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Case Study

Here's a case study on how we advanced agent interoperability: https://www.humansimulation.ai/case-studies/startup

Inspiration

The inspiration for Stealth Startup came from the idea of automating the entire process of building a company. We wanted to create intelligent agents that simulate the roles of a CEO, CTO, and Marketer, each contributing to building out a startup from scratch, mirroring the experience of launching a real-world tech startup and seeing how a particular idea would play out in a given market.

What it does

We were able to create the first fully self-functioning startup run purely by AI, there's no human interaction to re-iterate the business plan, refactor some of the code, or even change up the colors on the logo AI-generated — it's the agents that are 100% in control of the iteration of all aspects of the startup. Stealth Startup is a simulation platform where AI agents act as key team member agents—CEO, CTO, and Marketer—who collaboratively build a startup. The CEO agent handles market research, generates business strategies, and designs the business plan — note that we connected it to the web to get the latest insights. The CTO agent directly modifies the codebase and pushes updates to a real GitHub repository — it's able to go through the entire codebase of the startup the agents are building, make actual changes to the code, and commit these changes to their personal repository. The Marketer agent designs and creates logos and branding materials for the startup — it's able to literally generate relevant logos based on the startup idea and iterate on the design based on consulting with the other agents. These AI agents communicate on Slack wherein they can have discussions between team members and provide updates to one another in various channels. The agents came together and ended up building a 911 dispatch assistant web application built fully in React by the CTO agent.

How it does it

We built Stealth Startup by developing specialized AI agents using Cohere's language models to generate realistic business strategies, technical code, and marketing content. Each agent was given distinct tasks: the CEO generates business plans, the CTO agent integrates with the GitHub repository to make real-time code changes, leveraging Groq for fast AI inference, and using headless browsers on Vercel v0 for versioning and deployments. The Marketer agent uses Flux 1 to create logos and branding materials. All these agents are orchestrated through a Dictator class that manages the workflow and ensures smooth communication between the agents, simulating the creation of a full startup. Additionally, we gathered 40+ applicants via Linkedin to apply to our company's intern posting that was generated by the CEO agent and had it select candidates to hire.