The Start of Our Agentic AI Journey
After experimenting with chat-based AI systems, we took the next step—building AI Agents. These autonomous programs go beyond simple conversations; they observe, process, and act with minimal human intervention. Think of them as digital assistants that take on specific tasks, making decisions based on predefined logic or learned behaviors.
The goal? To create intelligent automation that speeds up repetitive tasks and enhances efficiency without sacrificing quality.
Building Our AI Agent Framework
Our approach was straightforward:
- Develop a flexible framework that enables quick creation and deployment of agents.
- Use text-based configurations to define agent behavior, making it easy to iterate and improve.
- Test different AI models to see how well they handle specific tasks.
With this setup, we can rapidly prototype and refine AI agents, ensuring they deliver real value.
Expanding Our AI Agent Library
As we continued experimenting, we built a growing library of AI agents to assist with a variety of tasks. Beyond user story and test case generation, we developed specialized agents like a React Code Generator to automate frontend development, an SEO Helper to optimize content, and a Marketing Maestro to assist with campaign messaging.
These agents are already proving useful, streamlining workflows and freeing up our team to focus on strategic initiatives rather than repetitive tasks.
A snapshot of our internal AI agent dashboard, showcasing various specialized agents for programming, SEO, test case generation, and more.
Testing AI Agents: User Story & Test Case Generation
To evaluate their effectiveness, we created agents for user story generation and test case creation—critical steps in software development. Instead of manually crafting these from scratch, the agents analyze feature requests and produce structured outputs that streamline the process.
This marks the beginning of our agentic AI journey, where AI goes beyond simple responses to take on real work.
👉 Read the next part in our series to see how we tested AI-driven user story and test case generation in action.
Next in This Series
Follow along as we document our AI experiments and insights.
🔹 AI Experiment Part 3
Start of an Agentic AI Journey: Exploring how AI can go beyond prompts to act autonomously.
🔹 AI Experiment Part 4
Alpha's Vision for AI in Action: Envisioning how AI can streamline the software development lifecycle from idea to execution.
🔹 AI Experiment Part 5
AI-Powered Automation with n8n: We're experimenting with n8n to automate routine workflows and connect AI agents across tools and teams.
Missed the introduction? Read it here.
NIKET ASHESH
Partner
