Systems | Development | Analytics | API | Testing

AI failures rarely look like crashes. More often, they appear as confident but incorrect answers, subtle bias, or culturally inappropriate responses.

Agentic coding tools like Cursor, GitHub Copilot, and OpenAI’s Codex are reshaping how software is developed. They enable developers to offload routine tasks and accelerate feature delivery. However, these tools also introduce new challenges – particularly in how we test and validate the code they produce.

The advancement and widespread availability of new artificial intelligence (AI) capabilities—through platforms like the Databricks Data Intelligence Platform and Mosaic AI—has completely reset expectations for engineering teams across every industry. Business now moves at a new pace, demanding rapid delivery of intelligent, real-time applications—instead of slowly stitched-together systems solving problems defined and scoped months prior.

Is your organization still managing contracts the traditional way, spending weeks drafting, reviewing, and negotiating terms? Are manual errors, compliance risks, and value leakages quietly affecting your bottom line? Well, in today’s competitive business environment, where every decision is under the microscope, inefficient contract management is a strategic vulnerability. And that’s where Gen AI comes into play.