Guide for Jira
Planning is where engineering teams lose the most time. This is where AI Architect starts.
Senior engineers and tech leads spend hours on work that should take minutes, reading through old tickets to understand what went wrong before, figuring out what a one-line Epic description actually requires, mapping out which services will be affected and which ones have been fragile in the past.
AI Architect automates this work inside Jira. When an Epic or Story is created, AI Architect posts a detailed implementation plan directly as a comment on the ticket. Feasibility analysis, story breakdown, risk warnings, historical patterns from your team's own tickets — all generated in minutes, right where your team plans.
What gets posted on your ticket
When AI Architect analyzes an Epic or Story, it produces a structured Markdown implementation plan that covers:
Feasibility assessment — Is this viable given your current architecture? Which services are involved, and how stable are they? What's the blast radius if something goes wrong?
Story breakdown — For Epics, a full decomposition into Stories with acceptance criteria, dependencies, and recommended execution order across sprints.
Effort estimates — Both traditional and agentic estimates, with a breakdown of where AI tooling saves the most time and where it doesn't.
Proactive risk detection — Race conditions in concurrent flows, memory leak patterns, regression-prone areas, API rate-limiting gaps, security concerns. Each risk comes with a suggested mitigation drawn from your team's actual history.
Historical pattern insights — AI Architect references past tickets to flag issues your team has already encountered. For example: "A similar concurrency issue took 3 sprints to resolve in PROJ-456 — consider redesigning the locking strategy before implementing this."
Open questions — Technical decisions that need to be made before implementation begins, so they don't surface mid-sprint.
The plan is in Markdown. Engineers can paste it directly into Cursor, Claude Code, or any other coding agent to start implementation with full architectural context already loaded.
Setup
Enable AI Architect for your workspace
Contact [email protected] if AI Architect isn't already active for your workspace. For self-hosted setups, see the self-hosted installation guide.
Connect Jira
Bito supports two ways to connect with Jira, depending on where your Jira instance is hosted:
Jira Cloud: for Jira sites hosted by Atlassian (e.g.,
https://mycompany.atlassian.net).Jira Data Center: for Jira instances hosted on your own company domain or servers (e.g.,
https://jira.mycompany.com).
Connect Bito with Jira Cloud (hosted by Atlassian)
Navigate to the Manage integrations page in your Bito dashboard
In the Available integrations section, you will see Jira. Click Connect to proceed.
Select the option Jira Cloud. You will be redirected to the official Jira website, where you need to grant Bito access to your Atlassian account.
Click Accept to continue. If the integration is successful, you will be redirected back to Bito.
Connect Bito with Jira Data Center (hosted on your own server)
Navigate to the Manage integrations page in your Bito dashboard
In the Available integrations section, you will see Jira. Click Connect to proceed.
Select the option Jira Data Center (self-managed).
Provide connection details:
Domain URL: Enter the base URL for your Jira instance (e.g.
https://jira.mycompany.com).Personal Access Token: Enter a valid Personal Access Token with admin permissions. Read the official Jira documentation to learn how to create a Personal Access Token.
Click Connect to Jira. You will be redirected to your self-hosted Jira website, where you need to grant Bito access to your Jira account.
Click Allow to continue. If the integration is successful, you will be redirected back to Bito.
Enable the feature flags
Two flags control how AI Architect behaves on your tickets. Contact your Bito team to enable them — a self-serve UI toggle is coming soon.
Jira Analysis Enabled
On-demand analysis via @bito or /bito comments, or bito labels
Jira Auto Analysis Enabled
Automatic analysis on Epic/Story creation and update
Start with Jira Analysis Enabled if you want to try it manually first, then enable auto-analysis when you're ready to run it on all new tickets.
How to trigger AI Architect in Jira
Automatic analysis
When enabled, AI Architect listens for new Epics and Stories and posts the implementation plan automatically, no action needed from the ticket creator.
Triggered on Epic/Story creation or update.
Requires the Jira Auto Analysis Enabled flag to be on for your workspace. Contact Bito team at [email protected] to enable it.
You can download the plan (markdown file) and use it in your agentic tools (Cursor, Claude Code, etc.) to further update it or use the analysis.
On-demand analysis
Trigger analysis manually on any ticket by using any of the following in a Jira comment:
You can use the @bito, /bito, or #bito in Jira comment to ask Bito to make changes to the analysis or update based on your needs, or add more details to update the plan based on any new information.
Example:
Or by adding one of these labels to the ticket:
Requires the Jira Analysis Enabled flag to be on for your workspace. Contact Bito team at [email protected] to enable it.
What AI Architect knows about your team
AI Architect draws on two sources when it analyzes a ticket:
Your codebase — All your repositories, services, API endpoints, modules, and design patterns are indexed into a knowledge graph. AI Architect understands how your system fits together, not just what individual files contain.
Your Jira history — AI Architect analyzes the last 6 months of your team's tickets and categorizes recurring patterns: race conditions across subsystems, services with instability histories, security and credential issues, error handling gaps, API rate-limiting problems. This context is applied to every new ticket so your team doesn't repeat what's already been learned.
Which agent skills power the Jira integration
AI Architect works through purpose-built agentic skills. The two skills that run in Jira are:
bito-epic-to-plan — Triggered on Epics. Converts an approved Epic or PRD into a sprint-ready plan with multiple architectural approaches, then granular Stories with effort estimates and acceptance criteria.
bito-scope-to-plan — Triggered on Stories. Auto-scales its output — a full multi-workstream plan for complex Stories, a focused single-workstream plan for simpler ones.
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