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Platform Overview

What is AI Product Builder?

AI Product Builder (AI CPO) is a platform for building and growing products based on the Product DNA (Discovery — Navigation — Acceleration) methodology. You chat with an AI assistant, describing your product, idea, or problem, and the platform automatically extracts facts, builds a Job Graph, generates 25 product artifacts, and helps you make data-driven decisions.

Unlike templates or document builders, AI CPO understands your product's context. Every artifact is built from collected facts about your niche, user pains, audience, economics, and competitors. The more context you provide, the more accurate the results.

How to Use the Platform

Three Workspace Panels

The workspace consists of three panels. You can resize them by dragging the dividers between them:

  1. Sidebar (left) — artifact navigation grouped by phase: Research, Strategy, Build, Launch, Diagnosis. Also includes project switching, credit indicator, and the custom artifact request button. Artifacts display colored status icons:
    • 🔒 Gray — locked (insufficient data)
    • 🔓 Blue — unlocked, ready for generation
    • ✅ Green — generated
    • ⚠️ Yellow — stale (data updated after generation)
  2. Preview (center) — view generated artifacts. You can open multiple artifacts in tabs, copy text, leave feedback (accuracy/completeness/relevance), and regenerate with a different AI model.
  3. Chat (right) — the primary interaction tool. Here you chat with the AI, upload files, launch research, and connect external data sources via connectors. At the top of the chat — the context bar and quick action buttons (research, connectors, backlog).

Getting Started

  1. Describe your idea or product — write in chat what you're building, for whom, and what problem you're solving
  2. AI extracts facts — each message is analyzed by an LLM that identifies facts across 5 dimensions
  3. Artifacts unlock — when enough data is collected, artifacts become available for generation
  4. Generate and iterate — click on an artifact, launch generation, review the result in the preview
  5. Add more context — the more information you provide, the better all artifacts become

Two Use Cases

UC1: New Idea — From Zero to MVP (Research Mode)

You have a product idea but no data. AI CPO will guide you through the entire journey: from niche research and problem formulation to landing page creation and pitch deck. At each step, the platform asks the right questions and generates artifacts that typically require a 3-5 person product team.

Example
You wrote: "I want to build a habit tracker for people with ADHD." AI CPO will extract the niche (health-tech, ADHD), identify key pains (forgetfulness, motivation loss), formulate Job Statements ("When I try to build a habit, I want to receive contextual reminders so I don't forget"), build segments by ABCDX, generate an interview script, and 20 more artifacts.
UC1 Path
Research (pain map → Job Statements → segments → personas → interview script) → Strategy (positioning → value proposition → offer bank → pricing) → Build (RAT tests → feature priority → unit economics) → Launch (landing → GTM → outreach → pitch deck).

UC2: Existing Product — Diagnosis and Growth (Diagnosis Mode)

You already have a product but don't understand why users churn or how to grow. AI CPO will conduct a product audit, churn diagnosis using the Switch formula "in reverse" (why users "fire" your product), compare with industry benchmarks, and propose a growth strategy.

UC2 Path
Connect data sources (PostHog, GA4, Telegram) → describe your product and metrics → generate Product Audit → Churn Diagnosis → Job Scorecard → Benchmarks → Growth Strategy.

Context Score: 5 Dimensions

At the top of the chat, you'll see a context score — the percentage of collected context. Context is gathered across five dimensions. Each fact extracted from your message has a weight from 10 to 100. The sum of weights determines the context level.

DimensionWhat's CollectedExample Facts
Niche Market, industry, geography, trends "B2B SaaS for restaurants", "Market growing 20% per year"
Pains Problems, frustrations, triggers "Losing 5 hours per week on manual tracking", "Report errors"
Audience Segments, roles, contexts, execution criteria "Freelancers earning $1,000-3,000/month", "Criterion: speed"
Economics Prices, WTP, budgets, business model "Competitors charge $20/month", "WTP: $5-10/month"
Competitors Alternative solutions, their strengths/weaknesses "Toggl — strong in tracking, weak in reports", "40% don't use anything"
Tip
Artifacts generated with low context (below 30%) will be marked as "draft." Aim for at least 50% context before generating key artifacts (positioning, unit economics).

