n o t
o n l y
t e c h n o l o g y

Custom AI Agent
For Automated
YAML Generation

Using the Agentic Framework, we developed an AI agent that automates the traditionally manual, repetitive, and error-prone processes of setting up DevOps configurations and YAML files for releases, templates, configuration items, and workflows

Use Case

The Client

A pioneering technology company from the US, offering an AI-powered software delivery platform designed primarily for large enterprises, including many Global 5000 companies.

The company’s core focus is on accelerating digital transformation by unifying agile planning, software development, application security, continuous testing, and value stream management into one integrated platform.

Overview

Our Agentic AI solution transforms how users handle configuration and automation in DevOps by dramatically speeding up the process, ensuring high accuracy, and empowering scalable, customizable automation with minimal manual input.

For complex workflows involving numerous tasks, subtasks, and phases, this Agentic AI solution provides a shortcut through conversations with an agent.

The Challenge

Creating or editing YAML files for software releases and templates is a manual, repetitive, and error-prone process.

Users typically click through web interfaces, manually tweak exported settings, and then import them back for further modifications.

This is a time-consuming task, especially for complex configurations, releases, or workflows.

The Solution

Using the agentic framework, we developed an AI agent that automates the generation of YAML files for DevOps configurations from conversational user inputs. This eliminates manual steps, speeding up setup and reducing effort.

The solution also enables custom agents and workflows, including an agent swarm with a central “core” agent orchestrating plugin-specific agents and autonomous container task execution, allowing users to scale automation across complex, multi-phase DevOps processes.

Results

Custom AI Agent featured image
01
Significant Time Savings and Efficiency Gains

The AI agent automates the traditionally manual, repetitive, and error-prone processes of setting up DevOps configurations and YAML files. Automation accelerates workflows and reduces tedious, time-consuming tasks (allowing users to focus on higher-value activities).

02
Reduced Errors and Improved Accuracy

Our AI agent generates consistent, validated YAML configurations automatically, minimizing human errors and ensuring that configurations are accurate and standardized.

03
Empowered Customization with Scalability and Autonomy

By enabling users not only to automate single tasks but also to create custom agents and workflows, our solution empowers users to scale their automation flexibly across complex, multi-phase DevOps processes.

Key Components

01
Core package

This foundation manages memory, semantic search, message processing, agent state, and provider integration.

02
Agent package

Manages agent lifecycles, character loading, and cross-platform orchestration.

03
Adapters

Support data persistence with multiple backend databases to store agent memory, relationships, goals, etc.

04
Clients

Provide standardized interfaces for interaction with communication platforms and also REST API support.

05
Plugin system

Flexible extension layer supporting blockchain, RAG, and text-to-image/video/3D.

06
AI model support

The agentic framework allows seamless local-to-cloud model switching.

07
Blockchain/network integrations

The framework used is web3-friendly, interacting with blockchains and including smart contract operations.

08
Multi-platform support

Powers agents with multimedia handling across various social and communication platforms.

Learnings
  • Rigorous QA, fine-tuning, and thorough testing are essential for optimal AI agent performance.
  • Set up strict access control protocols to prevent unauthorized access and misuse.
  • Design each agent to handle one specific task for focused efficiency.
Conclusion

Notch’s Agentic AI solution transforms how users handle configuration and automation in DevOps by dramatically speeding up the process, ensuring high accuracy, and empowering scalable, customizable automation with minimal manual input.

The autonomy to manage workflows drives greater agility, enabling users to confidently delegate intricate tasks to AI, thereby supporting broader adaptability and innovation.

The Agentic Framework we used is a sophisticated open-source AI agent built with TypeScript and modular components that excels at integrating AI into decentralized and social networks. It offers autonomous-agent capabilities, extensive customization options, and support for advanced LLMs.

Technologies, Frameworks & Tools

Eliza Agentic Framework RAG
YAML LLMs Vector Databases
Typescript