Test AI Behavior: A Practical Regression Testing Playbook (Chat-Based) Most teams “test” an AI assistant once. They run a few friendly chats.They see a decent answer.They ship. And then the assistant slowly breaks in...

Test AI behavior before production tests you.

A practical chat-based regression testing playbook for AI agents: golden conversations, break tests, rubrics, and workflow validation.

monobot.ai/library/blog...

#AIAgents #AIQA #RegressionTesting #ConversationalAI

You Can’t Improve What You Can’t See: Observability for AI Voice & Chat Agents Most AI assistants fail silently. They don’t crash.They don’t throw errors.They just slowly become less accurate, less helpful — and more expensive....

Most AI agents don’t break.
They slowly degrade — and teams notice too late.

Observability is what turns AI from a black box into a controllable system.

New Monobot post: monitoring, QA, and continuous improvement for AI voice & chat agents.
🔗 monobot.ai/library/blog...

How to Build a High-Accuracy Knowledge Base for AI Voice & Chat Agents (Monobot Playbook) AI agents are getting smarter every month — but in production, accuracy still breaks for the same reason: knowledge. When customers ask about...

Most AI assistants don’t fail because the LLM is “bad”.
They fail because the knowledge base is messy and hard to retrieve.

New post: a practical playbook to build a high-accuracy KB for voice + chat agents using Monobot.
🔗 monobot.ai/library/blog...

#AI #AIAgents #KnowledgeBase