How to be an AI developer, tech layoffs, and enterprise-level GenAI feat.

In the latest episode of Sea the Ocean podcast, we invited Rajesh Shrivastav, a Senior AI Developer at NTT Data, prev. Oracle to discuss the current themes and use cases of Gen AI in the industry, what skills needed to be an AI developer and more about enterprise grade ai applications...

Connect with us:
Rajesh Shrivastava: ‪@genieincodebottle‬ ,   / genieincodebottle  
Shresth Shukla – uselessai.in
Sudhanshu Tiwari – linkedin.com/in/sudhanshu1st/

Video Timeline
[00:00] Intro & agenda – Setting the stage for enterprise GenAI discussion.
[01:02] Career journey – Professional background from Air Force to data science.
[05:47] Enterprise scale-up – Differences between a PoC/MVP and enterprise-ready AI.
[07:07] Legacy data challenges – Overcoming security and infrastructure hurdles in old systems.
[11:44] Risk management – Why startups take more risks than established enterprises.
[14:09] Business readiness – Determining if a client is truly ready for AI solutions.
[15:55] AI's probabilistic nature – The shift from deterministic software to unpredictable AI outputs.
[18:23] Managing AI costs – Strategies for predicting and controlling token usage.
[21:52] Impact on workforce – How AI is used for productivity and labor reduction.
[30:19] AI vs. simple automation – Knowing when to use LLMs versus traditional RPA.
[35:40] Failure points – Why AI projects often stall before reaching production.
[38:19] Autonomous vs. assisted AI – The current necessity of human-in-the-loop systems.
[41:06] Advice for leadership – Strategic recommendations for CTOs and consultants.
[47:49] GenAI tech stack – Essential tools for modern AI developers (Cloud, React, Vector DBs).
[52:05] Hiring criteria – What to look for in freshers versus experienced AI hires.

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