AI Agents Write Code. You Have No Idea What They Wrote.
Developers use AI coding assistants every day. But no one tracks what the agents wrote, whether it was reviewed, or where it ended up in production. You're shipping code with zero attribution.
Of developers now use AI at work, spending a median of 2 hours per day with AI coding tools.
Pull requests authored by GitHub Copilot's coding agent in just 5 months. AI is now an active code author at production scale.
Experienced developers completed tasks 19% slower with AI on complex, unfamiliar codebases: the opposite of expectations.
Monitor. Inspect. Tag. Track.
Desktop Agent Monitoring
Lightweight desktop agent observes AI coding assistant activity (Copilot, Cursor, Claude Code, and others). See what agents are writing across every developer workstation without interrupting flow. No IDE plugins. No workflow changes.
- Zero-friction desktop agent: no IDE plugins required
- Supports all major AI coding assistants
- Activity logged locally before secure sync
- Developer-visible: no hidden surveillance
Build-Time Code Inspection
Every build is inspected to extract exactly what went in: source commits, dependencies, build parameters, and AI-generated code markers. The build system is the source of truth, not self-reported metadata.
- Full dependency manifest from actual build output
- AI-generated code markers detected automatically
- Build parameters and environment captured
- Queryable build history across all services
Cryptographic Provenance Tagging
All AI-generated code is tagged with provenance metadata: which agent, which developer, which timestamp. Tags are embedded in build artifacts and persist through commits, merges, rebases, and deploys. Attribution is cryptographic. It survives everything.
- Provenance tags embedded in build artifacts
- Agent type, model, and developer recorded
- Attribution survives rebases, squashes, and cherry-picks
- Human modifications tracked alongside AI attribution
AI Code in Production: Real-Time Inventory
Follow AI-generated code from the developer's desktop through CI/CD into production. Know exactly which containers, services, and endpoints run agent-written code right now. Build system inspection plus production beaconing equals ground truth.
- End-to-end lineage from IDE to running container
- Real-time production inventory of AI-generated code
- Percentage of AI-authored code per service and team
- Review status tracking: approved, pending, unreviewed
AI Code Traceability Knowledge Base
Field data, regulation, and tactics for tracking what autonomous coding agents are writing in your codebase.
Prove what your agents wrote.
Monitor AI agent activity, tag every line with cryptographic provenance, and track agent-written code from desktop to production.
Frequently asked about ai code traceability.
The desktop agent observes AI coding assistant activity: accepted suggestions, applied completions, and inserted code blocks. It records which agent, which model, and which developer, without capturing keystrokes or screen content outside the coding context.
View full page →Provenance tags are embedded in build artifacts during CI/CD. Even if a developer modifies the code after generation, the original AI attribution is preserved alongside the human modifications. Tags survive rebases, squashes, and cherry-picks.
View full page →GitHub Copilot, Cursor, Claude Code, Codeium, and any assistant that operates through standard IDE interfaces. The monitor detects agent activity at the OS level, so new assistants are supported automatically.
View full page →No. The desktop agent is a lightweight background process. There are no IDE plugins to install, no workflow changes, and no approval gates. Developers code exactly as they did before. Crash Override just makes the invisible visible.
View full page →A CISO at a major AI company went from Defcon 5 to Defcon 1 on AI adoption risk in a single quarter. Crash Override provides the visibility and guardrails that let teams adopt AI agents confidently, without blocking developer velocity.
View full page →Other vendors want to block agents. Developers route around blockers. We provide visibility and guardrails, not gates. You see exactly what agents produce, where it ships, and what runs in production.
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