Stack replacement

Replacing Jira and Slack

Engineering teams on Jira and Slack have a tracker, a chat tool, and specs living in ticket descriptions.

What the move costs

Jira and Slack cover tracking and conversation but leave no home for written specification, so requirements end up in ticket descriptions and channel threads. Polaris adds a docs tree alongside tasks and chat. Slack is in the connection catalog and can stay. Jira has no importer, so live issues are rebuilt by hand and the closed history stays in Jira, read-only.

Slack
Connects, no export
Jira
No importer, manual rebuild
What you gain
A docs layer this stack never had
Billing after
~$2 per human-hour delivered

The ticket description is doing a job it is bad at

In a Jira and Slack shop, the specification is whatever is in the ticket description on the day someone picks it up. That field was designed to describe one unit of work, and it is being asked to hold context, rationale, edge cases and the reason a previous approach was abandoned.

So the rationale goes to Slack instead, where it is searchable in theory and gone in practice. Six months later somebody asks why the retry logic works the way it does, and the honest answer is that three people knew and two of them have left.

The gap is not tracking. Jira tracks well. The gap is that this stack has nowhere durable to write, and no amount of ticket hygiene fixes that.

Where each piece lands

Stays roughly as it is

  • Slack, connected once for the organisation and left alone
  • GitHub, also in the connection catalog, so pull requests stay where they are
  • Closed Jira issues, readable in Jira with write seats dropped
  • Whatever CI and deploy tooling reads the repo rather than the tracker

Changes shape

  • Live issues become tasks in a workstream, retyped rather than imported
  • Ticket descriptions get split: the work becomes a task, the reasoning becomes a doc
  • Jira automations that post to Slack are replaced by Inbox suggestions
  • Anything that depended on workflow transitions needs a different answer

Migration in four stages

  1. 1

    Write down the three things everyone asks about

    Before moving any ticket, create three docs for the questions your team answers repeatedly in Slack. Deploy process, on-call expectations, and whichever part of the system nobody understands. This is the layer the stack was missing, and building it first proves the point faster than any tracker migration.

  2. 2

    Connect Slack and GitHub

    Both are in the connection catalog and authorised once, org-wide, with credentials stored server-side. Slack messages start arriving as prefilled task suggestions in the Inbox. AI workers you hire later can read both without you granting anything again.

  3. 3

    Move the current sprint, not the backlog

    Export the sprint from Jira to CSV for reference and create the tasks in Polaris by hand. Leave the backlog behind on purpose. If an item matters, someone will raise it again within a fortnight, and if nobody does, it was never going to be built.

  4. 4

    Give a worker the boring half of the sprint

    Hire an AI worker with GitHub, Slack and web search, and assign it release notes, dependency triage, or the bug reproduction nobody wants. A machine wakes per task, ticks its own acceptance criteria, and posts the work as a comment with files attached. An engineer reviews and closes it.

The Jira features with no equivalent

Check this list before you commit to anything.

Jira featurePolaris equivalentWhat to do
Workflow schemes and transitionsNoneKeep Jira for anything a deploy gate reads
Custom fields and screensLabels and lanesRebuild only the two or three fields you filter on
JQL saved filtersNoneRebuild as lanes, which is coarser and usually enough
Sprint and velocity reportsNoneExport as PDF before dropping seats
Issue linking and epicsWorkstreams and lanesFlatter model. Deep epic trees do not survive it
Automation rulesAI workers assigned standing tasksDifferent mechanism, so plan a rewrite rather than a port

Questions people ask

+Can we keep Slack and still use Polaris chat?

Yes, and most teams should for the first month. Slack connects to Polaris rather than being replaced by it, so messages arrive in the Inbox as task suggestions while the channels keep working. Teams that try to move conversation on day one usually end up with two half-used chat tools.

+Is there any way to import Jira issues in bulk?

Not into Polaris. Jira has no importer and is not in the connection catalog. Export to CSV for your archive, then create the live items by hand. A fifteen-person team's active sprint is typically two hours of typing, and the resulting board has no dead tickets in it.

+What replaces our Jira automation rules?

AI workers assigned standing tasks, which is a different mechanism rather than a port. A rule that moved an issue on a status change has no equivalent. A rule that generated a weekly summary does, because a worker can be given that job with real tool access and it delivers the summary as a comment with a file.

+Where do specs live in Polaris?

In Docs, a nested tree with a block editor, markdown shortcuts, to-dos and sub-pages. Files are versioned and support review and comments. It is the layer a Jira and Slack stack does not have, and for most engineering teams it is the part of this migration that changes daily life the most.

+How does the pricing compare to Jira plus Slack?

Jira and Slack are both per-seat and both grow with headcount, including for people who barely open them. Polaris software is free with no seat count, and billing happens only when an AI worker delivers work, at roughly two dollars per human-equivalent hour. The cost pages have the current list prices with the date they were checked.

Your next hire takes 60 seconds.

The software is free — unlimited people, tasks, workstreams and docs. You pay only for work an AI worker actually delivers, itemised by the hour.

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