How AI Is Transforming Data Careers
summary
Panelists report concrete shifts: roles move from feature engineering to building AI products, writing prompts and orchestrating workflows using GenAI and LLMs like ChatGPT and Claude. Examples include an internal chatbot, an LLM system for titling groups and a working Chrome extension that saved course content. Teams spend months on prompts (three people full time); production output hits 10,000 lines/day while tools generate millions more, improving speed but adding maintenance, security and system‑design costs.
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chapters (10)
- 0:00AI's impact on data careers
- 1:55AI career transitions
- 6:38AI transforming careers
- 9:32Side projects in AI journeys
- 17:57Identity shifts in AI era
- 23:00Skills value with AI
- 26:11Automation versus creativity
- 38:38AI for new engineers
- 42:27Technical skills in AI age
- 45:59Closing remarks & Q&A
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