Use case
Bug ticket in. PR out.
Agents pick up Jira or Linear tickets, reproduce bugs on your real stack, fix the code, run tests, and open a pull request.
Why this is hard
Small bugs are expensive to pick up
A one-line fix still costs a context switch, a branch, a local repro, and a review. That overhead is why the backlog has three hundred of them.
Reproducing is most of the work
By the time you have the right data, the right account, and the right sequence of clicks, the actual fix is often obvious.
Tickets rot
A bug filed six months ago may already be fixed, or may now be three bugs. Nobody wants to be the one to find out.
From ticket to pull request
The agent reads the ticket where it lives
Linear, Jira, or a GitHub issue, including the comment thread where someone already explained the workaround.
It reproduces on a real stack
It sets up the state the report describes and confirms the behavior. If it cannot reproduce, that is the answer and it says so.
It fixes, then proves the fix
The change comes with a test that fails before and passes after, so "fixed" is a claim you can verify.
It opens a pull request and links the ticket
The PR references the issue and includes the reproduction, so review does not start with archaeology.
What you get back
- Pull request
- Failing-then-passing test
- Reproduction steps
- Ticket comment with findings
What makes the fix trustworthy
Tickets stay in Linear, Jira, or GitHub
No new queue or label scheme — the agent reads the thread where someone already explained the workaround.
Snapshots that match the report
Seeded accounts and data get the agent to the situation the user described before it touches code.
A failing test written before the fix
The regression test proves the bug existed and that the change actually addresses it.
Who runs this
The moment I could trust that what comes back actually works and my only job was merging the PR, that was a huge change for us.
Matan KleymanCEO, ObertRead the full story →Each employee can be many agents, working in Salesforce, running web searches, and more. When an agent writes Python for analytics or a heavy calculation, we dispatch it to Islo and run the code in a sandbox. That is where our story began.
Barel TayouriCTO, Stealth AI startupAll customer stories →
Where teams go next
Common questions
Can an agent pick up bugs directly from Linear or Jira?
Agents can pick up work from Linear and Jira with scoped access through the Islo gateway.
Will the agent open a pull request after fixing the bug?
Yes. After reproducing the bug, applying a fix, and passing tests, the agent opens a PR with context from the ticket.
Can I jump in while the agent is working?
Yes. The computer keeps running. Use the CLI or dashboard to check logs, jump in, or take over.
What happens if the agent can't reproduce the bug?
The agent can return the steps, logs, and evidence it collected instead of guessing at a fix, so a developer can inspect the same environment and continue the investigation.
Does the agent verify the fix before opening a PR?
Yes. The workflow can rerun the reproduction, execute the relevant test suite, and check the application in a browser before it opens the pull request.