Keep the original words.
A proposed interpretation should point back to the statement it came from. A correction becomes a separate entry.
RESEARCH ATLAS / language
Turn a request into
something you can review.
The useful step between words and action is an interpretation a person can inspect. Preserve the source, show the proposed operation and keep uncertainty visible.
FORM STUDYAI-generated art
Not scientific evidence
Not scientific evidence
A research objective, tested one workflow at a time.SOURCE → CONTEXT → OPERATION → CONSEQUENCE
WORDS / CONTEXT / ACTION
What was said.
What the system proposes.
The current local workbench handles a defined set of memory instructions. It gives us a concrete way to test the whole path before extending it to broader language.
SUPPORTED SYNTHETIC EXAMPLE
Remember “signal” is “amber”.
Change “signal” to “green”.
What is “signal”?
- 01 / STOREsignal ← amberCreate a named value.
- 02 / REPLACEsignal ← greenKeep the source of the change.
- 03 / RECALLsignal → greenShow the answer and its history.
implementedSupported words become inspectable operations
A versioned authored grammar produces write, change, recall and reset events. Review precedes adoption; unresolved wording remains visible.
Finite phrase coverage does not establish general language understanding.
This is an illustration of the documented grammar. The public page does not interpret visitor input.
WHAT THAT MAKES POSSIBLE
A useful interpretation
can be challenged.
Instead of treating a generated answer as the end of the process, keep the information needed to inspect and correct it.
Say what is missing.
Unsupported wording and ambiguous references stay visible. A partial interpretation is not understanding the whole request.
Review before adoption.
People can inspect the proposal before changing the accepted record. Imported text never grants permission to take external action.
EXTENDING TOWARD CUSTOMER WORK
Messages, reviews
and claims.
OscarMike explores assistance around source content and comments. The next useful question is whether a review is relevant, supported and clear enough to help someone—not whether a model can assign a confident-looking score. Current model scores still need calibration and better handling of missing context.
START WITH YOUR WORK
What needs to
stay true?
Bring a task, a source of information and a result you need to trust. We can discuss where the current tools fit, what would need to be built, and how to test whether it helps.
Discuss your use case ↗mr.white@jtech.aiAn exploratory conversation. Customer integrations and commercial arrangements are agreed separately.