Your AI agents are building the wrong thing.
Karl helps you scope the work your agents can't scope themselves. You bring the idea. Karl brings context from your codebase, Jira, Confluence, and Figma.
Connect in 2 minutes. Your code stays on your infrastructure.
AI agents are only as good as their input.
Your team writes a ticket in 10 minutes. The agent codes it in 10 minutes. Then it takes days to fix what the agent got wrong. The bottleneck was never the code. It was the spec.
Context-blind
Agents don't know your team already built something similar last sprint, or that the API they need already exists in your docs.
They build from scratch what already exists.
Spec-starved
A two-line Jira ticket becomes 200 lines of code built on assumptions. No edge cases. No guardrails. No awareness of existing patterns.
They fill gaps with guesses.
Rework loop
PR review catches what the spec missed. Dev rewrites. Reviewer re-reviews. The 10-minute generation becomes days of back-and-forth.
Speed without accuracy is just faster rework.
Karl fills the gap between your idea and your agent's first line of code.
Pulls context from everywhere
Before you typeKarl connects to your GitHub repos, Jira board, Confluence space, and Figma files. It indexes your codebase patterns, past ticket structures, API docs, and design specs. When you start talking, Karl already knows what exists.
Interviews you with the right questions
2–5 minNot a form. A conversation. Karl asks targeted questions based on what it found in your codebase. Every question is grounded in reality, not templates.
Catches blind spots proactively
During the sessionKarl flags things you didn't think to ask about. Edge cases from your Figma specs. Patterns from past tickets. Dependencies you'd discover halfway through implementation. These surface before a single line of code is written.
Produces agent-ready output
DoneTwo artifacts. A Jira ticket with acceptance criteria, edge cases, and dependencies. And an agent handoff optimized for AI agents with codebase context, guardrails, and definition of done.
Without Karl
With Karl
This is what your agent receives instead of a two-line ticket.
A Jira-ready ticket for your board. An agent handoff for your AI agent. Both generated from the same 5-minute session, both grounded in your actual codebase.
Add promotional banner to homepage
As a marketing team member, I want to display a promotional banner on the homepage so that visitors are aware of our seasonal campaign.
Acceptance Criteria
- AC1Banner displays full-width above the fold
- AC2Copy and CTA link are editable via CMS
- AC3Dismiss button persists choice for 24h (cookie)
- AC4Banner respects reduced-motion preferences
- AC5A/B variant support via feature flag
Edge Cases
- No active campaign → banner hidden, no layout shift
- CMS fields empty → fallback to default copy
- Cookie expired → banner reappears
- Mobile viewport → single-line copy, stacked CTA
Related
PROJ-98Dismissible tooltip patternDependencies
| 1 | # Add promotional banner to homepage |
| 2 | |
| 3 | Add a dismissible promo banner that pulls copy from |
| 4 | the CMS and supports A/B testing via feature flags. |
| 5 | |
| 6 | ## Context |
| 7 | |
| 8 | - CMS endpoint: /api/v2/banners (already exists) |
| 9 | - Feature flags via LaunchDarkly (SDK already init'd) |
| 10 | - Design tokens in src/styles/tokens.ts |
| 11 | - Existing Banner component is deprecated. |
| 12 | Build fresh in src/features/promo/ |
| 13 | |
| 14 | ## Guardrails |
| 15 | |
| 16 | - Do NOT modify the global layout component |
| 17 | - Use existing FeatureFlag wrapper, not LD directly |
| 18 | - Cookie util at src/lib/cookies. Don't add js-cookie |
| 19 | - All animations must respect prefers-reduced-motion |
| 20 | |
| 21 | ## Done when |
| 22 | |
| 23 | - [ ] Banner renders from CMS data |
| 24 | - [ ] Dismiss persists 24h via cookie |
| 25 | - [ ] A/B variant renders based on feature flag |
| 26 | - [ ] Zero layout shift (CLS) when banner loads |
Every highlighted line came from your codebase, your docs, or your ticket history. No agent could discover this from a two-line prompt.
Exports to Jira wiki markup, Markdown, or JSON.
Connects to your stack in 2 minutes. Reads everything.
Karl indexes your GitHub repos, Jira board, Confluence space, and Figma files before the first session. Every question it asks and every output it produces is grounded in what your team has actually built, decided, and designed.
1,247 files indexed
- Existing components and utilities
- Naming conventions and patterns
- Recent PRs and what changed
89 tickets analyzed
- How your team writes acceptance criteria
- Common edge cases in past tickets
- Dependencies and blockers
34 pages parsed
- API documentation and endpoints
- Architecture decisions
- Team conventions and standards
12 design files synced
- Component specs and variants
- Responsive breakpoints
- Design token mappings
“Our agents went from 3 rounds of PR review to 1. The code wasn't better. The input was.”
Fix the input. Fix the output.
Your agents are fast. Karl makes them accurate.