Performance
7 articles about performance.
Inference Optimization Is a Distraction for AI Agent Builders
Why optimizing API call speed barely matters for AI agents - the real bottleneck is action execution, not model inference.
385ms Tool Selection Running Fully Local - No Pixel Parsing Needed
Local agents using macOS accessibility APIs skip the screenshot-parse-click cycle. Structured app data means instant element targeting and sub-second tool selection on Apple Silicon.
Native Swift Means Your AI Agent Launches Instantly
Electron apps take seconds to start. Native Swift apps launch in under a second. For an always-on agent activated by hotkey, that speed difference matters every time.
Why Removing Unused MCP Servers Speeds Up Claude Code More Than Removing Skills
Trimming unused MCP servers made way more difference than removing skills. MCP servers are actual processes that all have to handshake on startup.
Scaling Real-Time AI - Why the Screenshot Capture Pipeline Is Always the Bottleneck
Building real-time AI agents that react to screen content? The screenshot capture pipeline is where performance hits a wall. Here's how to fix it.
Real-Time AI Agent Performance - Fixing the Screenshot Pipeline
Your AI agent is slow because of screenshot capture, not LLM inference. Here are practical techniques to speed up the capture pipeline.
Fixing SwiftUI LazyVGrid Performance Issues on macOS
LazyVGrid jitter and stuttering on macOS comes from view identity instability. Here are practical fixes: stable .id() values, extracted cell views, async image loading, and avoiding inline closures.