Blog
Deep dives into AI evaluation, data management, and building reliable AI systems. Expert perspectives from the Briefcase AI team.
How We Built a Production Blog in 50 Minutes Using Four Parallel Agents
From infrastructure deployment to content migration: A real-world case study of agent coordination that eliminated the traditional bottlenecks crushing development teams.
Pre-Classification: The Missing Infrastructure Layer That Actually Makes AI Systems Scale
Why 95% of production AI systems never achieve their scaling promise and how pre-classification confidence infrastructure finally delivers the operational scaling that teams built AI automation to achieve.
When 60% Wrong Isn't Good Enough: Building a Zero-Hallucination AI System for NYC Tenants
How off-the-shelf LLMs hallucinated critical legal information 60% of the time—wrong phone numbers, incorrect fee caps, fabricated deadlines—so we built a systematic data versioning pipeline that achieved 100% accuracy.
From Contract Chaos to Git-Style Legal Workflows: How LakeFS Eliminated Review Hell
How Briefcase AI replaced scattered email threads and conflicting document versions with lakeFS-powered contract reviews—surfacing 5 critical dealbreakers in 2 days.
LakeFS as the Foundation for Auditable Multi-Tenant Agent Architectures
How repository-based tenant isolation and versioned agent state enable enterprise-grade AI systems with complete regulatory compliance.
How We Built Documentation in 2 Hours Using Our Own Multi-Agent System
From 3-week bottleneck to 2-hour delivery: A real-world multi-agent case study that achieved 8.7/10 quality with 89% time savings.
The Executive's Guide to AI Evaluation Infrastructure: Lessons from Tellen's Domain-Specific Implementation
Essential guidance for CMOs and co-founders on building domain-specific AI evaluation infrastructure, featuring real-world implementation strategies and decision frameworks for professional services.
The Observability Crisis in Enterprise AI
Why dataset catalogs and agent proliferation are the same unsolved problem—and how infrastructure that captures operational reality solves both.
Why Reproducibility Matters in AI Evaluation
Explore the reproducibility crisis in AI and learn how modern data snapshot approaches are solving this fundamental challenge.