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Episode

981: How Data Engineers Are “10x’ing” Themselves With Agents, feat. Matt Glickman

Podcast
Super Data Science: ML & AI Podcast with Jon Krohn
Published
Apr 7, 2026
Duration seconds
4475
Processing state
processed
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Markdown
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Summary

Data engineering is shifting from manual pipeline construction to autonomous agent orchestration. Matt Glickman explains how Genesis Computing uses agentic workflows to automate complex data tasks with built-in guardrails.

Topics

  • Data Engineering
  • AI Agents
  • Autonomous Workflows
  • Genesis Computing
  • Enterprise AI
  • Machine Learning Operations
  • Agentic AI
  • Automation

Highlights

  • Main idea: AI agents are moving beyond simple copilots to execute entire multi-step data engineering workflows autonomously
  • Practical takeaway: Deploying agents like an 'onboarding' process ensures company knowledge remains a permanent internal asset
  • Failure mode: Relying on human-only verification leads to 'human laziness' and unproven artifacts in complex data pipelines
  • Main idea: The transition to agentic AI requires a shift from step-by-step instruction to managing high-level blueprints and guardrails
  • Practical takeaway: The most valuable future hires will be 'agent orchestrators' who can manage and scale AI-driven operations

Chapters

  1. 1:00 Introduction: Jon Krohn introduces Matt Glickman and the context of the current AI revolution.
  2. 6:15 From Goldman Sachs to Genesis: Matt discusses his transition from managing data platforms at Goldman Sachs to founding a startup.
  3. 11:45 Cloud and AI Adoption in Finance: A look at why highly regulated industries like finance and healthcare are becoming early adopters of AI.
  4. 17:30 The Genesis Onboarding Process: How Genesis Computing maps enterprise data environments and memorializes institutional knowledge.
  5. 23:15 The Shift to Private Cloud Concepts: Comparing modern AI infrastructure to the evolution of massive private cloud environments.
  6. 29:00 Ensuring Agent Accountability: Using artifacts and proofs to prevent errors and overcome the human laziness factor in data testing.
  7. 34:35 The Rise of the Agent Orchestrator: Why the next generation of data professionals will focus on managing AI agents rather than manual coding.