AI Agents Hack with LabLab and MindsDB

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Using AI agents to automate the SDLC workflow.

The Synapses

pedro3000

harisellahi

syedshahhussain

We designed four agents to automate the SDLC. These were:
Requirements Agent: Understand requirements from requirements doc
Design Agent: Create high level design doc
Software Development Agent: Generate codebase to build PoC (small project)
Code Test Agent: Generate code tests

The workflow steps we followed were as follows:
a. Requirements Gathering
Task: Extract key requirements from a document.
Goal: Create a concise summary of the CRM system's required features.
Outcome: Defines the project scope (authentication, CRUD operations, task management, reporting).
b. High-Level System Design
Task: Design the architecture of the CRM system.
Diagrams Generated:
Use Case Diagram
Class Diagram
Entity-Relationship Diagram (ERD)
UI Design for Dashboard
Outcome: A document detailing the architecture, components, and visual diagrams of the system.
c. Code Generation
Task: Develop the Code for the system.
Goal: Create functional code that implements core features.
Outcome: Working code implementing authentication, database operations, and reporting.
d. Code Testing
Task: Run test cases to verify code functionality.
Goal: Ensure the system meets the requirements and works as expected.
Outcome: A detailed test report highlighting results and potential issues.

Future Work could include:
Improvements in Design Diagrams: Explore more AI-driven tools for automated generation of detailed design diagrams.
Customization: Enable more advanced configurations for tasks such as adding new agents or expanding CRM functionality.
Deployment: Plan for deployment of the final CRM system in a production environment.

We also considered building an agentic workflow for MLOps, but ultimately decided on the SDLC.

Build an agentic workflow for the software development life cycle (SDLC)

"The Synapses team on AI Agents Hack with LabLab and MindsDB Hackathon"

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