The Data T

Armon Petrossian and Satish Jayanthi

Previously known as Coffee with Coalesce, The Data T is a monthly podcast hosted by Armon Petrossian and Satish Jayanthi, co-founders of Coalesce, the data transformation company. Each month, we invite industry experts, entrepreneurs, and executives to spill the tea on the data industry's hottest topics: from data modeling and data ops to AI and LLMs, data engineering trends and predictions, datapreneurship, and more.

  1. 10/30/2025

    Gleb Mezhanskiy on Rewriting the Migration Playbook with AI

    Data migrations have long been the costly, painful bottleneck of modernization, dragging on for years and carrying multi-million-dollar price tags. But AI is already flipping that script. Gleb Mezhanskiy, founder & CEO of Datafold, who has been deep in the trenches of AI-driven migrations, joins us on the Data T podcast to unpack how AI automation is finally making it realistic to move off entrenched legacy ETL tools. Drawing on his years as a hands-on data engineer and PM (including leading a massive migration initiative at Lyft), Gleb explains where migrations go off the rails: millions of lines of legacy code and lack of automation lead to massive human time sunk into reconciliation and QA. He shares how Datafold attacks the problem end-to-end, using agents and data diffing to translate and validate at scale, so teams can “lift and shift” quickly, then refactor with confidence on modern stacks like Snowflake and Coalesce. Beyond migrations, Gleb and podcast host, Coalesce co-founder and CEO Armon Petrossian, dig into how AI is reshaping data engineering itself. They argue AI won’t replace great engineers; it elevates them, shifting work from tedious rewrites to higher-leverage design, governance, and outcomes. The teams that master AI-assisted workflows, evaluation, and modern patterns will widen the gap, moving from weeks of manual effort to rapid, continuous delivery. Key Topics Data migration challengesThe role of AI in data migrationsLimitations of generic AI tools and LLM models for migration projectsHow AI is reshaping data engineering rolesPredictions for data infrastructureAI for productivity

    42 min
  2. 10/14/2025

    The AI-Ready Data Team with Erik Duffield

    This month on The Data T, we sit down with Erik Duffield, CEO and co-founder of Hakkoda, now an IBM Company, to unpack the latest hot topic in our industry: AI-ready data. Everyone’s talking about it, but what does it really take to build an AI-ready data team or data practice? AI-readiness isn’t about the latest tool, it’s about a mindset shift. Duffield shares why data programs must now be designed for machines as primary consumers, how data governance has evolved from a blocker to an enabler, and why the speed of iteration, not a single big launch, is the real measure of success. Duffield touches on agentic AI in production, the future of data careers, and what 2026 may hold for both the AI market and enterprise adoption. Co-hosted by Coalesce cofounders Armon Petrossian and Satish Jayanthi Key topics: What does an AI-ready data program look like?Gaps between hype and reality in AI initiativesWhat keeps data leaders up at night?Data security concernsData team composition and reskilling for AI successLabor force shifts and career progression challengesHow do you define and measure trusted, AI-ready data?Top data trends and predictions for 2006 Resources: About Hakkoda, an IBM Company: https://hakkoda.io/ About Coalesce: https://coalesce.io/ Coalesce is the only data transformation and governance platform designed for the AI era. Built on a metadata-driven framework, Coalesce gives data teams the speed to build and deploy transformations 10× faster—while enforcing the standards, structure, and governance needed to scale sustainably. With Coalesce Catalog, transformation and metadata management come together in a single solution, enabling discovery, trust, and collaboration across the business. Whether accelerating AI-assisted migrations from legacy tools or future-proofing enterprise data architectures, Coalesce provides the guardrails and efficiency to keep data teams AI-ready.

    45 min
  3. 07/03/2025

    The Architect of Scale: Ion Stoica on Open Source, AI, and the Future of Data

    Ion Stoica is a professor of computer science at UC Berkeley, Co-Founder and Executive Chairman of Databricks, and a key architect of the Apache Spark project. Most recently, he’s the Co-Founder of Anyscale, which leverages the open source Ray framework developed in-lab to enable scalable AI workloads, much like Spark revolutionized large-scale data processing. In this episode of The Data T, we chat with Stoica about his illustrious career, how his obsession with solving hard technical problems led him from networking research to peer-to-peer video, Apache Spark, and ultimately Databricks. He recounts turning Spark’s open-source momentum into a successful enterprise business, crediting speed of execution and targeted hiring for the company’s rise and urging founders to move fast and recruit experienced operators early. Stoica warns that tomorrow’s workloads will demand vertically integrated, multi-accelerator systems. Optimistic yet realistic about AI, he sees reliability and “human-in-the-loop” workflows as today’s gating factors and advises data professionals to embrace continuous learning as the industry accelerates. Hosted by Armon Petrossian and Satish Jayanthi, co-founders of Coalesce. Key topics: The origins of Apache Spark and DatabricksCommercializing open source projectsScaling AI infrastructure complexityAdvice for data practitioners Resources: About Coalesce: https://coalesce.io/about/Coalesce podcast archive (The Data T): https://coalesce.io/podcast/

    36 min

About

Previously known as Coffee with Coalesce, The Data T is a monthly podcast hosted by Armon Petrossian and Satish Jayanthi, co-founders of Coalesce, the data transformation company. Each month, we invite industry experts, entrepreneurs, and executives to spill the tea on the data industry's hottest topics: from data modeling and data ops to AI and LLMs, data engineering trends and predictions, datapreneurship, and more.