Lendi Group Runs First Project Through "Agentic SDLC"

Why It Matters

The agentic SDLC slashes development cycle time and improves traceability, giving Lendi a competitive edge in a highly regulated fintech market. It also demonstrates a scalable model for AI‑driven delivery that other financial firms can emulate.

Key Takeaways

• Lendi deployed Atlassian Teamwork Graph for its first agentic SDLC.
• Meetings now auto‑transcribed to PRDs via Loom and Confluence.
• AI agent converts PRDs directly into Jira epics and stories.
• Cursor AI coding tool generates production‑ready code within the workflow.
• Lendi aims to become fully AI‑native across all operations.

Pulse Analysis

The software delivery landscape is undergoing a rapid AI‑driven transformation, and Lendi Group’s recent rollout of an “agentic software development lifecycle” (SDLC) illustrates the shift from manual orchestration to autonomous pipelines. By leveraging Atlassian’s Teamwork Graph—a unified data layer that stitches together Loom recordings, Confluence pages, and Jira tickets—Lendi has created a single source of truth that feeds directly into downstream automation. This approach mirrors broader trends in fintech, where speed, compliance, and scalability demand that code, documentation, and project tracking be generated with minimal human friction. In practice, the new workflow eliminates the traditional hand‑off of product requirements.

During a meeting, Loom captures a high‑fidelity transcript, which is instantly transformed into a concise idea brief and stored in Confluence as a product requirements document (PRD). An AI‑powered agent then parses the PRD, auto‑creates Jira epics, and breaks them into sprint‑ready stories. The integration of Cursor, an AI coding assistant, further accelerates development by producing production‑grade code snippets that developers can review and merge. Early internal metrics suggest a 40 % reduction in cycle time from concept to deployment. Beyond Lendi’s internal efficiencies, the agentic SDLC signals a strategic pivot for the home‑lending sector toward full AI‑native operations.

As regulatory scrutiny intensifies, automated traceability from meeting minutes to released features can improve auditability and risk management. Competitors are likely to adopt similar pipelines, especially as Atlassian expands Teamwork Graph’s capabilities. However, organizations must balance speed with governance, ensuring that AI‑generated artifacts meet security standards and retain human oversight where critical decisions are made. Lendi’s experiment offers a blueprint for scaling AI‑augmented development across regulated financial services.