DiscoverMixture of ExpertsAI code generation: Wins, fails and the future
AI code generation: Wins, fails and the future

AI code generation: Wins, fails and the future

Update: 2025-12-26
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What’s the future of AI code generation? This week on Mixture of Experts, host Tim Hwang is joined by Chris Hay, Olivia Buzek and Gabe Goodhart to debrief the biggest AI use-case of 2025: AI-powered software engineering.  


Claude Opus 4.5  solved a months-long optimization in under an hour but failed spectacularly at simple tasks. The barbell effect is real. Next, who's the architect—you or the model? We discuss agent orchestration, context windows and why tool performance varies wildly. Then, model differentiation: are OpenAI and Anthropic fundamentally different, or does agent architecture matter more? Finally, can open-source compete with closed ecosystems? We explore vertical integration, inference costs and the future of open models. All that and more on this week's Mixture of Experts


00:00 – Introduction 

01:11 – The barbell problem: AI coding wins and fails 

03:46 – Claude Code cracks Apple Metal optimization 

07:52 – Who's the architect: You or the AI? 

11:44 – Model vs agent orchestration 

20:44 – The future of unsupervised AI agents 

24:30 – Open source vs proprietary tools 

33:22 – The inference cost challenge 


The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

 

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Visit Mixture of Experts podcast page to get more AI content → https://www.ibm.com/think/podcasts/mixture-of-experts 

Learn more about AI code generation → https://www.ibm.com/think/topics/ai-code-generation  

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AI code generation: Wins, fails and the future

AI code generation: Wins, fails and the future

IBM