Episode
236: What AI replaces in data work and when not to reach for it, with Julie Beynon
- Podcast
- Humans of Martech
- Published
- Sep 8, 2026
- Duration seconds
- 3350
- Processing state
not_requested
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Summary
What's up everyone, today we have the pleasure of sitting down with Julie Beynon, Head of Analytics at Augment Code. (00:00) - Intro (01:07) - In This Episode (04:13) - Breaking Into Data Without A Computer Science Background (06:05) - Why AI Made Building Cheap But Maintenance Expensive (09:25) - How To Push Back On AI Projects Without Killing Momentum (12:28) - Building AI Agents That Multiply A Two Person Data Team (16:29) - When Not To Reach For AI At Work (22:23) - Running A Lean Data Team As A Force Multiplier (27:28) - The Spreadsheet Test For Keeping Your Data Stack Simple (31:49) - How To Prove The Value Of Invisible Data Work (39:14) - Why Data Analytics Is Becoming GTM Operations (41:47) - What Part Of The Data Analyst Job AI Is Replacing (47:15) - The Data Skills AI Can't Replace (52:07) - How To Decide What Deserves Your Energy Summary: Julie Beynon came into data sideways from content marketing, got cut down to 2 words by a CEO, and turned that into a 15-year career running lean data teams. In this episode she breaks down how she cloned her best analyst into an AI agent named JimBot, why she pushes back on AI projects without ever saying no, and how she gets companies to fund the invisible foundation work nobody claps for. She makes the case that AI knocked down the SQL wall, so the real bottleneck moved to the data model underneath, and that simple is now the hardest skill in the room. There's a spreadsheet test, a team of 2 that runs like 10, and a surprisingly hopeful take on AI making us more human. Stick around for the part where she explains why the boring option takes the most nerve. About Julie Beynon Julie Beynon is the Head of Analytics at Augment Code, an AI coding assistant company, where she runs a lean data team and builds AI agents that let…