Stories by Kelvin Yap
Agent Optimization: Define what better means, and let AgentControl find it
Agent Optimization, now in beta in AgentControl, automatically searches for a better agent configuration against criteria you define.
Kelvin Yap
Adaptive Triggers: AI that corrects itself in production
Adaptive Triggers is now available in closed beta.
Kelvin Yap
Agent Optimization: Discover better agent configurations automatically
Agent Optimization is now available in private beta for eligible customers.
Kelvin Yap
Introducing AgentControl
AgentControl is the operational layer for managing agents in production.
Kelvin Yap
Agent graphs bring control and visibility to multi-agent AI workflows
Agent graphs bring real-time control to multi-agent AI workflows.
Kelvin Yap
Online evals in AI Configs is now GA
Online evals in AI Configs help you define and monitor quality in production.
Kelvin Yap
Introducing LLM Playground for AI Configs
Test, compare, and trace LLM prompt and model variations before they reach production.
Kelvin Yap
Online evals: LLM-as-a-Judge
Online evals in AI Configs give teams quality signals to successfully ship AI changes.
Kelvin Yap
Understanding AI behavior: LLM observability in AI Configs
Get deeper visibility into model behavior and impact with LLM observability.
Kelvin Yap
