Agent Training — also referred to as Agent Coaching or Agent Instructions — allows you to improve your Fullview AI Agent using natural language.
Instead of building complex decision trees or modifying fragile workflows, you coach the agent directly in plain English. The agent applies that instruction immediately and carries it forward into future conversations.
This feature is part of Fullview’s broader “Teach AI Your Way” approach .
What Is Agent Training?
Agent Training enables you to:
Instruct the AI agent in natural language
Modify how it answers specific scenarios
Add conditional logic (e.g., based on user roles or properties)
Enforce internal policies and procedures
Improve future responses instantly
As described in recent product updates, the goal is to give customers full control over agent behavior, including clarification questions, follow-up questions, and complete answer changes .
Internally, we’ve positioned this as moving away from rigid block-based workflows and instead configuring the agent via natural language instructions .
Why Agent Training Exists
Traditional support bots often fail because:
They rely on static knowledge articles.
They require engineering support to change behavior.
Small workflow mistakes can break the system .
They act as “black boxes” with limited transparency .
Agent Training solves this by:
Shortening the feedback loop.
Allowing direct, immediate corrections.
Storing improvements so the same issue doesn’t repeat .
Giving visibility into the knowledge used for each response .
How Agent Training Works
1. Identify a Response to Improve
From the Conversations page, any response that looks incorrect or incomplete can be trained and iterated on directly by a support admin .
Training mode transforms the interface into an AI coaching environment and clearly separates training sessions from production conversations .
2. Provide Natural-Language Instruction
You describe how the agent should behave — exactly as you would coach a human employee.
Example shown in demo materials:
“When the customer asks about adding new users, check their user properties to ensure they are an admin first.”
This replaces complex workflow builders with plain-English instructions .
3. Review and Approve the New Behavior
After submitting the instruction, the agent generates a preview of how it will respond going forward. You can approve the changes before they are applied .
4. Persistent Learning
Once approved:
The instruction is stored.
Future similar conversations apply the change automatically.
The same mistake is not repeated .
Subsequent examples work “out-of-the-box” .
This creates a super-fast feedback loop with immediate improvements.
Where Agent Training Fits in the Broader Setup
Agent Training works alongside:
Knowledge Base Ingestion
The agent can ingest:
Help center articles (Salesforce, Zendesk, Intercom)
Uploaded PDFs
Scraped web content
Past agent conversations
UI Awareness & Visual Intelligence
The SDK allows the agent to read the DOM and understand where the customer is inside the product .
Action Execution
The agent can:
Trigger API calls
Perform actions (e.g., refunds, freezes, upgrades)
Escalate with context and recordings
Agent Training defines how these capabilities should be used in specific scenarios.
Key Benefits
1. Immediate Improvements
Changes apply instantly after approval .
2. Shortened Feedback Loop
You can see exactly which knowledge was used and quickly correct outdated or incorrect behavior .
3. Reduced Workflow Complexity
No need for fragile block-based flows or engineering changes .
4. Persistent Scenario-Level Learning
Once coached, similar future cases automatically improve .
5. Full Operational Control
Admins are in control of clarification questions, follow-ups, answer structure, and escalation logic .
Best Practices for Agent Training
Start with real flagged conversations.
Apply human training only where thumbs-down feedback exists .
Use specific, policy-aligned instructions.
Include conditional logic when needed (roles, plans, permissions).
Re-test the same scenario after approving changes to verify behavior.
Summary
Agent Training transforms Fullview from a static AI responder into a controllable, coachable support agent.
Instead of asking engineering to modify workflows, you:
Spot an issue.
Describe the correct behavior.
Approve the new logic.
See it persist immediately.
It replaces fragile automation with flexible, human-readable control — while still leveraging Fullview’s deep integrations, UI intelligence, and execution capabilities .
In short: you don’t configure flows, you coach outcomes.