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Battle Bots Hack Night & Watch Party (w/ OpenAI Codex)

lumaHosted on Luma

Fetched about 2 hours ago

Thursday, July 16, 2026

to Thursday, July 16, 2026

Artificial Intelligence

Event Type

in person

428

Participants

38

Est. Projects

Come to the Pre Hack Night Tournament! https://luma.com/mini-battlebots-tournament-jul15-2026 Battle Bots Hack Night & Watch Party A playful hack night for builders who want to make bots battle, compete, negotiate, race, fail dramatically, and maybe even behave intelligently. This is a hands-on evening at Bright Data's Web Data Loft for agent-vs-agent experiments, bot games, lightweight robotics-flavored demos, and weird competitive AI projects that can be built in a few hours. What to Expect A short kickoff with the theme and constraintsOpen build time for solo builders and small teamsBot-vs-bot, agent-vs-agent, game, simulation, or robotics-inspired projectsLightweight demos or battles near the end of the nightLight food, drinks, and a room of technical builders Good Project Fits Agent battle arenas or evaluation gamesCompetitive coding-agent workflowsRobot or simulation demosBrowser, game, or CLI botsAnything weird, fun, technical, and demoable by 9 PM Who Should Apply This is for engineers, founders, designers, students, and builders who like fast experiments and live demos. Admission is free and approval-based because space is limited. When: Wednesday, July 15, 2026 | 5:00 PM - 9:00 PM PTWhere: Bright Data Web Data Loft, 625 2nd St, San Francisco, CA Note: this date is tentative pending final host schedule confirmation.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct