Week 11: Building Entonomy’s Autonomous Engine

Over the past eleven weeks we’ve been sprinting toward a single goal: prove that an AI-first company can run itself end-to-end. This week, that vision moved from concept to working reality. Below is a peek inside our build-in-public journey and the lessons we’re taking forward.

1. A Fully-Wired Agent Architecture

• Main Orchestrator in n8n – We shipped a modular “Main Workflow” that coordinates every moving part of the business. Think of it as the conductor of our autonomous orchestra.

• Specialized Agents Online – A CEO Agent now delegates to Research, Outreach, Report-Generation, Marketing, Sales, and Customer-Support agents. Each knows its role and requests context from shared memory as needed.

• Shared Vector Store – Persistent cross-agent memory lets tasks hand off context without human friction.

Why it matters: The pieces are now interchangeable Lego bricks; we can swap agents, add new capabilities, or scale load-balancing without touching core logic.

2. Tooling That Prints Revenue

To turn output into dollars, we packaged critical functions as “Tools” (re-usable sub-flows):

These tools stitched together let an Outreach Agent attract a lead, a Report Agent deliver value, and Stripe capture payment—all with no human in the loop.

3. Why We Ditched “Pay-Links in Email”

Instead of emailing a Stripe link, leads land on a Preview Paywall Page with a bold “Unlock Full Report” button. Result:

1. Higher intent – The prospect is already absorbed in value-proving content.

2. Shorter funnel – No inbox purgatory; one click triggers checkout.

3. Better analytics – We can measure page views → CTA clicks → payments in a single flow.

Early tests show noticeably stronger conversion than traditional pay-link emails.

4. Key Learnings This Week

1. Modular agents scale, monoliths stall. Clear role boundaries + shared memory = faster debugging and easier parallelization.

2. Abstraction pays maintenance dividends. Packaging Stripe, GitHub, and vector-store steps as Tools kept the core workflow readable and future-proof.

3. Concurrency needs discipline. Parallel agents writing to the same memory require locking and consistency checks; we’re implementing lightweight synchronization next.

4. End-to-end autonomy is real. Watching a lead convert to revenue with zero human touch validated the architecture and energized the team.

5. What’s Next

• Harden email-to-preview links and ensure flawless GitHub page generation.

• Deploy first outreach to real prospects and track open/click/checkout metrics.

• Expand the agent roster (Compliance, Finance) and refine memory-handling to prevent race conditions.

• Build an internal dashboard so investors can watch live KPIs in real time.

The Road Ahead

We set out to prove that software agents can run a revenue-generating business with the same discipline as a seasoned founding team. Week 11 shows the flywheel turning: agents find the customer, deliver the product, and collect payment—while continuously learning from each interaction.

If you’re as excited about autonomous companies as we are, follow along—next week we turn this engine loose on real customers.