ENGINEERING

AI drift triage agent: Figma changes to prioritized Linear work

An agent reviews each batch of Figma library changes, reasons about engineering impact, drafts prioritized Linear tickets with effort estimates.

CategoryEngineering
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFigma library publish eventFigmaFigma
  • ActionAgent inspects change set and GitLab usageGitLabGitLab
  • LogicReason about impact; drop zero-impact cosmetic changes
  • ActionDraft prioritized Linear tickets with estimatesLinearLinear
  • OutputPost triage digest to SlackSlack

What it does

Turns raw Figma library changes into triaged engineering work. An agent inspects what changed, reads where those components are used in the codebase, judges blast radius and effort, then writes prioritized Linear tickets and a plain-language Slack summary the team can sanity-check before sprint planning.

When to use it

Use this when the volume of design-system change is too high to triage by hand. Instead of a flat list of diffs, you get reasoned priorities — what's a breaking change, what's cosmetic, and roughly how much work each migration is.

How it works

  1. 1A Figma library-publish event triggers the run.
  2. 2The agent fetches the change set from Figma and inspects affected component usage via GitLab search.
  3. 3It reasons about impact: breaking vs. cosmetic, number of call sites, suggested priority and effort.
  4. 4A logic gate drops changes judged purely cosmetic with zero call sites.
  5. 5The agent drafts prioritized Linear tickets with estimates and acceptance notes.
  6. 6It posts a triage digest to Slack summarizing what was filed and why.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FigmaFiles, frames, comments, assets.
  2. 2
    Connect GitLabRepos, MRs, pipelines, registry.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.