The comparison sounds reasonable on the surface, but it breaks down once you separate:

1. Understanding code semantically and deterministically, versus
2. Generating probabilistic explanations about code.

AI is extremely good at the second. Understand is extremely good at the first. AI and Understand solve different layers of the same problem.


For example, LLMs are excellent at:

  • explaining functions

  • summarizing files

  • onboarding developers

  • suggesting fixes

  • generating tests

  • accelerating exploration

The thing to remember is AI is fundamentally probabilistic. Because of this AI can have a number of downsides:

  • misunderstand context
  • hallucinate relationships
  • miss edge cases
  • lose accuracy on massive codebases
  • fail silently
Understand is deterministic. It parses your code and builds a database of relationships. Understand uses that database to build:
  • symbol tables
  • dependency graphs
  • call relationships
  • inheritance hierarchies
  • data/control flow
  • metrics
  • architectural relationships
That means the information you get from Understand is reliable and won't change based on what model you are using. Things like:
  • “Who calls this?” is exact.
  • “What breaks if I change this?” is grounded.
  • “Show every usage across 12M LOC” is deterministic.
  • “Which files violate MISRA?” is auditable.
Understand and AI provide fundamentally different capabilities. The best teams will use both, which is why we've spent so much time and effort adding AI capabilities to Understand. The thing is, AI depends on tools like Understand more than you might think, and adding Understand to your AI's toolkit can make a huge difference.

For smaller projects, Understand is likely unnecessary and using AI with Cursor or VS Code is probably sufficient, but for larger projects, embedded systems, and safety critical systems, tools like Understand will still be required. When AI is given tools like:
  • ASTs
  • symbol graphs
  • dependency maps
  • cross-reference databases
  • static analysis results
AI goes from impressive to trustworthy. Understand is the kind of infrastructure that makes enterprise AI reliable.