Credit System

Every action on the platform costs a certain number of credits. When you create your first project, you receive 15,000 welcome credits — enough for a full analysis of several products.

ActionCostComment
Chat message10 creditsEach message = fact extraction
Artifact generation200 creditsFirst generation of any artifact
Artifact regeneration100 creditsRegeneration after data update
Premium artifact300 creditsComplex artifacts (unit economics, audit)
Research500 creditsAutomated search via Telegram, web
Connector import300 creditsPostHog, GA4, Telegram, Yandex.Metrica
Custom artifact400 creditsArtifact by your request
Estimate
15,000 credits ≈ 75 chat messages (750 cr.) + 10 artifacts (2,000 cr.) + 1 research (500 cr.) + 3 regenerations (300 cr.) + 1 custom artifact (400 cr.) — with credits to spare. Credits never expire and work across all projects.

AI Models

The platform uses multiple AI models for different tasks:

TaskPrimary ModelFallback
Chat (standard)Qwen3-235BGPT-OSS-120B → Nemotron
Chat (escalated)Claude Sonnet 4Claude Haiku 4.5
Fact extractionLlama-3.3-70B (Groq)Claude Haiku 4.5
Artifact generationGemini 2.0 FlashQwen3-235B
Niche researchLlama-3.3-70B (Groq)Gemini 2.0 Flash

When generating artifacts, you can choose the model manually: Gemini 2.0 Flash (default), Qwen3-235B, Claude Sonnet 4, Claude Opus, or Claude Haiku. Model choice affects quality but not credit cost.

Tip
For most artifacts, Gemini 2.0 Flash delivers excellent results. Try Claude Sonnet 4 for complex artifacts (positioning, unit economics) where depth of analysis matters.

Feedback System

After generating each artifact, a feedback panel appears with three dimensions: Accuracy, Completeness, and Relevance. Give a thumbs up or down for each dimension. For negative ratings, a comment field appears.

Your feedback doesn't disappear — it's aggregated and analyzed by AI weekly. Based on the analysis, the platform automatically improves prompts and artifact generation. See Platform Evolution for details.

File Uploads

Drag a file into the chat area or click the paperclip button. Supported formats:

  • Documents: PDF, DOCX, XLSX, CSV, TXT, JSON
  • Images: PNG, JPG
  • Audio: MP3, WAV, OGG, M4A, WEBM

Maximum file size is 10 MB. Files are validated by extension and magic bytes, renamed to UUID for security. File contents are analyzed by AI and facts are extracted automatically.

What to Upload
  • Telegram chat exports from your target audience — AI will extract real pains from conversations
  • Competitor reviews (App Store, Google Play) — for competitive analysis
  • Customer development interview transcripts — maximum valuable facts
  • Financial data (CSV) — for accurate unit economics
  • Interview audio recordings — AI will transcribe and extract facts

Connectors

Connect external data sources for automated import and analysis. Click the API button in the chat toolbar.

SourceStatusWhat's Imported
TelegramActivePosts from public channels
PostHogActiveTrends, retention, funnels, DAU
Google Analytics 4ActiveTraffic sources, demographics, conversions
Yandex.MetricaActiveVisits, sources, behavior
VK, App Store, Google Play, etc.PlannedReviews, metrics

Each import costs 300 credits. Data is depersonalized before analysis.

Escalation and Model Switching

If the AI detects dissatisfaction with responses (negative tone, repeated questions, no progress), it automatically switches to a more powerful model. The system detects 5 types of signals:

  1. Explicit request — "call a senior", "connect an expert"
  2. Negative tone — frustration, dissatisfaction in messages
  3. Stagnation — 4+ messages without new facts (context not growing)
  4. Repetition — more than 60% word overlap between messages
  5. Tone mismatch — serious question, superficial answer

Upon escalation, a notification appears in the chat: "Senior Expert connected" (empathetic, deep) or "Analyst connected" (data-driven, precise). When the conversation normalizes, AI automatically returns to the standard model to save resources.

Shadow Projects (No Registration)

You can start working without registration. The platform creates a "shadow" project tied to your session. All messages, facts, and artifacts are stored in the database (not in cookies). When you register or log in, the project automatically binds to your account — nothing is lost.

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