WorkBox AI behaves more like a focused software engineer and operations assistant than a chatbot. It streams its desktop, takes on structured tasks, and works end-to-end on code, documents, prototypes or planning workflows — with every input and file optically ingressed, sanitized, and under your control.
WorkBox AI is a local AI worker that helps with the kind of work people do at a desk: writing and refactoring code, preparing documentation, exploring ideas, and supporting business operations tasks like reports, checklists and small tools.
WorkBox is designed around tasks, not endless conversation. You point it at a project or problem, describe the goal, and let it work inside a controlled desktop session instead of firing off one-shot prompts.
The aim isn’t to replace all work. It’s to offload the heavy lifting on parts that are repetitive, mechanical or exploratory, while you stay in charge of direction, review and approval.
Because WorkBox runs on a workstation, it sits next to your code, documents and tools. It doesn’t need to send your files to a remote API to be useful.
That makes it a good fit for internal projects, prototypes and environments where cloud AI is either not allowed or not trusted — but you still want serious AI help.
Early versions of WorkBox AI focus on a few concrete roles. They’re simple enough to understand, but powerful enough to be genuinely useful on real projects.
Point WorkBox at a codebase and a goal: clean things up, add tests, sketch a new tool or prototype a feature. You stay in control of commits and deployment.
Turn rough notes, TODO lists, transcripts or specs into material your team can actually read and act on.
Support repetitive operations work without giving the model a blank cheque: keep humans in the loop, but let WorkBox grind through the grunt work.
Uploading files to a WorkBox is not the usual “drag everything into a cloud chat” model. Inputs are structured, filtered and, in the full setup, can be delivered optically rather than piped straight into an online model.
In the WorkBox + GlassBox configuration, files and prompts can be transferred via structured optical bursts — the same philosophy as the GlassBox Isolator.
Even without the Isolator attached, the WorkBox is built with the assumption that ingress is explicit and governed, not a firehose.
The long-term goal is for WorkBox to operate mostly on sanitized, structured context instead of raw piles of sensitive information.
The worker can still be powerful and useful — it just doesn’t need a full copy of your life to do its job.
A WorkBox session should feel like working alongside a very fast but very literal colleague who lives on a dedicated workstation.
You describe the goal in plain language: which project or files, what constraints, and what “good” looks like. The task is logged as a structured job.
The AI runs inside the WorkBox desktop, generating code, drafts or analyses. You can watch the screen live or just review its outputs afterwards.
Nothing goes straight into production. You inspect diffs, drafts and suggestions, keep what you like and discard the rest.
Once you’re happy, you apply changes in your own tools, or queue follow-up tasks. The loop stays incremental and reversible by design.
WorkBox AI is an active R&D project. The priority right now is to make the core worker loop solid and safe before offering it as something others can rely on.