GitHub user gupta-sahil01 created a discussion: Ambient "operator recommender" 
— predictive next-operator suggestions on the canvas

## The idea in one line
As a user builds a workflow, show 1–3 faded "ghost" operators on the output 
port of the operator they just added — ranked suggestions for what likely comes 
next, one click to insert.

## How it differs from the existing chatbot agent
The current chatbot is on-demand and conversational: the user describes a goal, 
the agent generates a workflow. That's powerful, but it assumes the user 
already knows what to ask for. This feature is ambient and predictive: 
suggestions surface automatically as part of normal canvas building, with no 
prompt. It's aimed at the moment where a user has some data on the canvas but 
doesn't know which operator unlocks the next step. Think Copilot ghost-text, 
but for the dataflow graph rather than a chat box. The two are complementary — 
I'd want to reuse the chatbot's LLM plumbing rather than build a parallel stack.

## Questions for the maintainers
Existing work: Is anyone already working on operator suggestions / autocomplete 
on the canvas? I'd rather extend than collide.
Mergeability: If this turns out well, would the team be open to a PR? What 
would make it acceptable (config flags, opt-in, evaluation, etc.)?

GitHub link: https://github.com/apache/texera/discussions/5240

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