3fbbb1a93b
- Next.js 14+ with App Router and TypeScript - Tailwind CSS and ShadCN UI styling - Zustand state management - Dexie.js for IndexedDB (local-first data) - Auth.js v5 for authentication - BMAD framework integration Co-Authored-By: Claude <noreply@anthropic.com>
6.4 KiB
stepsCompleted, inputDocuments, date, author
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2026-01-20 | Max |
Product Brief: Test01
Executive Summary
Test01 is a "Self-Study & Personal Branding Companion" designed for data analytics learners who struggle to consistently create content for their personal brand. By transforming a daily chat-based "learning diary" into high-quality, vlog-style educational content, Test01 removes the friction of writing while ensuring the output is authentic and highly relevant to recruiters.
Core Vision
Problem Statement
Data analytics bootcamp graduates need to build a personal brand to get hired, but they are often too exhausted to write consistent, high-quality content. Traditional note-taking is passive, and staring at a blank page for a blog post is daunting, leading to abandonment of personal branding efforts.
Problem Impact
Without visible proof of learning (like a blog or active LinkedIn), talented graduates get lost in the sea of applicants. They struggle to demonstrate their problem-solving process and unique voice, reducing their employability despite having the technical skills.
Why Existing Solutions Fall Short
- Standard Note Apps (Notion, Obsidian): Great for storage, but require high effort to transform notes into public content.
- AI Writing Tools (ChatGPT): Can generate content, but often sound generic, robotic, or lack the deep context of the user's specific learning journey ("hallucinated expertise" vs. "authentic struggle").
- Social Media Schedulers: Manage distribution but don't help with creation or ideation.
Proposed Solution
A mobile-first, chat-based interface where the user "vents" or debriefs their daily learning struggles to an AI "Teacher." This AI engages in a supportive dialogue to extract insights (active elicitation), then switches to a "Ghostwriter" persona (using long-term user context) to automatically draft authentic, "vlog-style" LinkedIn posts and Medium articles. The system prioritizes "narrative over tutorial," focusing on the journey of learning.
Key Differentiators
- Two-Stage Pipeline (Teacher-to-Ghostwriter): Solves the "blank page" problem by first using a "Teacher" agent to purely elicit information via probing questions, then passing that structured context to a "Ghostwriter" agent for content generation.
- Vlog-Style Authenticity: Optimizes for "Peer Learner" engagement (empathy/struggle) rather than just "Expert" tutorials, differentiating the user from other juniors.
- Frictionless Ritual: Replaces "writing a post" with "chatting about my day," lowering the barrier to entry for consistent documentation.
Target Users
Primary Users
"The Exhausted Learner" (Alex)
- Context: Recent Data Bootcamp graduate. Competent in Python/SQL but exhausted by the job hunt.
- Pain Point: Knows personal branding is necessary but lacks the mental energy to convert raw code/learnings into polished LinkedIn content. Fears sounding like an imposter.
- Goal: Secure a job by demonstrating "public learning" without adding significant workload to their day.
- Core Behavior: Uses the app to "vent" or debrief immediately after a study session/bug fix.
Secondary Users
"The Hiring Manager" (Sarah)
- Context: Senior Data Lead reviewing hundreds of resumes.
- Goal: Differentiate between "tutorial zombies" (who just copy code) and "problem solvers" (who understand the why).
- Value: Values authentic "vlog-style" content that shows the candidate's thought process, struggle, and resilience.
User Journey (The "Venting" Ritual)
- Trigger: Alex hits a wall or solves a tough bug (e.g., a Pandas merge error).
- Action: Opens Test01 and chats comfortably: "Ugh, I hate how merge defaults to inner join."
- Transformation (The Magic): The AI "Teacher" asks a probing question: "That's a common trap! How did you catch it?" This forces Alex to articulate the lesson.
- Reward: The AI "Ghostwriter" instantly drafts a polished, engaging post: "Why I'll never trust a default merge again."
- Outcome: Alex posts to LinkedIn in seconds. Sarah sees it and validates Alex's troubleshooting skills.
Success Metrics
User Success
- Metric: "Posts Generated per Week"
- Target: Active users generate >1 LinkedIn post per week.
- Why: If Alex is just "venting" but not "posting," the Ghostwriter pipeline is failing. This proves the "Ritual" is sticking.
Business Objectives
- Metric: "Engagement per Post" (Relative to manual posts)
- Target: Test01-generated posts see 1.5x higher engagement than user's previous manual posts.
- Why: Proves the "Vlog-style" hypothesis—that authentic struggle stories perform better than generic tutorials. This is the core value proposition for "Getting Hired."
Key Performance Indicators
- Quality KPI: "Edit Distance" (<10% manual edits)
- Definition: Percentage of text changed by user before posting.
- Definition: Percentage of text changed by user before posting.
- Why: Measures the quality of the "Teacher's" context extraction. High edits = Teacher failed to ask the right questions.
MVP Scope
Core Features (The "Venting Machine")
- Chat Interface: Simple text chat to capture the raw "venting."
- Basic "Teacher" Agent: A prompt-engineered agent that asks one smart follow-up question to dig deeper into the struggle.
- Basic "Ghostwriter" Agent: Takes the chat transcript and formats it into a LinkedIn-ready post.
- Copy-Paste Export: No API integration. Just a "Copy to Clipboard" button.
Out of Scope for MVP
- Medium Integration: Focus on LinkedIn short-form first.
- Voice Notes: Adds transcription complexity.
- User Accounts/Cloud Save: Local storage only (or simple Firebase) to start.
- Analytics: No dashboards.
MVP Success Criteria
- Pass: Does the AI produce a post that Alex is willing to share with <10% edits?
- Fail: Does the AI hallucinate details that didn't happen in the chat?
Future Vision
- V2: Cloud sync, User Profiles ("My Tone" settings).
- V3: Multi-platform support (Medium, Dev.to) and "Series" management (turning 5 posts into an article).