Screenshots are dead.
JSON speaks.
How we actually use E2LLM to make QA and debugging contextual.
Everyone says “we’re using LLMs for QA.”
Almost no one shows what the LLM actually sees.
We decided to do it differently.
No marketing slides, no diagrams — just the real feed we use every day inside E2LLM.
Not screenshots, but the runtime state itself — DOM as JSON.
That’s how our browser extension (the same one on Firefox & Chrome) captures reality for the model.
Why this works
The secret isn’t the LLM — it’s the context.
Models hallucinate when they don’t see what’s real.
E2LLM takes the rendered UI (DOM, attributes, visibility, validation) — not the source — and turns it into structured JSON.
That’s what the model gets as input.
It’s like sending the actual world, not a story about it.
How we actually use it
- Debugging broken forms (the classic “Submit disabled” mystery).
- QA pipelines — one snapshot before, one after → diff → clarity.
- Testing lazy-loaded components (“hidden until scrolled” → caught by snapshot).
- Feeding UI-state into RAG chains — the model gets the current context of a webapp, not a hallucinated one.
{
"element": "button#submit",
"visible": false,
"disabled": true,
"reason": "validation: email missing"
}
What it gives back
Fewer “invisible bugs.”
QA teams spend less time explaining and more time fixing.
Prompts become reproducible — same DOM → same output.
And yes, it feels weirdly satisfying to see the machine see what you see.
Final thought
We built E2LLM because debugging LLMs without context felt like debugging blind.
If you work with QA, UI automation, or agent pipelines — give it a try.
Install it. Capture one page.
Watch how your model suddenly stops guessing and starts contextualizing.