SHAPING THE FUTURE OF
AI DEBUGGING
AI CODING
VS
AI DEBUGGING
AI coding assistants – powered by LLMs like GitHub Copilot, Claude, and OpenAI Codex – are changing how developers write code. They help generate boilerplate, suggest fixes, and even tackle entire features.
But coding is only half the battle. When things break, the challenge is understanding what the existing code did — and fixing bugs AI introduced along the way.
Today’s AI assistants can analyze source code, logs, and outputs from other tools to help find bugs. But they can’t see how your program actually behaved unless you explicitly tell them.
- They can’t know the dynamic behavior of the software just by looking at the source code (they don’t have access to the inputs, variable values, thread interactions that led to the failure)
- Logs capture some dynamic behavior, but only if you have them in the right place. If you don’t, you and the LLM need to go around tedious cycles of editing, rebuilding, and reproducing the issue.
In short, AI is brilliant at pattern recognition – but debugging requires precise context, not educated guesses.
Undo provides what AI cannot generate on its own: a full-fidelity recording of a program’s actual execution. This unique capability to make AI better is enabled by time travel debugging.
Undo is the leading provider of time travel debugging technology — capable of recording unmodified Linux software and replaying every instruction, variable change, and I/O event.
WITH TIME TRAVEL DEBUGGING
UNDO CAPTURES
And once recorded, execution can be replayed across machines – forward or backward – so engineers (and now AIs) can trace the root of issues in one single debug cycle (or just see where reality diverged from expectations).
Undo is already trusted in performance-critical environments – from networking software, to large-scale simulation software, data management systems, or low-latency trading and market data software.
And now, we’re bringing this power to AI agents.
Large Language Models (LLMs) are incredible at processing text – but they’ve never had access to a complete, queryable timeline of program behavior.
Until now.
Undo is building a recording-aware AI interface where LLMs can ask
“When did this variable last change?”
“What caused this null pointer?”
“What was the thread state before the crash”
A query-oriented debugging layer, tuned for AI workflows (not just human ones)
Tools that let LLMs reason over execution — with far less hallucination, and far more precision
SMARTER AGENTS. MORE ACCURATE DIAGNOSES. LOWER TOKEN COSTS.
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