Vector

The self-evolving AI agentic harness that The self-evolving AI agentic harness that has an agent of its own, can have a judge check its work before calling it done, sets up your database and deploys it, runs subagents in batches of up to eight, lets a trusted teammate join from the terminal, runs in your terminal too, prices each run from the tokens your provider reported, hosts Claude, Codex and Cursor alongside its own agent, and is planning Vector Velocity, a model with 550B+ parameters.

An AI agentic harness for the repository on your computer: plan, edit, run and ship with Vector's own agent. Low-cost by design, and self-evolving with Vector Brain, from desktop 1.99.110.

Free with a Vector account. macOS, Windows, and Linux.

Vector
Testing

The three boundaries are staged: fingerprint-bound trust for a repository's executable configuration, a repository policy that can only narrow permissions, and a trust check before a repository's MCP servers start. Focused tests pass on the staged tree.

Next I will integrate the latest origin/main, re-run the checks and ask a judge for a verdict before anything is committed.

Interrupted

Session costChatGPT plan58.8M tokens

continue

Defining success criteria and original request

Specifying detailed success criteria for security patch

Success means: the staged security controls remain intact with no Critical/High bypasses; the patch integrates cleanly with the latest origin/main; focused tests, package typechecks, generated-client checks, the app build, and a browser smoke check pass; an independent judge returns PASS; and the resulting conventional commit is pushed with remote main pointing to that exact commit. Unrelated untracked WIP must remain untouched.

· 33K tokens · 1 running task

  • Audit the staged security patch and repository state , in progress
  • Fetch and integrate the latest origin/main in isolation , not started
  • Re-run focused verification on the integrated tree , not started
  • Obtain an independent judge PASS , not started
  • Commit, update main, push, and verify the remote commit , not started

An interactive preview — switch the branch, open Tasks, Changes or the terminal, fold the todos. The desktop app connects it to your real repository and agents.

An agent that learns you and your company.

Vector Brain: every session starts from what the last one learned.

Vector Brain is Vector's own technology. Give it your specs, PDFs and docs once. It reads them on your computer, links them to the code that implements them, and keeps what proved useful in runs that passed. Then, offline, with a code graph and retrieval of its own, it gives your model only the few lines of them that bear on each request.

Your prompts, your data, your Vector: the brain lives on your computer, you choose who runs the model for each request, and you can see, undo or erase what it learned. Free models labelled May train on your prompts are the exception.

  • A brain for each repository

    Rules, memory, what the agent learns and the documents you give it, in one local graph. It adds to it as it works, and one click undoes anything it learned.

  • Linked to your code

    Specs, PDFs and docs are read into requirements, limits and decisions, linked to the code they name, and flagged when the code drifts from them.

  • Only what the task needs

    The tokenomics engine sends the few cards a task needs and stops at its budget. "hi" carries no memory at all, so it costs nothing extra.

On Vector's knowledge eval of 19 October 2026, recall through code links brought in the governing requirement for 40 of 40 tasks, against 1 of 40 by keywords alone, at 131 tokens a request on average. The eval is five short specs and 58 requests written alongside the feature, not an independent benchmark.

Read about documents and code links

Inside the app

More of the app, rebuilt to click.

Not screenshots: like the window at the top of the page, each one below is the desktop app redrawn in HTML from the app's design and run on sample data, so you can click it. The composer stays a picture — there is no repository or model behind this page.

Built-in browser

A browser beside the conversation.

Vector opens pages in a panel next to the session, so the agent can load your app while you watch it. Go back, reload, or type a path: the pages here are small drawings of this site.

Vector
Testing

The three boundaries are staged: fingerprint-bound trust for a repository's executable configuration, a repository policy that can only narrow permissions, and a trust check before a repository's MCP servers start. Focused tests pass on the staged tree.

Next I will integrate the latest origin/main, re-run the checks and ask a judge for a verdict before anything is committed.

Interrupted

Session costChatGPT plan58.8M tokens

continue

Defining success criteria and original request

Specifying detailed success criteria for security patch

Success means: the staged security controls remain intact with no Critical/High bypasses; the patch integrates cleanly with the latest origin/main; focused tests, package typechecks, generated-client checks, the app build, and a browser smoke check pass; an independent judge returns PASS; and the resulting conventional commit is pushed with remote main pointing to that exact commit. Unrelated untracked WIP must remain untouched.

· 33K tokens · 1 running task

  • Audit the staged security patch and repository state , in progress
  • Fetch and integrate the latest origin/main in isolation , not started
  • Re-run focused verification on the integrated tree , not started
  • Obtain an independent judge PASS , not started
  • Commit, update main, push, and verify the remote commit , not started

Agent Dashboard

Every workspace on one board.

Each isolated workspace you start lands here with its live status, the files it touched and its pull request. Search, filter by status, runtime or pull request, or switch the board to a list.

Agent Dashboard

Every workspace, agent, and review in one place

0 running 0 need you 0 done

0 agents0 files touched

No agents yet

Start an isolated workspace and its live status will appear here.

Privacy

Your code lives on your computer.

Vector's servers keep no copy of your prompts, Vector never trains on your code, and you pick who runs the model.

  • Local first

    Sessions, history and checkpoints are saved on your computer, and desktop dictation is transcribed there too.

  • Straight to your provider

    With your own key, prompts go straight to that provider under its terms, never through Vector, and a model on your own computer keeps them there.

  • No copy on our servers

    Vector's servers never keep your prompts or code, except what you choose to send: a share link you publish, public for 30 days at most, or a bug report.

  • Never trained on

    Vector collects nothing for training, and Vector Velocity, our planned model with 550B+ parameters, won't be trained on customers' code.

  • On Vector's own models

    Codium, coming soon, routes only to endpoints OpenRouter records as zero data retention. Requests to free models whose providers don't train ask them not to train on your prompts, and free models whose providers may train are labelled May train on your prompts and sent only after you accept that once. Providers of free models may still keep prompts under their own policies.

  • Counts, not content

    Usage counts are totals like sessions and tokens, never your prompts, code, file names or output. You can switch them off, and crash reports are off by default.

Read the privacy policy

An agent you can trust
is one that shows its work.

23 of them, in detail — code review, the browser, coordinated agents, the judge, the ledger. Every card opens the documentation behind it.