Signal — layout A
Execathon — Launch pad
Execathon 2.0 is a facilitator-led session where your team races the same problem statement from a blank page to a launched marketing campaign — working with a crew of named AI agents you address directly, in one shared stream.
What this is
Every team gets the same problem statement at the same moment. There are no personas, no pre-built templates — just your team, a crew of agents, and the hour.
How it works, and how you're scored
Your group is its own isolated workspace — nothing you see or send is shared with any other group. Inside it, you address a crew of named agents directly, in one shared stream everyone at your table can see.
Grounds audience and market reasoning in a real live search, not just pattern-completion — feeds the market snapshot.
Defines the product — what it is, who it's for, why it's worth buying. Feeds the product concept.
Writes campaign copy and positioning, checked against real live search rather than assumed. Feeds the campaign.
Art directs the imagery — concept, mood, composition — then generates it. Feeds the hero image.
Reads the rest of the crew's work and turns it into page layout, structure, and content. Feeds the web page.
A market snapshot, a product concept, a campaign, a hero image, and a web page — five shared slots, synced live to your whole team.
Your conversation with the crew is your own — not synced across teammates. The five artifact slots are the shared state everyone sees update together.
Process-based — how well your team operates the cycle: briefing clearly, iterating, using the hour well. Not a simulated audience reacting to what you ship.
The architecture behind the Execathon
Five layers, and where they connect. Scroll for the step-by-step version below.
Each participant's own chat pane — per person, not synced across your team.
The one piece of state every teammate shares — market snapshot, product concept, campaign, hero image, web page, updating live for everyone in the group.
Named agents, addressed directly by @name. Every request is attributed to your group specifically.
Text generation calls the Anthropic API directly — per-group attribution on every call, no shared pool.
Hero images call the OpenAI API directly, through the same per-group attribution layer.