanstack router

import { createFileRoute } from "@tanstack/react-router";

export const Route = createFileRoute("/workspace")({
  // parse + validate search once, fully typed
  validateSearch: (s): { agent?: string; status?: string } => ({
    agent: s.agent as string | undefined,
    status: s.status as string | undefined,
  }),
});

function WorkspaceView() {
  // structural sharing: SAME reference unless agent/status actually change
  const filters = Route.useSearch();

  useEffect(() => {
    refetchAgents(filters);
  }, [filters]); // fires only when a value really changes

  return ; // no re-render!
}

Steps:

1. Define routes with createFileRoute and add a validateSearch function that parses and types search params
2. Replace useSearchParams() with Route.useSearch() to get a stable reference
3. Remove manual useMemo wrappers around parsed params—structural sharing handles it
4. Verify with React DevTools Profiler that only components with actual changes re-render on navigation

Virtualize + memoize streaming chat lists

When a chat UI with hundreds of messages re-renders on every token, combine virtualization (render only visible items) with memoization (skip unchanged items).

Before:

// Before: the simple approach where each message/token rerenders everything

function Chat({ messages }) {
  return (
    
      {messages.map((m) => (
         // all N re-render on each token
      ))}
    
  );
}

After:

// After: virtualize the list + memoize each row

const Message = React.memo(function Message({ message }) {
  return ; 
});

function Chat({ messages }) {
  // VirtuosoMessageList is a component from Virtuoso
  return (
     }
    />
  );
}

Steps:

1. Wrap each message component in React.memo so it only re-renders when its props change
2. Replace the .map() loop with react-virtuoso's VirtuosoMessageList (or Virtuoso for general lists)
3. Pass the full message array as data and render each item via itemContent
4. Let Virtuoso handle scroll anchoring, bottom-stick during streaming, and dynamic height measurement
5. Verify that only the streaming message re-renders while the rest stay memoized

Move expensive synchronous work off the critical path

When a blocking operation (like a git checkpoint) sits between user input and the first response token, move it to the background.

Pattern:

• Before: User hits enter → synchronous git add -A → send prompt → first token arrives
• After: User hits enter → send prompt immediately → first token arrives → checkpoint runs in background

Steps:

1. Identify synchronous operations on the critical path (e.g., file snapshots, database writes)
2. Fire them asynchronously after the user-facing action completes
3. Ensure the background task still completes before the next checkpoint is needed
4. If resumption depends on the checkpoint, pass a --resume flag so the session can restart from disk

Manage memory for multiple heavyweight child processes

When your app spawns multiple long-lived processes (e.g., agent sessions), shut down idle ones and resume on demand.

Steps:

1. Track the last activity timestamp for each child process
2. After a threshold of inactivity (e.g., 5 minutes), kill the process and reclaim memory
3. Persist session state to disk with a unique identifier (e.g., --resume )
4. When the user returns to that workspace, spawn a new process with the resume flag
5. Verify in Activity Monitor / Task Manager that idle workspaces don't hold memory

Anti-patterns

❌ Don't wrap every unstable reference in useMemo manually—fix the root cause by switching to a library that provides stable references (like TanStack Router's structural sharing).

❌ Don't render all list items and rely on CSS overflow: scroll—virtualize so only visible items exist in the DOM.

❌ Don't block the UI thread with synchronous git operations or file I/O on the critical path—move them to background tasks.

❌ Don't let heavyweight child processes accumulate indefinitely—implement idle shutdown and resume-on-demand.

❌ Don't skip profiling because your webview doesn't support Chrome DevTools—shim the native bridge and run the same client in Chrome for development.

❌ Don't assume local-first means fast by default—once network latency is gone, rendering bottlenecks become the new constraint.

Source

The Conductor Rewrite: What They Changed to Make It Fast

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: boraoztunc
• Source: boraoztunc/skills
• License: Apache-2.0
• Homepage: https://bookmarker.cc

Install and usage instructions live in the source repository linked above.