LLMs for Devs: Model Selection, Hallucinations, Agents, AGI – Jodie Burchell | The Marco Show

Confused about which LLM: ChatGPT, Claude, or Gemini, is best for your dev projects?

In this interview, Dr. Jodie Burchell, data scientist and developer advocate in data science, breaks down the LLM landscape for 2025. Discover the key criteria for choosing the best AI model: performance, cost, use-case fit, and more, so you don’t waste tokens (or your budget) on the wrong solution.

What you’ll learn:
– Choosing the best LLM for YOUR use case: from code generation to data analysis
– How to compare LLMs
– Why most AI model assessments are flawed
– Enhanced vs Adaptive thinking: Is your AI model truly intelligent?
– Future-proofing your developer workflow for 2025 and beyond
– Privacy, self-hosting, and cost: what every developer should know
– Copyright lawsuits, climate concerns, and the ethics of AI
– Hallucinations, confidence, and the AI self-reinforcement loop
– Will AGI arrive in the next 5 years?

🎁 Giveaway
If you could name your own LLM, what would you call it?
Reply in the comments. The most creative answer wins either a JetBrains merchstore coupon or a free 1-year license to your favorite JetBrains product.

⏱️ Timestamps:
00:00:00 Teaser
00:00:37 Intro
00:01:08 From PhD and academia to data science at JetBrains
00:02:31 Early NLP versus modern LLMs
00:04:46 From LSTMs to Transformers (BERT and GPT)
00:08:49 The DeepSeek surprise and model scaling limits
00:12:25 Benchmarks, assessments, and confusion for end users
00:17:18 Choosing models in practice
00:21:10 “Thinking” models and reasoning limits
00:23:48 Do you really need the newest model?
00:25:58 Hallucinations and how to handle them
00:28:30 Agents and RAG: real-world applications
00:32:55 Vibe coding: hype versus reality
00:37:46 What are AI agents? Tools, MCP, and multi-agent apps
00:43:01 Self-hosting versus proprietary models
00:45:20 Fine-tuning explained and Hugging Face
00:50:17 Building reliable AI apps (tests, A/B, traces)
00:55:33 Privacy, company data, and self-hosting concerns
00:58:37 Ethical issues: data sourcing and labor
01:04:23 Environmental costs and the push for smaller models
01:06:26 Juniors, skills, and the future of coding with AI
01:09:15 Learning fundamentals in the age of LLMs
01:13:24 AGI: definitions, timelines, and Jodie’s twenty euro bet
01:20:03 Rapid-fire questions: slang, food, and culture
01:25:47 Giveaway
01:26:26 Outro

Follow Jodie Burchell:
LinkedIn:   / jodieburchell  
Bluesky: https://bsky.app/profile/t-redactyl.b...
Mastodon: https://mastodon.social/@t_redactyl@f...

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