DoT Blog

  Logo courtesy of Databricks Over the last couple of years, the conversation around AI in enterprise software has moved quite quickly. Not long ago, the focus was on large language models (LLMs) and generative assistants; today, the discussion is shifting toward something more operational: agentic systems , AI agents capable of reasoning, planning, and acting across workflows. With the introduction of Genie Code , this past March, Databricks is making a clear statement about where it believes the future of data engineering and analytics is heading. The announcement positions Genie Code , the company’s tool designed for data teams for AI solution development, as a tool that allows developers and data professionals to build, orchestrate, and operate AI agents that interact directly with data environments. The interesting part is not just the tool itself. It’s, in my view, what it signals about the direction of the modern data platform.   From Data Pipelines to Agenti...

  Logo courtesy of  Amazon.com, Inc. For the past few years, the AI conversation has been dominated by large public models and cloud-scale services, but quietly, another trend has been gaining traction: the push toward private, autonomous AI agents running closer to where data and decisions live. With the recent introduction of OpenClaw on Amazon Lightsail , Amazon Web Services (AWS) is nudging that conversation forward. This new offering essentially allows developers and organizations to run autonomous AI agents in their own AWS-controlled environment using relatively simple cloud infrastructure. On the surface, this might look like just another developer-friendly deployment option, but if we step back for a moment, it hints at a deeper shift into how organizations might design AI systems in the near future.   From AI Assistants to Autonomous Agents So far, most of today’s AI implementations still operate basically as assistants. You prompt them, they respond, even in en...

  Logo Image Courtesy of Oracle Oracle’s latest announcement doesn’t sound like just another product release; it’s a statement. With its new AI Data Platform, Oracle is telling the enterprise world that the time for siloed data and experimental AI is over; we’re now entering an era where AI needs to live inside business data, not beside it. Unveiled at AI World 2025 , the Oracle AI Data Platform aims to unify data management, AI model integration, and automation, all within a single environment. According to the company, it combines data lakehouse and analytics capabilities with built-in generative AI tools, vector indexing, and an “agent hub” for building intelligent applications. So, the message is clear: Oracle wants to make AI an operational layer across business workflows, not an add-on.   From Data Storage to Intelligence Activation For years, enterprises have struggled to connect their data systems to AI models efficiently. Oracle’s approach focuses on bringing AI to t...