> ## Documentation Index
> Fetch the complete documentation index at: https://docs.prisme.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# No-Code Agents Overview

> Learn how to create powerful AI agents without writing code using Prisme.ai

Prisme.ai's no-code capabilities empower users across your organization to create sophisticated AI agents without programming experience. This democratizes AI development while maintaining enterprise-grade security, governance, and performance.

No-code is the business door into the same unified foundation your technical teams build on. Agents created here inherit the platform's governance and traceability by design, so business experts can move fast without stepping outside enterprise controls.

## Benefits of No-Code AI Development

> **Wider Access**
>
> Empower subject-matter experts to create AI solutions directly

> **Faster Deployment**
>
> Reduce development time from weeks to hours

> **Reduced Costs**
>
> Eliminate dependency on specialized AI development resources

> **Domain Expertise**
>
> Enable those with business knowledge to shape AI behavior

> **Experimentation**
>
> Facilitate rapid prototyping and iteration

> **Governance**
>
> Maintain control with centralized oversight

## No-Code Agent Types

Prisme.ai supports several types of no-code agents, each with distinct capabilities:

**Simple Prompting Agents**

Basic agents powered by foundation models with specialized instructions.

**Key Features:**

* Custom system instructions
* Persona definition
* Response formatting
* Specialized knowledge embedding

**Best For:**

* Question answering
* Content generation
* Simple conversational assistants
* Standard processes with clear instructions

[Learn more about Simple Prompting Agents →](https://docs.prisme.ai/create-agents/no-code/simple-prompting-agent)

**RAG Agents**

Knowledge-powered agents that access your organization's documents and information.

**Key Features:**

* Document processing and ingestion
* Knowledge base creation
* Semantic search integration
* Source citation

**Best For:**

* Internal knowledge bases
* Document-based workflows
* Policy and procedure guidance
* Self-service information access

[Learn more about RAG Agents →](https://docs.prisme.ai/products/agent-factory/creating-agents.md)

**RAG with Built-in Tools**

Advanced agents that combine knowledge retrieval with specialized capabilities.

**Key Features:**

* Knowledge base integration
* Pre-configured tool access
* Task automation
* Enhanced capabilities beyond conversation

**Best For:**

* Advanced customer support
* Technical documentation with examples
* Research and analysis
* Content creation with external information

[Learn more about RAG with Built-in Tools →](https://docs.prisme.ai/create-agents/no-code/rag-builtin-tools-agent)

## Available Built-in Tools

No-code agents can leverage several built-in tools without any programming:

> **Web Browsing**
>
> Access current information from the internet using Serper integration

> **Image Generation**
>
> Create images based on text descriptions

> **Code Interpreter**
>
> Run code to perform calculations, data analysis, and visualizations

> **PDF Analysis**
>
> Extract, summarize, and analyze information from PDF documents

> **Document Generation**
>
> Create formatted documents, reports, and presentations

> **Data Visualization**
>
> Generate charts and graphs from data

## No-Code Development Process

Creating effective no-code agents involves several key steps:

**1. Define Purpose and Requirements**

Clearly articulate what your agent needs to accomplish.

Key questions to answer:

* What specific problem will this agent solve?
* Who are the intended users?
* What information does it need access to?
* What actions should it be able to perform?
* How will success be measured?

**2. Select Agent Type**

Choose the appropriate agent architecture based on your needs.

Selection criteria:

* Simple Prompting for basic interactions
* RAG for knowledge-intensive applications
* RAG with Built-in Tools for enhanced capabilities

**3. Prepare Knowledge Resources**

Gather and organize the information your agent needs.

For RAG agents:

* Collect relevant documents
* Organize content logically
* Update outdated information
* Remove sensitive or irrelevant content

**4. Configure Agent Behavior**

Define how your agent will interact with users.

Key configurations:

* System instructions
* Response style and format
* Tool selection and usage criteria
* Knowledge retrieval settings

**5. Test and Refine**

Validate performance and iteratively improve.

