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In this episode, we examine how the software industry is fundamentally changing. We're joined by our expert guest, Matt Edmunds, a long-time UX director, principal designer, and Principal UX Consultant at Tiny Pixls. The episode kicks, analyzing how early AI implementation in Applicant Tracking Systems (ATS) created rigid hiring processes that actively filter out the varied candidates who actually bring necessary diversity to engineering teams.
Of course we get to the world of "vibe coding", and revisit the poor LLM usage highlighted in the DORA 2025 report, exploring how professionals without traditional software engineering backgrounds are leveraging models to generate functional code.
Matt details his hands-on experience using the latest models of Claude Opus and Gemini Pro, successfully building low-level C virtual audio driver in 30 minutes drive by personal needs. We discuss the inherent challenges of large context windows, and coin the term "guess-driven development". To combat these hallucinations, Matt shares his strategy of using question-based prompting and anchoring the AI with comprehensive test files and documented schemas, which the models treat as an undeniable source of truth.
Beyond the code, we look at the broader economic and physical limitations of the current AI boom, noting that AI providers are operating at massive financial losses while awaiting hardware efficiency improvements.
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