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

Page: https://stenobird.com/podcast/super-data-science/981-how-data-engineers-are-10x-ing-themselves-with-agents-feat-matt-glickman
Text version: https://stenobird.com/podcast/super-data-science/981-how-data-engineers-are-10x-ing-themselves-with-agents-feat-matt-glickman.md
Podcast: [Super Data Science: ML & AI Podcast with Jon Krohn](https://stenobird.com/podcast/super-data-science)
Published: 2026-04-07T11:00:00+00:00
Episode link: https://www.podtrac.com/pts/redirect.mp3/chrt.fm/track/E581B9/arttrk.com/p/VI4CS/pscrb.fm/rss/p/traffic.megaphone.fm/SUPERDATASCIENCEPTYLTD7109622026.mp3?updated=1775550082
Audio file: https://www.podtrac.com/pts/redirect.mp3/chrt.fm/track/E581B9/arttrk.com/p/VI4CS/pscrb.fm/rss/p/traffic.megaphone.fm/SUPERDATASCIENCEPTYLTD7109622026.mp3?updated=1775550082
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Duration seconds: 4475

## Resource

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.

## 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

## Topics

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

## Chapters
- 1:00 — Introduction: Jon Krohn introduces Matt Glickman and the context of the current AI revolution.
- 6:15 — From Goldman Sachs to Genesis: Matt discusses his transition from managing data platforms at Goldman Sachs to founding a startup.
- 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.
- 17:30 — The Genesis Onboarding Process: How Genesis Computing maps enterprise data environments and memorializes institutional knowledge.
- 23:15 — The Shift to Private Cloud Concepts: Comparing modern AI infrastructure to the evolution of massive private cloud environments.
- 29:00 — Ensuring Agent Accountability: Using artifacts and proofs to prevent errors and overcome the human laziness factor in data testing.
- 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.

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## Transcript

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