How do AI Employees keep dependencies current and proven green?
A dependency upgrade AI Employee that runs on a weekly schedule to find what's behind, apply the upgrades on a branch, install clean, and run the full test suite in your own environment. It opens a PR only when the change is green, and never merges it itself.
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Dependencies drift. Left alone, a project falls months behind, security patches pile up, and the eventual upgrade turns into a large, risky change nobody wants to own. The usual version bump bots open a PR for every package but can't tell whether a bump breaks anything. That check still falls to a person, so the PRs queue up unreviewed and the project drifts anyway. The common fixes are incomplete. Ignoring upgrades until something forces the issue turns a routine bump into a migration. Merging bot PRs on green CI trusts whatever tests already exist, not that the upgrade is actually safe. Doing it by hand is reliable but slow, and it's the first thing dropped when the team is busy.
On a weekly schedule the dependency upgrade AI Employee starts from a clean checkout of the default branch, checks which dependencies are behind and how far, applies the upgrades on a branch, installs clean, and runs the full suite in your own environment. It opens a PR only when the change is green, with the bumps grouped and the changelog attached, and a named human merges. A bump that breaks a test never becomes a PR; it comes back flagged with the failure.
See exactly how the work gets done.
Runs on a weekly schedule
A run fires once a week and starts clean inside your own environment, seeded with a fresh checkout of the default branch. Nothing carries over between weeks, and independent upgrade sets can run in parallel.
Carries your upgrade playbook
Which packages are pinned on purpose, how to run the suite, the order to apply major versions in, and migrations that have bitten before travel with it as a skill. When an upgrade needs a manual step, it's written down and applied on the next run.
Connects to the codebase and CI, with permissions you set
It reads the manifests to resolve what's behind, updates the lockfile and installs clean on a branch, runs the full suite (unit, integration, and e2e) inside your environment, and opens a PR on GitHub. Credentials stay in memory, never written to disk, never exposed to the model.
Proves it green before it asks
It opens a PR only when the suite passes. A failing upgrade is dropped or split, not pushed for a human to debug, so a bump that breaks a path fails in your environment rather than in review.
Opens the PR, never merges
It opens the pull request and stops. It never merges and never pushes to the default branch; a named human owns the merge. Reviewers see a green change with the changelog attached instead of a bump to check out and test by hand.
Runs in your environment
Every run is isolated inside your own infrastructure on its own branch; it can install, resolve, and run the suite to prove an upgrade, and only the branch and result leave it.
Permissions you set
The GitHub and CI credentials stay in memory, injected at run time, never written to disk, never exposed to the model or the logs.
Green only
It opens a PR only when the full suite passes. A failing upgrade is dropped or split and comes back flagged, never pushed for a human to debug.
Opens, never merges
It opens a pull request and stops. It never merges and never pushes to the default branch; a named human owns the merge.
You own the rules
The upgrade playbook, pinned packages, skills, and permissions are yours, versioned and changed on your terms, not in a vendor dashboard.
Dependencies stay current without anyone scheduling the work, and the upgrade PRs that land in review have already been run against the full suite. Reviewers see a green change with the changelog attached instead of a bump they have to check out and test by hand.
Weekly
Upgrades proposed on a schedule, not when something breaks
Green only
PRs opened only after the full suite passes
Human merge
The AI Employee proves the change; a person decides
Our free AI audit shows you where AI fits, what your security risks are, and gets your first AI employee working.
How do AI Employees keep your docs in sync with the code?
Sweeps the code merged each day, rewrites the docs those changes touched, and opens one reviewable pull request. Publishing waits for a human merge.
×How do AI Employees test every pull request before a human reviews it?
Checks out every pull request, runs the suite, exercises the change through the edge on a test deploy, and posts the result. It stays off production, leaving the merge to a person.
×How do you get a postmortem drafted the moment an incident resolves?
Reconstructs the incident timeline, correlates it against deploys and log spikes, and opens a structured postmortem as a doc PR. It drafts, and the team finalizes.
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