Testing approaches:

* Sample conversations
* Edge case scenarios
* User feedback collection
* Performance monitoring

**6. Deploy and Monitor**

Make your agent available to users and track its effectiveness.

Deployment considerations:

* Access controls
* Usage monitoring
* Feedback mechanisms
* Improvement workflows

## Creating Agents with Agent Creator

Prisme.ai's Agent Creator provides a user-friendly interface for creating no-code agents:

### Key Features

> **Visual Agent Builder**
>
> Intuitive interface for agent configuration without coding

> **Template Library**
>
> Pre-built templates for common use cases

> **Knowledge Integration**
>
> Direct connection to organizational knowledge bases

> **Tool Configuration**
>
> Simple setup for built-in tool access

> **Testing Environment**
>
> Dedicated space to validate agent performance

> **Versioning**
>
> Track changes and manage agent versions

### Agent Creator Workflow

**1. Create New Agent**

Start with a blank slate or select from templates.

![Create New Agent](https://mintcdn.com/prismeai/lwRK6OzRqQlHjEmp/images/agent-creation.png?fit=max\&auto=format\&n=lwRK6OzRqQlHjEmp\&q=85\&s=39f3a52189d9a5335da5123bb0481c58)

Options include:

* Blank agent
* Industry-specific templates
* Function-based templates
* Duplicating existing agents

**2. Define Basic Information**

Set the agent's identity and purpose.

Key information:

* Agent name
* Description
* Category/tags
* Access permissions

**3. Configure Capabilities**

Select and customize the agent's features.

Available options:

* Foundation model selection
* Knowledge base connections
* Built-in tool activation
* Response parameters

**4. Set System Instructions**

Define the agent's behavior through prompting.

Instruction components:

* Role definition
* Response guidelines
* Knowledge utilization
* Tool usage criteria
* Limitations and constraints

**5. Test and Preview**

Validate agent performance in the testing environment.

Testing capabilities:

* Interactive conversation
* Sample queries
* Tool execution preview
* Knowledge retrieval verification

**6. Publish and Share**

Make the agent available to intended users.

Sharing options:

* Organization-wide publication
* Team-specific access
* Individual user permissions
* External link sharing (if permitted)

## Best Practices for No-Code Agents

> **Start Simple, Then Expand**
>
> Begin with basic functionality and add complexity incrementally.
>
> **Approach:**
>
> * Create a minimal viable agent first
> * Test core functionality thoroughly
> * Add additional capabilities one at a time
> * Validate each new feature before moving on
>
> This iterative approach helps identify issues early and ensures a solid foundation.

> **Craft Clear Instructions**
>
> The quality of your system instructions directly impacts agent performance.
>
> **Guidelines:**
>
> * Be specific about the agent's role and purpose
> * Provide examples of ideal responses
> * Include formatting requirements
> * Define boundaries and limitations clearly
> * Use simple, unambiguous language
>
> Well-crafted instructions create consistent, predictable agent behavior and reduce the need for frequent refinements.

> **Optimize Knowledge Organization**
>
> How you structure your knowledge bases affects retrieval quality.
>
> **Best practices:**
>
> * Organize documents logically by topic
> * Use clear, descriptive document titles
> * Break large documents into meaningful chunks
> * Include relevant metadata for filtering
> * Remove duplicate or outdated content
>
> Strategic knowledge organization improves response accuracy and relevance.

> **Test with Real Scenarios**
>
> Validate your agent with authentic use cases and edge cases.
>
> **Testing approach:**
>
> * Create a diverse set of test questions
> * Include common queries and edge cases
> * Test with different phrasings of similar questions
> * Incorporate actual user language and terminology
> * Validate tool usage with realistic scenarios
>
> Thorough testing identifies gaps and ensures the agent can handle real-world interactions.

