Engineering the Bulletproof AI agent.
Deep-dives into verification protocols, provider orchestration, and the architecture behind zero slop autonomous coding.
External Agents Need a Filesystem Boundary
If another agent can generate file actions, the next question is not which model wrote them. It is who verifies what actually changed on disk.
Read article →One-Shot AI Coding Agents Need Verification, Not Just Better Prompts
Scriptable AI coding agents are useful only when they keep the same safety guarantees as the interactive chat loop. Here is why one-shot execution still needs filesystem verification.
Read article →The GitHub PR Surfaces AI Agents Should Never Change Quietly
AI code review should care less about impressive summaries and more about the files that can change installs, CI, deploys, secrets, and command execution.
Read article →Why AI Coding Tools Hallucinate File Paths (And How SWD Fixes It)
Every AI coding agent lies about files. They claim to write code that doesn't exist, modify files they never touched, and delete things that were never there. Here's why — and the protocol we built to stop it.
Read article →Multi-Provider AI Routing: Handling Provider Failures Without Losing the Session
What happens when a provider rate limits, stalls, or fails mid-session? Mythos can retry, score providers, and fall back to another configured provider instead of treating one API failure as the whole session.
Read article →How to Evaluate Coding Models Behind an SWD Boundary
Model quality matters, but filesystem verification changes what you should measure: target accuracy, action schema adherence, correction behavior, latency, and cost.
Read article →Ready to stop AI from lying about your code?
Verified file operations · Multi-provider fallback · Budget tracking · Self-healing memory