Insights on AI Operations
Practical guides on AI implementation, model selection, governance, and measuring real ROI. No hype — just what works in production.
Why Most AI Pilots Fail — And How to Design Ones That Don't
The difference between a successful AI pilot and a failed demo comes down to three things: scope, measurement, and production-shaped design. Here's how to get all three right.
OpenAI vs Anthropic vs Open Source: How to Choose the Right Model for Your Workflow
Model selection isn't about which AI is "best." It's about matching capabilities to your specific workflow requirements — accuracy, cost, latency, and data residency all matter.
The Practical Guide to Human-in-the-Loop AI Systems
Full autonomy is rarely the right answer. Here's how to design AI systems with the right level of human oversight — from quality review to approval workflows.
How to Measure AI ROI Without Guessing
Hours saved, handling time reduction, throughput increase, cost per execution — the six proof metrics every AI implementation should track from day one.
Have a Workflow Challenge?
We write about what we build. If you have a workflow that could benefit from AI, let's talk about making it happen.