# Works on My Machine

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Prachi Agarwalla](https://cerebralvalley.ai/u/prachi221), [Aniruddh Vijayvargia](https://cerebralvalley.ai/u/aniruddh2017)
- **GitHub:** https://github.com/ANIRUDDH-001/Tabwise
- **Demo video:** https://youtu.be/FfnHxoUwskI
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2970

Accessibility bugs are not always visible in a screenshot or detectable through static checks. Sometimes a dialog closes, keyboard focus disappears, and a screen-reader user loses their place. Reproducing these failures requires connecting user interactions, spoken feedback, focus transitions, and source code.

**Tabwise is an AI-assisted accessibility debugging and repair workflow built around what users actually experience.**

Developers can record and save keyboard journeys, inspect screen-reader observations, identify failures, review source-level repairs, and compare the original behavior with a repaired rerun.

Tabwise combines a React/Next.js workspace, genuine Windows NVDA capture, structured evidence, Meta Muse Spark reasoning, human-controlled patch review, and deterministic verification. Evidence and repair artifacts are source-bound and preserved for inspection.

In our measured Fernway seat-selection example, dismissing a dialog incorrectly moved focus to the document body. Meta Muse Spark connected the recorded behavior to the dialog-close handler and proposed a targeted correction. After reviewing and approving the exact patch, we executed a fresh native NVDA run.

The deterministic comparison reported **FIXED**: focus returned to the seat-selection button, and the tested surrounding keyboard and speech behavior was preserved.

Tabwise turns accessibility debugging from guesswork into an evidence-driven workflow where a proposed fix can be inspected and measured.

## More from Meta Global AI Developer Hackathon

- [Parent Loop](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2967)
- [VisionPilot](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2968)
- [Compinche](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2969)
- [Vellam Kaappaan](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2971)
- [MATRIX-code](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2972)
- [SheRules](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2973)

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