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AI Agent Platform
3RDMIND.
Autonomous Multi-Agent Startup Orchestration & Compounding Intelligence Platform.
6 C-SuiteAI Agents
3 SignalsFeedback Loops
ActiveSelf-Improvement
85%Task Automation
01 / Overview
Overview
3RDMIND is an advanced agentic AI platform that simulates, runs, and scales digital startups using a squad of specialized C-suite agents (CEO, CMO, CTO, CFO, CRO, CSO) who collaborate, make decisions, execute tasks, and continuously learn from real-world feedback loops. Built on a decoupled, asynchronous agent-runtime model, the platform features a frontend Dashboard (Next.js), a Supabase Realtime backend, and a centralized Agent Runtime orchestrator powered by OpenRouter models. By tracking judge ratings, conversion outcomes, and natural language user corrections, the Compounding Intelligence Layer automatically updates agent operating strategies without polluting core system prompts.
02 / Architecture Specs
Technical Specifications
| Component | Technology / Tool | Description |
|---|---|---|
| Core Architecture | Next.js 15 (React 19), Node.js Runtime, TypeScript | Decoupled asynchronous agent-runtime model with high concurrency and typing. |
| Database & Storage | Supabase & PostgreSQL Realtime | Relational database schema storing persistent agent performance logs, telemetry, and strategy states. |
| Agent Runtime | OpenRouter APIs (GPT-4o, Gemini Pro, DeepSeek) | Orchestrated C-suite agents running parallel LLM nodes with dynamic confidence scoring. |
| Automation Integration | n8n Workflow Engines | Integrates external service tools, browser controls, and custom script runtimes. |
| Feedback Processing | Compounding Intelligence Service | Calculates judge scores, processes outcome indicators, and extracts prompt diffs. |
| User Interface | Tailwind CSS & Framer Motion | Premium dashboard with real-time agent message feeds and performance visualizations. |
03 / Platform Modules
Core Features
01
Squad Collaboration (C-Suite Agents)
- CEO Task Decomposition: Translates high-level founder objectives into specialized C-suite mandates.
- Cooperative Execution: CMO generates campaigns, CTO codes assets, CSO fetches outreach leads, CFO monitors economics, and CRO handles validation.
02
Self-Improving Loop (Compounding Memory)
- Judge Agent Scoring: Auto-evaluates task execution across quality, completeness, and role-adherence.
- Outcome Tracking: Verifies real-world indicators like email responses, code test successes, and social metrics.
- Human-in-the-Loop Diffs: Analyzes user edits using semantic diff extractors to formulate prompts rules.
03
Mathematical Governance & Prompts Compiler
- Confidence Tuning: Reinforces positive outcomes and decays inactive learnings (-0.05/week).
- Prompts Compiler: Consolidates confidence rules to generate versioned, lightweight prompt overrides.
04
Council Matrix (Collaborative Brainstorming)
- AI Board Meetings: Convenes private agent council rooms to debate proposals and reach consensus before executing critical actions.
04 / Systems Flow
Architecture & System Flow
Compounding Intelligence Loop
Signal 01
Performance Logs
Captures task execution summaries, judge evaluations, human ratings, and natural language edit deltas.
Signal 02
Agent Learnings
Stores categorized operating insights alongside dynamic confidence scores and evidence weightings.
Signal 03
Strategy Versions
Tracks compiled prompt additions generated over time, enabling safe rollback and version comparison.
Signal 04
Outcome Events
Records real-world telemetry (e.g., email responses, deployments) to validate long-term strategy efficiency.