Inspiration Every member of our team has either built a startup or is currently building one. We've learned a lot of things the hard way! From figuring out what problem is actually worth solving, to struggling with outreach, market research, and getting our product in front of the right people. Finding the right thing to build and the right audience to reach was always the hardest part.
Today, tools like Lovable, Base44, and other vibe coding platforms have made it incredibly easy to build a product. But building is only half the battle. Getting exposure isn't easy as not everyone understands the market, the business landscape, or how to position what they've built. That gap between "I built something" and "people are using it" is where most startups die. That's the inspiration behind what we built.
What It Does Our product is an autonomous startup builder. It analyzes trends from around the world, extrapolates problem statements from that data, and then autonomously builds software products to address those problems, while simultaneously handling the business development and customer outreach. From trend to product to customer, all on autopilot.
How We Built It We designed a multi-agent orchestration system using a chain-of-thought pattern, splitting responsibilities across two core pipelines.
The Agent Pipeline handles product creation. We built specialized agents for data gathering, review, and problem statement generation. These agents research global trends, rationalize and contextualize the information, and extrapolate actionable problem statements. From there, the system triggers an automation layer in VS Code that autonomously builds products through Jac Coder.
The Business Pipeline runs in parallel. It includes agents that handle valuations, value propositions, market research, and all aspects of business development. On the outreach side, we built agents that send automated emails and conduct AI-powered calls through Vapi AI.
The majority of the system was built within the Jaseci ecosystem.
Challenges We Ran Into The most difficult challenge was automating product creation through Jac Coder. Because Jac Coder operates as a VS Code extension rather than a fully integrated product, we had to write native device scripts to ensure our agents could internally prompt and send information directly to the Jac Coder system. Building a fully out-of-the-loop autonomous multi-agent orchestration layer that researches, rationalizes, and contextualizes extrapolated information was a significant engineering challenge.
Accomplishments That We're Proud Of We built a working system that takes a global trend and turns it into a launched product with business infrastructure and outreach, all without human intervention. Getting the full loop working end to end, from trend analysis to autonomous code generation to customer outreach, is something we are very proud of.
What We Learned We gained deep experience with the Jaseci ecosystem, adapting to a completely new technology and tech stack under a contracted timeline. We also developed a much stronger understanding of MCP servers, particularly when automating the connection between our agent system and Jac Coder.
What's Next for Outloop AI Team We want to continue building and testing within this new language and push our idea of completely autonomous scanning and production further. Beyond the platform itself, we plan to use our own system to autonomously build and launch real products, proving the concept by being our own first customer.
Built With
- jac
- jaseci
- python
- react
- typescript
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