Case Studies
Five AI harnesses — each automating a phase of business operations, working together as one system.
How They Connect
AI-Driven Development Harness
End-to-End Software Delivery Automation with 7 Specialized Agents
A development team needed to ensure AI-generated code consistently met specifications across a multi-repository codebase. Manual code review was catching spec deviations too late, and the feedback loop between ticket creation and verified implementation was slow and error-prone.
Read Case StudyAutonomous Build Pipeline
One-Line Prompt to Production-Ready Application
Building production-ready applications from scratch requires coordinating multiple concerns: architecture design, task decomposition, parallel implementation, testing, quality assurance, and documentation. Each step traditionally requires human coordination and context switching.
Read Case StudyBusiness Operations Hub
Natural Language Commands to Automated Workflows via Discord
A solo operator managing multiple projects needed a central command interface to handle daily operations: task management, meeting follow-ups, daily journaling, and information collection — spread across separate tools with no unified access point.
Read Case StudyMeeting Intelligence Pipeline
Audio Transcription to Structured Tasks in 60 Seconds
Meeting action items were getting lost. Participants would discuss tasks, but follow-up depended on someone manually reviewing notes and creating tickets. By the time tasks were logged, context was lost and deadlines were missed. Even getting audio off the recording device was a manual step someone had to remember.
Read Case StudyAI Log Triage
Error Detection to First Response in Seconds
An engineering team was spending hours investigating error logs that turned out to be expected behavior — external API timeouts, rate limits, DNS blips. Real issues got buried under noise, and the on-call engineer couldn't tell which ERRORs needed attention without digging into each one manually.
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