From the team
On AI Agents
in Production
Practitioner-level writing on what breaks, why it breaks, and how to build multi-agent systems that hold up under real operating conditions.
The Demo-to-Production Gap Is a Visibility Problem, Not a Skill Problem
Every demo succeeds. Most production agents don't. The gap isn't your model, your prompt, or your team. It's observability — and span-level data is how you close it.
Agentic AI Is a Systems Problem. Most Teams Are Solving the Wrong One.
Most agentic AI pilots don't fail because of the model. They fail because teams built tools when they needed systems. Here's the math, and the mindset shift.
You're Monitoring the Wrong Layer: What Production Spans Reveal About Agent Failures
6,101 production spans reveal AI agents fail in orchestration, not models. Most teams are monitoring the wrong layer. Here's what the data shows.
Your Platform Already Has the Signal. KriyAI Turns It Into Action.
DevOps, SRE, and observability platforms sit on the richest behavioral telemetry in the enterprise. KriyAI is the reliability layer that completes the loop.
The Agentic Future: AI That Works With You, Not Just For You
The AI era is shifting from prompts to agents. Here's what changes when AI stops answering questions and starts doing the work.
The Trust Gap: Why Agent Reliability Is the Only Metric That Matters
Every agent failure is a trust withdrawal you can't easily reverse. Here's the specific mechanic through which unreliability destroys adoption — and what it actually takes to fix it.