DEVOPS

Weekly build-slowdown investigation with agentic bisect

Weekly, an agent identifies the project with the worst build-minute regression, walks the recent commit and dependency changes from GitHub to hypothesize the cause.

CategoryDevOps
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule triggers the agent
  • ActionFind worst-regressing project and slowdown window in VercelVercelVercel
  • ActionRead commits, PRs, and lockfile diffs from GitHubGitHubGitHub
  • LogicReason over evidence to rank likely causes
  • OutputPost root-cause brief to SlackSlack

What it does

Once a week, this agent finds the Vercel project whose build minutes regressed most, then investigates why. It pulls the deployment history from Vercel to locate the commit range where the slowdown began, reads the GitHub commits and lockfile diffs in that window, and reasons about likely culprits — a heavy new dependency, a slow build script, an exploding bundle. It writes a plain-language root-cause brief with a recommended fix.

When to use it

Use it when you keep seeing build-time alerts but nobody has time to manually bisect which change caused them. This does the detective work and hands engineering a starting hypothesis instead of a raw number.

How it works

  1. 1A weekly schedule triggers the agent.
  2. 2It queries Vercel for build durations and picks the worst-regressing project, pinpointing the deploy where the climb started.
  3. 3It reads the GitHub commits, PRs, and lockfile changes across that build range.
  4. 4It reasons over the evidence to rank candidate causes and draft a remediation suggestion.
  5. 5It posts the root-cause brief to Slack for the owning team to action.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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