- Agent Builder lets anyone create custom AI agents through a visual interface
- Pre-built templates and components accelerate development for common use cases
- Agents can be tested, refined, and deployed without involving engineering teams
The biggest barrier to AI adoption is not technology. It is the gap between business needs and technical implementation. Business teams know what they need automated, but building AI agents traditionally required engineering resources.
Kolossus Agent Builder changes this equation. Our visual builder lets anyone create custom AI agents that connect to your systems and execute complex workflows. No coding required.
This guide shows you how to build, test, and deploy custom agents using Agent Builder.
What is Agent Builder?
Agent Builder is a visual development environment for creating AI agents. Think of it as a design tool for automation.
Key Capabilities
- Visual workflow design: Drag and drop to create agent logic
- Natural language instructions: Tell agents what to do in plain English
- Pre-built components: Ready-made actions for common tasks
- Testing sandbox: Try agents before deploying to production
- Version control: Track changes and roll back if needed
Who Uses Agent Builder?
Agent Builder is designed for business users, operations teams, and analysts who understand their workflows but may not write code. Common users include:
- Operations managers automating manual processes
- Sales leaders creating account research agents
- HR teams building onboarding assistants
- Finance teams automating report generation
- Customer success managers creating support agents
Building Your First Agent
Let us walk through creating an agent that researches companies before sales calls.
Step 1: Define the Goal
Start by describing what you want the agent to accomplish:
"Research a company before a sales meeting. Find recent news, key executives, potential pain points, and relevant case studies from our library."
Step 2: Add Data Sources
Select the integrations your agent needs:
- Web search for company news
- LinkedIn for executive information
- Your CRM for existing relationship data
- Document library for case studies
Step 3: Design the Workflow
Use the visual canvas to define the agent's process:
- Receive company name as input
- Search for recent news and announcements
- Find key decision makers and their backgrounds
- Check CRM for existing contacts and opportunities
- Match relevant case studies from your library
- Compile findings into a briefing document
Step 4: Configure Output
Define how the agent delivers results:
- Format as a structured briefing document
- Include links to all sources
- Send to Slack or email before the meeting
- Save to the CRM opportunity record
Step 5: Test and Refine
Run the agent with sample companies and review outputs. Adjust instructions, add data sources, or modify the workflow based on results.
Advanced Features
Once you have mastered the basics, Agent Builder offers advanced capabilities for complex workflows.
Conditional Logic
Add branching based on conditions:
- If the company is in healthcare, include HIPAA compliance information
- If deal size exceeds $100K, notify the sales director
- If no recent news found, expand the search timeframe
Human-in-the-Loop
Insert approval steps where needed:
- Pause for review before sending external communications
- Request manager approval for actions above thresholds
- Allow users to provide additional input mid-workflow
Scheduled Execution
Set agents to run automatically:
- Daily briefings delivered every morning
- Weekly reports generated each Friday
- Real-time triggers when events occur in connected systems
Multi-Agent Workflows
Chain multiple agents together:
- Research agent gathers information
- Analysis agent identifies insights
- Communication agent drafts the summary
- Delivery agent sends to the right channels
Best Practices
Follow these guidelines for successful agent development:
Start Simple
Begin with a focused use case and expand from there. An agent that does one thing well is better than one that tries to do everything.
Be Specific in Instructions
Clear, detailed instructions produce better results. Instead of "research the company," specify what information matters and how it should be organized.
Test with Real Scenarios
Use actual examples from your work when testing. This reveals edge cases and helps refine the agent for real-world use.
Iterate Based on Feedback
Collect feedback from users and continuously improve. The best agents evolve based on how people actually use them.
Document Your Agents
Add descriptions and notes so others can understand and maintain agents you create. This is especially important for shared team agents.
Start Building Today
Agent Builder is available to all Kolossus customers. Whether you want to automate a simple task or build complex multi-step workflows, you can create agents that fit your exact needs.
- Templates library with 50+ pre-built agent starting points
- Interactive tutorials to guide you through your first build
- Community gallery with agent examples from other customers
- Expert support when you need help with complex requirements
Written by
Kolossus Team
Product & Research
Expert in AI agents and enterprise automation. Sharing insights on how organizations can leverage AI to transform their workflows.
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