Build AI Support That Actually Works

What I Look At

• Real conversations, not test prompts
• Where users lose trust or get stuck
• Prompt structure and failure patterns
• Knowledge gaps and contradictions
• Escalation logic and handoff quality

What You Get

• Written audit with specific examples
• Clear list of what to fix, why, and in what order
• Quick wins vs foundational changes

Best For

Teams who already have an AI agent live but know it's underperforming.

Focus Areas

• Training for trust, not just accuracy
• Aligning responses with desired user behavior
• Handling uncertainty, limits, and escalation properly
• Reducing friction without hiding constraints

What You Get

• Rewritten system and behavioral prompts
• Conversation patterns your agent should follow
• Guidance your internal team can maintain

Best For

Teams who want their AI agent to feel reliable, calm, and competent.

What Changes

• Writing for AI consumption, not just humans
• Clear intent, scope, and ownership per article
• Removing ambiguity and overlap
• Structuring content to support reasoning

What You Get

• A repeatable knowledge framework
• Example articles rewritten for AI
• Clear rules for future documentation

Best For

Teams whose AI answers are technically correct but practically unhelpful.

Includes

• Regular review of AI performance
• Iterative prompt and knowledge updates
• Support team enablement
• Strategic guidance as AI capabilities evolve

Best For

Teams treating AI support as a core system, not an experiment.