AI Ticket Creation: Better Requirements in Minutes, Not Hours

Writing good tickets takes hours. Our AI chat interface scans your codebase and knowledge base to generate well-defined tickets — technical or business-focused — ready to assign.

The Old Way: Vague Tickets, Endless Clarification

You've seen this pattern:

Title: Fix login bug
Description: Users are having trouble logging in. Please fix.

An engineer picks this up. What happens next?

• "Which users? All users or specific ones?"
• "What error are they seeing?"
• "Which login flow — email, OAuth, SSO?"
• "Is there a specific browser or device?"
• "Can you share reproduction steps?"

Three days of back-and-forth before anyone writes a line of code.

The New Way: AI That Knows Your Code

Synlets Ticket Creation is a chat interface connected to your entire project context:

• Your repositories — The AI sees your codebase structure, patterns, and conventions
• Your knowledge base — Confluence, Notion, architecture docs, API specs
• Your existing tickets — Past implementations, decisions, and context

When you describe what you need, the AI doesn't just capture your words. It scans the relevant parts of your codebase, references your documentation, and generates a ticket that's actually implementable.

How It Works

1. Describe What You Need

Just talk to it like you'd explain to a colleague:

"We need to add rate limiting to the payments API. Users are hitting our Stripe integration too frequently and we're getting throttled."

2. AI Pulls Context Automatically

The agent scans your codebase to understand:

• Where the change belongs — Which files, modules, or services are relevant
• Existing patterns — How similar features were implemented before
• Dependencies — What other code might be affected
• Technical constraints — API structures, database schemas, authentication flows

It also references your knowledge base:

• Architecture decisions that affect the implementation
• Coding standards and conventions
• API documentation and specs
• Previous tickets that solved similar problems

3. Get a Well-Defined Ticket

The output is a complete, implementable ticket:

Title: Add rate limiting to Payments API endpoints

Description:
Implement rate limiting for the Stripe integration endpoints to prevent
API throttling. Based on current usage patterns and Stripe's limits.

Acceptance Criteria:
- [ ] Add rate limiting middleware to /api/payments/* routes
- [ ] Limit: 100 requests per minute per user
- [ ] Return 429 Too Many Requests with Retry-After header when exceeded
- [ ] Log rate limit violations to monitoring (follows existing pattern in
      src/middleware/logging.ts)
- [ ] Add rate limit status to response headers (X-RateLimit-*)

Technical Notes:
- Use existing Redis instance for rate limit storage (see config/redis.ts)
- Follow middleware pattern established in src/middleware/auth.ts
- Stripe webhook endpoints should be excluded from rate limiting

Related Files:
- src/api/payments/routes.ts
- src/middleware/rateLimit.ts (create new)
- src/config/redis.ts

Related Documentation:
- API Rate Limiting Standards (Confluence)
- Stripe Integration Architecture (Notion)

All the context. All the technical details. Ready to assign — no clarification needed.

Technical or Business — Your Choice

The AI adapts to who's writing the ticket.

For Product Managers

Describe the user problem and business outcome. The AI translates it into technical requirements:

"Users want to see their subscription status on the dashboard. They keep asking support when their plan renews."

For Engineering Leads

Describe the technical change. The AI fills in implementation details:

"We need to migrate from REST to GraphQL for the user profile endpoints."

For Executives and Founders

Describe the high-level goal. The AI breaks it down into actionable work:

"We need to be SOC 2 compliant by Q2."

Then What?

Once you have a well-defined ticket, you can:

Assign to an AI Agent

Label the ticket and let a Synlets Project Agent implement it. The agent reads the detailed requirements you just generated and delivers a PR.

Assign to an Engineer

Share the ticket with your team. Engineers get everything they need:

• Clear acceptance criteria
• Technical notes on implementation approach
• References to existing code patterns
• Links to relevant documentation

Review and Iterate

Not quite right? Chat with the AI to refine:

• "Can we also handle the edge case where users have multiple subscriptions?"
• "Actually, let's use a different rate limit for enterprise customers."
• "Add a note about backward compatibility for the v1 API."

The ticket updates in real-time.

The Result: Better Requirements, Faster Shipping

It's Not Just About Speed

The deeper benefit: tickets that actually match your codebase.

When the AI generates a ticket, it's not guessing. It's looking at your actual code, your actual patterns, your actual documentation. The ticket isn't a wish list — it's a blueprint that fits your system.

Engineers stop saying "that's not how our codebase works."

PMs stop rewriting tickets after technical review.

Everyone ships faster because the requirements are right the first time.

Getting Started

1. Connect your repositories — GitHub or GitLab, so the AI can scan your codebase
2. Add your knowledge base — Confluence, Notion, or any docs you'd share with a new hire
3. Open the ticket chat — Describe what you need in plain language
4. Review and assign — Get a detailed ticket, then assign to agents or engineers

No more vague tickets. No more endless clarification. Just clear requirements, ready to build.