AI code generation: Wins, fails and the future
35 min•26 december 2025
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.
Subscribe for AI updates → https://www.ibm.com/account/reg/us-en/signup?formid=news-urx-52120
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
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.
Subscribe for AI updates → https://www.ibm.com/account/reg/us-en/signup?formid=news-urx-52120
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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