Description
Brain Co. is building the world's first AI-native permitting, and we need people who've actually done the work to help us get it right. You would play a role in helping shape AI Permitting in the US.
We're looking for 1) homebuilders and developers - production builders, custom builders, small regionals, and 2) architects, and 3) engineers to join us as part-time advisors. You'll work directly with our product and GTM teams, telling us where our AI falls short, what would actually change how you operate, and what it would take for a tool like this to earn a place in your workflow.
We are looking for someone for a minimum of 2 hours per week for 3-4 months. Opportunity to extend as needed.
Requirements
What you'll do
- Walk us through how you submit - Tell us what is included, what you’ve learned to front-load, where submissions get tripped up
- Use the product on a project - Run a real permit package through our software alongside normal process
- Tell us where we are wrong - Review AI output on real permit submissions and flag errors, gaps, or misapplied code
- Jurisdiction knowledge - Help us understand how review actually works across different jurisdictions and permit types
- Help us learn what a good submissions looks like - Review sample packages and tell us what would sail through, come back with comments, or get rejected
Who we're looking for:
- Someone who has personally submitted permits, not managed the process from a distance, but actually prepared packages, responded to comments, and tracked submissions through approval
- Active or former plans examiner, permit engineer, architect of record, or homebuilder, anyone whose name is on the drawings or whose desk the rejection letter lands on
- Deep knowledge of how permitting actually works in Florida, Texas, or California, the codes, the departments, the local amendments, and the unwritten rules
- Enough history with a jurisdiction to tell us what reliably gets approved, what comes back with comments, and what gets rejected outright
- Opinions about what's broken and no hesitation sharing them - "this is wrong because..." is exactly what we need
- Open to sharing examples on applications (passed and failed)
- No technical background required - your job is to tell us if the AI gets it right, not to explain how it works
