Reliability
18 articles about reliability.
Accessibility APIs vs Pixel Matching - Why Screenshots Miss So Much Context
Screenshots give you pixels. Accessibility APIs give you semantic structure with element roles, labels, values, and actions. The reliability difference is fundamental.
The Hardest Part of Building AI Agents Is Execution, Not Planning
LLMs are surprisingly good at planning multi-step tasks. The hard part is reliable execution - clicking the right targets, handling page loads, recovering from unexpected modals and UI state changes.
Error Propagation in Multi-Agent Networks - The Problem Nobody Talks About
When one AI agent makes a bad decision, every downstream agent inherits that error. Multi-agent systems amplify mistakes instead of catching them. Here is why error propagation is the real challenge.
Don't Trust Agent Self-Reports - Verify with Screenshots
Why AI agents report success even when they fail, and how screenshot verification after every action catches errors that self-reports miss.
Testing AI Agents with Accessibility APIs Instead of Screenshots
Most agent testing relies on screenshots which break constantly. Accessibility APIs give you the actual UI structure - buttons, labels, states. Tests that check the accessibility tree survive UI redesigns.
When AI Agents Roleplay Instead of Executing - Why Desktop Wrappers Matter
AI agents sometimes pretend to complete tasks instead of actually doing them. A proper desktop app wrapper with real tool access solves the fake execution problem.
AI Agents Lie About What They Did - Why You Need Action Verification
LLMs confidently report failed actions as successful. You need accessibility tree snapshots and state verification to know if your agent actually did what it claims.
Making Claude Code Skills Repeatable - 30 Skills Running Reliably
Running 30 Claude Code skills reliably for a macOS agent. The key to repeatability is explicit frontmatter, narrow scope per skill, and clear input/output contracts.
Why Claude CoWork Feels Like Your Worst Coworker - VM Reliability Issues
CoWork's VM-based approach means random crashes, lost context, and slow restarts. When your AI coworker needs more babysitting than a junior developer, something is wrong.
DOM Manipulation vs Screenshots for Browser Automation Agents
Screenshot-based browser automation is painfully slow - capture, send to vision model, interpret, click coordinates. Direct DOM manipulation is faster, more reliable, and the agent knows exactly what elements exist.
DOM Understanding Is More Reliable Than Screenshot Vision for Browser Agents
Vision models guess what's on screen. DOM parsing knows exactly what elements exist, their states, and their relationships. For browser automation, structured data wins.
Error Handling in Production AI Agents - Why One Try-Except Is Never Enough
Why a single broad try-except catches everything and tells you nothing. Production AI agents need granular error handling with different recovery strategies.
What File Systems Teach About AI Agent Reliability
File systems solved reliability decades ago with atomicity, journaling, and crash recovery. AI agents can learn the same lessons for more reliable execution.
Screenshots Are Better Than LLM Self-Reports for Multi-Agent Verification
Judge-reflection patterns in multi-agent systems sound good but the judge LLM can be fooled. Screenshots provide ground truth for verifying whether an action actually changed the screen.
Multi-Provider Switching for AI Agents - Why Automatic Rate Limit Fallback Matters
When your AI agent hits a rate limit, multi-provider switching automatically swaps to another provider. Here's why this pattern is essential for reliable automation.
Non-Deterministic Agents Need Deterministic Feedback Loops
AI agents are inherently unpredictable, but their feedback loops should not be. Why deterministic verification is the key to reliable agent systems.
Real Problems AI Agents Solve vs Demo Magic - Edge Cases and Reliability
AI agent demos look incredible. Production is different. Here is what actually matters: accessibility API reliability, screen control edge cases, and the gap between demos and daily use.
What a 37% UI Automation Success Rate Teaches About Building Reliable Desktop Agents
UI automation started at 40% success. Top-left vs center coordinates, lazy-loading, scroll races - here is what we learned getting to 85-90% reliability.