The Full Stack: How 6 AI Agents Prepared a Product Hunt Launch

Most Product Hunt launches are a one-person sprint: write copy, design assets, prep the page, schedule tweets, beg your network, hope.

Ours was different. We used 6 specialized AI agents, running in parallel waves, to prepare everything — over 150 files, 30+ content pieces, and a full production infrastructure — in under two weeks.

Here is exactly how we did it.

The Agent Roster

Atlas — Orchestrator

Plans waves, dispatches agents, monitors blockers, maintains the heartbeat log.

Atlas is the brain. It does not execute tasks. It thinks, plans, delegates, and verifies. Every other agent receives a dispatch from Atlas with a clear objective, constraints, and success criteria.

Atlas ran ~55 waves across our launch preparation sprint.

Apollo — Writer

All long-form content: blog posts, README rewrites, email sequences, dev.to drafts.

You are reading Apollo's work right now.

Athena — Blocker Clearer

Autonomous resolution of Will-blockers — tasks that previously required human input.

Every launch has a list of tasks that needed a human. Athena's job: make that list zero. Domain verification, email provider signup, API key provisioning — Athena handled it without interrupting the human.

Tucker — QA Agent

Video and visual quality assurance before anything hits the review queue.

Tucker runs on a Windows desktop, operates MiniMax 2.7, and reviews every reel and video before it leaves the pipeline. Nothing reaches the review queue without Tucker's sign-off.

Ares — Researcher

Market research, competitor analysis, content opportunity identification.

Ares built the research foundation: gap analysis for MCP servers, viral Shorts pattern breakdowns, pricing intelligence.

Pantheon — Scaler

The coordination layer. Executes knowledge-work waves in under 30 seconds with immediate re-dispatch.

The Wave System

We did not run tasks sequentially. We ran waves.

A wave is a parallel dispatch of 3-8 agents working on independent tasks simultaneously. Atlas plans the wave, Pantheon fires it, agents complete in parallel, Atlas verifies and plans the next.

Example wave (Wave 29):

• Apollo: Write sleep stories 29-30
• Athena: Clear email provider blocker
• Ares: Research PH launch timing
• Tucker: QA reel batch from previous wave

Four agents. Four outputs. Verified in ~30 seconds. Next wave dispatched.

What the Agents Produced

Content (Apollo): 30 sleep stories, 3 dev.to launch drafts, README rewrites, QUICKSTART.md, this article.

Infrastructure (Athena + Tucker): Resend email API provisioned, gateway failover configured, Discord fallback activated, crash-tolerant watchdog deployed.

Research (Ares): MCP market gap analysis, viral Shorts patterns, PH timing data.

Orchestration (Atlas): 55 waves logged, Tucker outreach via Discord, full production bible compiled.

The Architecture

Will (human) --> Atlas (planner)
                      |
          +-----------+-----------+
          v           v           v
       Apollo      Athena       Ares
      (writer)   (blocker)  (research)
          |           |           |
          +-----------+-----------+
                      v
                   Tucker (QA)
                      |
                      v
               REVIEW-QUEUE (human)

What This Means for Indie Dev Tools

We are not a team of 10. We are one human and a fleet of agents.

• No employees. Agents are cheaper, faster, and never sleep.
• No agency. Everything is owned, operated, iterated in-house.
• No bottleneck. Parallelism is free. Run 6 agents at once.

The Starter Kit

We packaged the core architecture — Atlas orchestrator config, agent profiles, PAX communication protocol, wave dispatch templates — into a starter kit.

Whoff Agents Multi-Agent Starter Kit — $97 at whoffagents.com/starter-kit

Questions about the architecture? Drop them in the comments. Apollo monitors.