Use case

AI Agents for Dependency Upgrades

Name: Fleet
Author: Fleet

Dependency upgrades are maintenance work that slips. Each individual upgrade is low priority. Collectively, falling behind creates compounding risk: security vulnerabilities in old packages, incompatibilities between packages that have diverged, and eventually a forced upgrade that requires significant effort because so many versions were skipped.

The work pattern for a dependency upgrade is: check what changed in the new version, update the version pin, run tests, fix any breakage caused by the upgrade, open a PR. This is repetitive and time-consuming for a human. For a small change, it takes longer to context-switch to it than to do it.

How it works with an agent fleet

A dependency-upgrade agent runs on a schedule. It checks for outdated dependencies, updates them, runs tests, fixes straightforward breakage, and opens a PR.

agents:
  - name: dep-updater
    role: backend-developer
    model: claude-sonnet-4-6
    schedule: "0 9 * * 1"  # Monday 9am

The agent's prompt lives at .fleet/prompts/dep-updater.md — Fleet resolves it by convention from the agent name, so there is no prompt: field in config. The dep-updater prompt specifies how to check for outdated dependencies in your language ecosystem, what changelog sources to check, and what categories of breakage the agent is authorized to fix versus escalate.

The fleet pattern

Dependency agent runs on a cron schedule, opening one PR per dependency update. Small PRs are easier to review and easier to revert if they cause a problem. A tech-lead reviews for any breaking API changes that the agent did not catch in tests. You can also file urgent security-patch tickets so an agent picks them up immediately rather than waiting for the next scheduled run.

Guardrails that matter here

One dependency per PR — makes it easy to bisect if a dependency update causes a production issue
Agent cannot merge — all upgrades go through tech-lead review to catch breaking API changes
Run-time (duration) budget prevents extended debugging on a complex upgrade; the agent escalates rather than continuing indefinitely

Who this is for

Engineering teams running on Node.js, Python, Go, Ruby, or any language with a package manager where dependency drift is a known risk. Also useful for teams that need security patches applied quickly without waiting for the next sprint.

Frequently asked questions

What happens when the upgrade breaks tests?

The agent attempts to fix straightforward breakage — updated API calls, renamed imports. If it cannot fix the tests within its run-time budget, it opens a PR with the broken state and a description of what it tried, so a human engineer can take over from a known starting point.

Can the agent handle major version upgrades?

Major upgrades with breaking changes are better treated as migration tasks with more detailed specifications. The dep-updater prompt can be configured to escalate major version upgrades for human planning rather than attempting them automatically.

Related use cases

AI Agents for Security Review →AI Agents for DevOps and CI →AI Agents for Tech Debt →

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