Prompted by Tim Heath’s (Yolo Group) LinkedIn post arguing iGaming may no longer need many developers, host Sam Bhatti and Strahinja Radman discuss AI’s impact on iGaming development and tech development in general.
Radman frames AI as the next abstraction layer in software evolution, explaining LLMs as pattern-recognition systems that generate token-by-token output and often make incorrect assumptions without strong context and constraints. They discuss how effective use requires an expert to conceptualize architecture, define business rules, break work into manageable domains, and test components separately, noting practical limits like token cost and “prompt too long” failures.
In the context of building BetHero’s proprietary iGaming tech, they discuss why developers favor Claude Code and compare major models Gemini 3, Claude (Opus 4.6), and OpenAI/ChatGPT (Codex 5.3)—with Claude strongest at complete code output, ChatGPT best for high-level architecture and requirements, and Gemini strongest for producing extensive documentation.
Radman argues AI won’t replace developers, especially due to debugging, maintenance, and the need for specialized roles (QA, frontend, backend, security), emphasizing production readiness requires careful planning and monitoring.
They close with career advice: don’t fear AI, learn how it works, build high-level design skills first, deepen fundamentals (including databases), and prioritize adaptability and achievement-oriented follow-through as key hiring traits.
00:00 Cold Open & Getting Set to Record
00:26 Tim Heath’s Hot Take: Do We Still Need iGaming Developers?
01:36 From Assembly to AI: Why LLMs Are the Next Abstraction Layer
03:02 LLMs 101: Pattern Recognition, Context, and How They ‘Think’
04:27 Can AI Build Complex Apps? Requirements, Assumptions, and Prompting
08:24 Architecture First: Breaking Work Into Domains & Components
11:43 Key Terms Explained: Tokens, Monoliths, and Microservices
15:01 Which AI Tool for What? Claude vs ChatGPT vs Gemini (and Why)
20:37 Why AI Won’t Replace Dev Teams: Debugging, Maintenance, and Specialties
24:21 Career Advice: How Developers Should Learn and Leverage AI
28:29 Hiring Signals: Adaptability, High Achievement, and Using the ‘Turbocharger’
31:12 Wrap-Up & Final Message: Don’t Be Afraid to Step Into the Unknown
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