Release Notes Manager

My Role — Sole Designer & Product Lead

I owned this project end-to-end as a single-person design team, responsible for:

– Defining the documentation problem and release workflow gaps
– Designing the full release management information architecture
– Mapping Jira and AI constraints into UX patterns
– Creating all interaction flows and UI states
– Designing the design system for light and dark modes
– Writing UX, AI prompt, and implementation specifications
– Aligning AI output structure with review, approval, and publishing logic

There were no additional designers, product managers, or UX teams involved — I handled the entire project independently from concept to delivery.

01 — The Problem

Release documentation at Smarteeva was fully manual and increasingly unscalable.

Every sprint, release managers and product teams had to compile release notes by hand from Jira, Slack, and commit logs. As product complexity grew across CAP, BASE, and RMP packages, the process became slow, inconsistent, and error-prone.

❌ What users struggled with

• Engineers wrote Jira stories inconsistently

• Jira descriptions were overly technical and not user-facing

• No standard release format across packages

• Managers rewrote content every sprint

• Information was scattered across multiple tools

• PDF exports required copy-paste and manual formatting

• Reviews and approvals happened late

Resulting business friction

• Hours wasted every release cycle

• Inconsistent communication to customers

• High dependency on engineering teams

• Last-minute rewrites and delays

• Poor visibility into release readiness

The Opportunity

Create a release management system that can:

✔ Generate readable release notes automatically from Jira
✔ Enforce consistent structure across all packages
✔ Support multi-sprint and multi-version releases
✔ Allow human review and approval before publishing
✔ Publish directly to documentation
✔ Export branded PDFs without manual effort

02 — Users & Needs

Primary Users

• Release Managers

• Product Owners

• QA Leads

• Engineering Managers

• Implementation & Support Teams

Core Needs

• “Generate release notes without rewriting Jira.”

• “Combine multiple packages into a single release.”

• “Review and approve AI output safely.”

• “Export clean PDFs for stakeholders.”

• “Maintain consistency across every release.”

Release Notes Manager needed to be predictable, reviewable, and scalable — not just automated.

03 — Goals

Business Goals

• Reduce release documentation effort

• Standardize release formats across teams

• Reduce reliance on engineering for documentation

• Improve release communication quality

UX Goals

• Deterministic AI output with no surprises

• Clear review and approval workflow

• Support complex, multi-package releases

• Fast editing, regeneration, and export

• Strong governance and trust controls
  
  

04 — Architecture Overview (Simplified)

The Release Notes Manager is designed as a two-phase system:
Generation & Publishing, followed by Export & Distribution.

The system intentionally separates AI generation from external sharing to ensure accuracy, governance, and predictable outputs.

Phase 1 — Generate & Publish

• Users select packages and sprints

• Jira stories are imported and normalized

• AI generates structured release notes

• Content is validated and published to the documentation site as the single source of truth

Phase 2 — Export & Share (No Code Required)

• Managers load already published release notes

• Packages, sprints, and sections are selected

• Export lists can be reordered or trimmed

• Final outputs are generated as:

  • Branded PDFs

  • Public shareable links (optional expiry)

Important:
The export flow never regenerates AI content.
It only consumes already published release notes, ensuring consistency, trust, and auditability.

05 — UX Strategy

Key UX Priorities

Trust over automation
AI never auto-publishes. Review and approval are mandatory.

Predictable structure
Every release follows the same schema across teams.

Enterprise scalability
Designed for large releases spanning multiple packages and versions.

Minimal cognitive load
Clear hierarchy, restrained color usage, and focused layouts.

06 — Key Screens

Screen 1 — Release Dashboard

• Overview of ongoing and past releases

• Approval status and ownership

• Jira sync health

• Quick access to drafts and exports

Acts as a single source of truth.

Screen 2 — AI Release Notes Generator

• Package and sprint selection

• Prompt configuration

• Deterministic AI generation

• JSON-backed output preview

Transforms raw Jira stories into structured content.

Screen 3 — Configuration & Export Selection

• Multi-package and multi-version selection

• Reordering releases before export

• Export list management

Eliminates manual compilation across teams.

Screen 4 — Review & Approval Flow

• Public vs internal notes separation

• Jira-linked review

• AI regeneration per item

• QA sign-off and final approval

Prevents hallucinations and ensures accountability.

Screen 5 — Jira Integration

• Authentication and scope control

• Issue-type filtering

• Label-based imports

Ensures clean, reliable inputs.

07 — Design System

1. Design Principles

• Clarity over decoration

• Predictability over creativity

• Governance-first AI UX

2. Color System

Optimized for light and dark modes.

Primary
Purple family — actionable but restrained

Neutrals
900 → 700 → 500 → 400 → 100
Inspired by Material elevation hierarchy

Semantic Colors

• Green — approved / completed

• Yellow — draft / pending

• Red — errors / blockers

• Blue — informational states

3. Typography

Inter

• High x-height

• Excellent readability

• Ideal for dense enterprise UI

4. Accessibility

• WCAG AA contrast

• 48px touch targets

• Minimal motion

• Colorblind-safe palette

08 — Impact

Quantitative

• Release creation time: 2–3 hours → 5–7 minutes

• Consistency improved by ~90%

• Manager rewrite time reduced significantly

• Multi-package export: ~45 minutes → under 1 minute

Qualitative Feedback

“This finally removed the chaos from release notes.”
“We don’t rewrite Jira anymore.”
“Publishing feels controlled and reliable now.”

09 — Challenges & Learnings

Working independently required combining product strategy, UX thinking, AI behavior, and enterprise constraints into a cohesive system.

Challenges

• Enforcing deterministic AI output

• Supporting different package structures

• Designing scalable review flows

• Preventing over-automation

What I Learned

• How to design AI-assisted documentation workflows

• How to balance automation with human oversight

• How to structure AI output for enterprise trust

• How to replace engineering-heavy processes with scalable systems

10 — Flow Chart

The flow below illustrates how Release Notes Manager separates AI generation, publishing, and external distribution into a predictable, enterprise-safe workflow.

Key principles illustrated in this flow:

• AI generation happens only once during the creation phase

• All release notes are reviewed and published before they become shareable

• The export flow is designed for non-technical users

• External outputs never regenerate or modify content

Important:
The export process only consumes already published release notes.
It does not re-run AI generation, ensuring consistency, trust, and auditability.

11 — Final Reflection

This was a fully self-directed project — every UX decision, architectural insight, and design detail was created solely by me.

Release Notes Manager didn’t just automate documentation — it standardized, governed, and scaled it.

It strengthened my ability to design:

• AI-assisted enterprise workflows

• Complex internal tools

• Governance-first AI UX

• Scalable design systems