π AI Feature Intake Engine
Turn raw product requests into Jira-ready stories in under 1 minute, with humans in control
β The Problem
Great product ideas fail every day. Not because theyβre bad, but because they arrive too late, too vague, or lose context before reaching the backlog.
Typical intake issues:
- Requests come in via email, chat, docs, or forms
- PMs and TPMs spend hours rewriting and clarifying
- Context gets lost between stakeholders
- By the time it reaches Jira, urgency is gone
- Engineers get half-baked tickets β rework and delays
Speed without control is dangerous. Control without speed is expensive.
β The Solution
The AI Feature Intake Engine accelerates product request review without removing human judgment.
In under *β¦
π AI Feature Intake Engine
Turn raw product requests into Jira-ready stories in under 1 minute, with humans in control
β The Problem
Great product ideas fail every day. Not because theyβre bad, but because they arrive too late, too vague, or lose context before reaching the backlog.
Typical intake issues:
- Requests come in via email, chat, docs, or forms
- PMs and TPMs spend hours rewriting and clarifying
- Context gets lost between stakeholders
- By the time it reaches Jira, urgency is gone
- Engineers get half-baked tickets β rework and delays
Speed without control is dangerous. Control without speed is expensive.
β The Solution
The AI Feature Intake Engine accelerates product request review without removing human judgment.
In under 60 seconds, it:
- Summarizes incoming requests
- Breaks them into Jira-ready technical tasks
- Surfaces ambiguities early
- Requires explicit human approval before action
AI does the heavy lifting. Humans make the decision.
π§ How It Works (High Level)
Request arrives From Google Sheets, form, or intake source 1.
AI enrichment Gemini studies internal product features and architecture and converts raw input into:
- Architectural summary
- Clear technical sub-tasks
Human-in-the-loop review Reviewer:
- Reads a clean, readable summary
- Approves or rejects explicitly (no auto-creation)
Outcome
- β Approved β Jira-ready payload
- β Rejected β Context-aware rejection email
All of this happens before backlog pollution.
Architecture
The system is intentionally split into three independent workflows for clarity, safety, and scale.
1. Main Intake Flow (AI Generation)
Google Sheets β Filter β Google Drive Files β Gemini β Code β Email
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Reads feature requests from Google Sheets
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The workflow triggers when a new row is added in the Request Intake sheet
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Internal Google Drive documents, like product features and technical architecture, are analyzed first
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Gemini AI generate:
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Architectural summary
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Technical task breakdown
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Normalizes AI output into a strict internal schema
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Sends an email with a secure Review Draft link
2. Review Draft Flow (Human-in-the-loop)
GET Webhook β HTML Review Form β Respond to Webhook
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Opens a clean HTML review page
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Pre-fills AI-generated summary and tasks
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Reviewer can:
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Edit content
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Approve or reject
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Add rejection reason if needed
This step prevents deterministic AI behavior from pushing bad specs downstream.
3. Submission Flow (Decision Engine)
POST Webhook β IF β Jira / Rejection Email
- If approved β Create Jira issue
- If rejected β Send rejection email with feedback to the requester
- Fully auditable and reversible
No brittle automation. No blind Jira creation. No black-box AI behavior.
π― Why This Matters (TPM / Technical PM Perspective)
From a delivery standpoint:
- Late or unclear requests create downstream chaos
- Engineers lose trust in product signals
- Backlogs fill with low-quality tickets
- Roadmaps drift due to rework
This engine pulls quality forward:
- Faster intake β rushed decisions
- Context preserved at the point of review
- Clear ownership before Jira is touched
- Fewer surprises during delivery
This is decision acceleration, not task automation.
β±οΈ Real Impact
- β³ Intake review time: Hours β < 1 minute
- π Rework caused by unclear tickets: Significantly reduced
- π§ Human oversight: 100% preserved
- βοΈ Jira hygiene: Protected
π οΈ Built With
- n8n β workflow orchestration
- Gemini β structured AI summarization
- Google Sheets β lightweight intake source
- Google Drive β document repository
- Jira β final system of record
- Strict JSON schemas β deterministic AI output
- HTML-based review UI β no stray JSON, no confusion
Demo
π₯ Watch the full workflow demo on Youtube: π https://youtu.be/bt-PUd4Po6g
π₯ The walkthrough shows:
- Intake β AI processing
- Human approval step
- Jira-ready output
π€ Who This Is For
- Technical Product Managers
- TPMs / Delivery Leads
- Startup founders handling high request volume
- Teams tired of backlog chaos
- Anyone who wants AI speed without losing control
πΌ Need Help Getting Started?
Setting up the AI-Feature-Intake-Engine can be complex. I offer personalized setup sessions to help you get up and running quickly.
π Book a Setup Session
30-Minute Quick Help β $50 Perfect for quick questions, troubleshooting, or guidance on specific features. π https://cal.com/kavish-sekhri/30min
60-Minute Deep Dive β $100 Comprehensive setup assistance, configuration, and Q&A. π https://cal.com/kavish-sekhri/60min
Whatβs Included
- β One-on-one video consultation
- β Personalized setup assistance for your team
- β Configuration guidance for your specific use case
- β Q&A
- β Follow-up support via email