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Building Enterprise AI

Building Enterprise AI

Agentic Coders
Uitgebracht: 2026-02-01
© 2026 Agentic Coders. All rights reserved.
Building Enterprise AI - QR Code
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1 aflevering
Audio
Luister in Apple Podcasts
Gratis0%
1 aflevering
Audio
Luister in Apple Podcasts
Uitgebracht: 2026-02-01
© 2026 Agentic Coders. All rights reserved.
Meest recente aflevering
Why Your Enterprise Needs Its Own LLM

Why Your Enterprise Needs Its Own LLM

Alex and Maya break down Abhijeet Patil's hands-on account of building a domain-specific LLM for the enterprise. Why do 88% of organizations use AI but nearly two-thirds haven't scaled it? Why did 77% of his training data turn out to be duplicated? How
Tijd: 9:47
Afspelen
Alex and Maya break down Abhijeet Patil's hands-on account of building a domain-specific LLM for the enterprise. Why do 88% of organizations use AI but nearly two-thirds haven't scaled it? How did a focused 7-billion parameter model hit 95% accuracy with near-zero hallucinations for $15 per training run?
Topics covered:
- The agentic AI storm and McKinsey's 2025 findings
- The Pluribus Syndrome: why foundation models sacrifice depth for breadth
- The CIO's dilemma: data privacy as the #1 barrier (IBM, 57%)
- RAG vs fine-tuning: reference books vs muscle memory
- DeepSeek's 7B model scoring 92.8% where GPT-4o managed 74.6%
- QLoRA fine-tuning on a single GPU for $15
- The 77% data duplication gut punch
Part 1 of the Building Enterprise AI series.
Full article: https://agenticcoders.dev/articles/domain-specific-llms-part1.html
#enterpriseAI #LLM #fineTuning #domainSpecificAI #QLoRA #agenticAI
Aflevering-ID: 1000750881267
GUID: agenticcoders-building-enterprise-ai-part1
Releasedatum: 1-2-2026 01:00:00

Beschrijving

Building Enterprise AI is a podcast about domain-specific LLMs, fine-tuning, and deploying AI systems in the enterprise. Hosted by Agentic Coders, each episode covers hands-on experience with agentic AI, LoRA and QLoRA training, deployment architectures on AWS, and the business case for machine intelligence. Real practitioners share what broke and how they fixed it. No hype. No theory.

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