> **Collect and Incorporate Feedback**
>
> Establish a systematic process for gathering and implementing user input.
>
> **Feedback system:**
>
> * Enable easy feedback submission within the agent interface
> * Review feedback regularly
> * Identify patterns in user satisfaction and pain points
> * Prioritize improvements based on impact
> * Close the feedback loop by informing users of changes
>
> Continuous improvement based on user feedback ensures the agent remains valuable over time.

## Common Challenges and Solutions

<table>
  <thead>
    <tr>
      <th>Challenge</th>
      <th>Description</th>
      <th>Solution</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td>Inconsistent Responses</td>
      <td>Agent provides varying answers to similar questions</td>

      <td>
        * Refine system instructions with more specific guidance\

        * Add example responses for common scenarios\

        * Lower the temperature setting for more predictability\

        * Create response templates for key question types
      </td>
    </tr>

    <tr>
      <td>Poor Knowledge Retrieval</td>
      <td>Agent fails to find or use relevant information</td>

      <td>
        * Improve document chunking strategy\

        * Enhance metadata for better filtering\

        * Adjust retrieval settings (more results, higher relevance threshold)\

        * Reorganize knowledge base structure\

        * Add query reformulation instructions
      </td>
    </tr>

    <tr>
      <td>Inappropriate Tool Usage</td>
      <td>Agent uses tools unnecessarily or incorrectly</td>

      <td>
        * Provide explicit criteria for when to use each tool\

        * Include examples of appropriate tool usage\

        * Add constraints for tool selection\

        * Create step-by-step instructions for complex tools\

        * Test with diverse scenarios to verify behavior
      </td>
    </tr>

    <tr>
      <td>Scope Confusion</td>
      <td>Agent struggles with determining boundaries of its role</td>

      <td>
        * Define clear in-scope and out-of-scope topics\

        * Provide explicit handling instructions for edge cases\

        * Include examples of appropriate redirects or escalations\

        * Create specific guidance for handling ambiguous requests\

        * Test boundary conditions regularly
      </td>
    </tr>

    <tr>
      <td>User Adoption Resistance</td>
      <td>End users hesitant to engage with AI agents</td>

      <td>
        * Create a transparent introduction explaining the agent's purpose and limitations\

        * Provide clear examples of how the agent can help\

        * Establish easy escalation to human support when needed\

        * Collect and address feedback proactively\

        * Show concrete value through time savings or improved information access
      </td>
    </tr>
  </tbody>
</table>

## Enterprise Governance Considerations

> **Access Control**
>
> Implement appropriate permissions for agent creation and usage
>
> **Key practices:**
>
> * Role-based access for agent creation
> * Approval workflows for production deployment
> * User group definitions for agent access
> * Audit logs for agent modifications

> **Content Compliance**
>
> Ensure agents adhere to organizational policies
>
> **Key practices:**
>
> * Pre-deployment review process
> * Compliance checklist verification
> * Sensitive information handling guidelines
> * Regular content audits

> **Performance Monitoring**
>
> Track agent effectiveness and usage
>
> **Key practices:**
>
> * Usage metrics dashboard
> * User satisfaction tracking
> * Response quality evaluation
> * System performance monitoring

> **Information Security**
>
> Protect sensitive data in agent interactions
>
> **Key practices:**
>
> * Data handling guidelines
> * PII protection measures
> * Conversation logging policies
> * Retention and purging schedules

## Next Steps

Ready to create your first no-code agent? Explore these resources:

> **[Simple Prompting Agent](https://docs.prisme.ai/create-agents/no-code/simple-prompting-agent)**
>
> Create basic agents with custom instructions

> **[RAG Agent](https://docs.prisme.ai/products/agent-factory/creating-agents.md)**
>
> Build knowledge-powered agents

> **[RAG with Built-in Tools](https://docs.prisme.ai/create-agents/no-code/rag-builtin-tools-agent)**
>
> Develop advanced agents with enhanced capabilities

> **[Agent Creator Guide](https://docs.prisme.ai/products/agent-factory/creating-agents.md)**
>
> Learn more about the Agent Creator platform


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