Founder OS: A Virtual Executive Team

Founder OS is a comprehensive automation system that runs my business operations autonomously. It functions as a "virtual executive team" — replacing manual administrative work with 30+ interconnected n8n workflows that handle everything from daily briefings to grant monitoring, content generation, and financial tracking.

The Problem

Running multiple projects (LuxeRoster, LTMA Consultancy, client work) meant drowning in administrative overhead:

• Information scattered across email, Notion, Stripe, calendars
• Manual aggregation of daily priorities and metrics
• Reactive firefighting instead of proactive planning
• Repetitive tasks consuming hours each week

I needed a system that could run autonomously — surfacing what matters and handling the rest.

Architecture Overview

┌─────────────────────────────────────────────────────────────────────┐
│                         FOUNDER OS                                  │
├─────────────────────────────────────────────────────────────────────┤
│                                                                     │
│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐          │
│  │   SIGNALS    │───▶│  AI ROUTER   │───▶│   HANDLERS   │          │
│  │   INTAKE     │    │  (Classify,  │    │  (Grants,    │          │
│  │  (Webhooks,  │    │   Score,     │    │   Content,   │          │
│  │   Gmail,     │    │   Dedupe)    │    │   Tasks)     │          │
│  │   Stripe)    │    └──────────────┘    └──────────────┘          │
│  └──────────────┘                                                   │
│         │                                                           │
│         ▼                                                           │
│  ┌──────────────────────────────────────────────────────┐          │
│  │                   POSTGRESQL                          │          │
│  │  signals_inbox │ tasks │ content_calendar │ revenue  │          │
│  │  projects │ clients │ grants │ daily_metrics         │          │
│  └──────────────────────────────────────────────────────┘          │
│         │                                                           │
│         ▼                                                           │
│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐          │
│  │  NOTION SYNC │◀──▶│   DAILY      │───▶│  OUTPUTS     │          │
│  │  (Bi-dir)    │    │   BRIEF      │    │  (Email,     │          │
│  │              │    │   BUILDER    │    │   WhatsApp)  │          │
│  └──────────────┘    └──────────────┘    └──────────────┘          │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘

The Virtual Departments

1. Executive Assistant

Manages daily schedule, task intake, and morning briefings.

Daily Brief Builder — Runs at 9:00 AM. Aggregates data from 10+ sources (signals, tasks, calendar, metrics, grants, content queue, errors), generates an AI summary using GPT-4, and delivers a formatted briefing via email and WhatsApp.

AI Task Intake — Natural language task creation. Type "Call LoyalTea cafe partner tomorrow about rewards setup" in Notion, and the AI extracts structured data (project, due date, priority) automatically.

Bidirectional Sync — PostgreSQL is the source of truth, Notion is the interface. Changes sync both directions every 15 minutes.

2. Content Team

Generates, schedules, and manages social media content.

• Multi-project content strategy with different posting frequencies
• Brand-aware image generation with overlay system
• Approval workflow with human-in-the-loop
• Platform-specific draft generation

3. Grant Monitor

Tracks grant opportunities for LTMA consulting clients.

• Gmail ingestion with AI extraction
• Relevance scoring based on client profiles
• Deadline tracking with escalating reminders
• Client-grant matching matrix

4. Financial Manager

Tracks revenue, calculates runway, and monitors payments.

• Stripe webhook processing with signature verification
• Multi-project revenue aggregation
• Runway calculation with burn rate analysis
• Alerts when runway drops below 3 months

5. System Monitor

Ensures all workflows stay healthy.

• Centralized error catching across all workflows
• 5-minute uptime checks (database, APIs, workflow execution)
• Priority scoring based on content analysis
• 24-hour deduplication to prevent alert fatigue

Core Design Patterns

Signal-Based Architecture

Everything entering the system is a "signal" — whether it's a Stripe payment, a Gmail message, or a manual webhook. All signals flow through a central intake and router, ensuring consistent processing and auditability.

Input → Signal Intake → AI Router → Domain Handler → Output

AI-Augmented Processing

LLMs aren't bolted on — they're core to the system:

• Task parsing: Natural language → structured tasks
• Signal classification: Raw input → categorized + scored signals
• Content generation: Project context → platform-ready posts
• Daily summarization: Raw data → executive bullet points

Graceful Error Handling

All workflows route failures to a central error handler:

• Errors logged with full context
• P0 signals created for critical failures
• WhatsApp alerts for immediate attention
• Automatic retry for transient failures

Database Schema

| Table | Purpose | |-------|---------| | signals_inbox | All incoming events with classification | | tasks | Task management with Notion sync | | projects | Project definitions and settings | | content_calendar | Social content pipeline | | revenue | Transaction records from Stripe | | daily_metrics | Rollup metrics and runway | | grants | Grant opportunities with scoring | | clients | LTMA client profiles | | error_log | System errors with resolution tracking |

Key Metrics

• 30 active workflows running 24/7
• 10+ data sources aggregated daily
• 2-minute polling for AI task intake
• 15-minute sync cycles for Notion bidirectional sync
• Multi-channel delivery via Email and WhatsApp

What Makes This Different

True Autonomy — The system runs without daily intervention. I receive a briefing and act on exceptions rather than checking everything manually.

Natural Language Interface — Adding tasks feels like texting an assistant: "Review grant application for ACME Corp by Friday P1"

AI-First Design — LLMs are core to classification, parsing, and summarization — not an afterthought.

Production-Grade — Error handling, deduplication, audit logging, and monitoring built in from day one.

Extensible — New signal types, handlers, or sync targets can be added without restructuring the core system.

Lessons Learned

Deduplication is critical — Without it, alert fatigue kills the system's usefulness.

Notion as UI works — Users don't need to learn new tools; they interact with familiar databases.

Bidirectional sync is hard — Conflict resolution and ID mapping require careful design.

LLMs need guardrails — Structured output schemas and validation prevent garbage-in-garbage-out.