The Cloudcast

Aaron and Brian review some of the latest AI model releases and discuss how they would evaluate them through the lens of an Enterprise AI Architect. 
SHOW: 1003
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SHOW NOTES:
Last Week in AI Podcast #234
Artificial Analysis.AI
Opus 4.6 Release
GPT Codex 5.3 Release
GLM-5 Release
OpenAI Preparedness Framework
Sam’s Tweet that 5.3 Codex hit “high” ranking for cybersecurity
Fortune Article on 5.3 high ranking
TAKEAWAYS
The frequency of AI model releases can lead to numbness among users.
Evaluating AI models requires understanding their specific use cases and benchmarks.
Enterprises must consider the compatibility and integration of new models with existing systems.
Benchmarks are becoming more accessible but still require careful interpretation.
The rapid pace of AI development creates challenges for enterprise adoption and integration.
Companies need to be proactive in managing the versioning of AI models.
The industry may need to establish clearer standards for evaluating AI performance.
Efficiency and cost-effectiveness are becoming critical metrics for AI adoption.
The timing of model releases can impact their market reception and user adoption.
Businesses must adapt to the fast-paced changes in AI technology to remain competitive.
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As we move into Q1 2026, Brian talks about 3 rooms where he'd like to be a fly on wall to see the blueprints of significant AI companies shaping the markets. 
SHOW: 1002
SHOW TRANSCRIPT: The Cloudcast #1002 Transcript
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A FLY ON THE WALL IN 3 ROOMS IN 2026
Room1 - NVIDIA’s M&A Room (Chips, Software Stack, Hosting Services, Agentic Tools, etc.)
Room 2 - Anthropic’s Agentic Vision
Room 3 - TSMC’s 2028-2030 Planning
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Aaron and Brian explore the evolving landscape of AI over the next three years, discussing its economic implications, political influences, technological advancements, partnership dynamics, changing buying patterns, and the potential impact on job creation and destruction. They emphasize the uncertainty surrounding AI's future and the need for understanding its broader implications.
SHOW: 1001
SHOW TRANSCRIPT: The Cloudcast #1001 Transcript
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SHOW NOTES:
Stratechery (Ben Thompson)
WHAT DO WE WISH WE KNEW ABOUT AI IN 3 YEARS?
Economics
Politics
Technology
Regulations
Partnerships
Buying Patterns
Usage Patterns
Devices
Job Creation/Destruction

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If someone walked into your office today and asked you to build a framework for how to value software development, what would you think about it? 
SHOW: 1000
SHOW TRANSCRIPT: The Cloudcast #1000 Transcript
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SHOW NOTES:
Chainguard introduces Factory 2.0
On running a startup of Claude Code agents
Agentic Product Development and the Theory of Constraints
Software Abundance

HOW SHOULD SOMEONE THINK ABOUT THE ECONOMICS OF SW DEV IN 2026?
If someone walked into your office today and asked you to build a framework for how to value software development, how would you think about it? 
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Are we ready to move into an era of wild predictions about where the future of Enterprise software is headed in 2026 and beyond? 
SHOW: 999
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SHOW NOTES
The SPAC-king is going to fix legacy software 
All Enterprise software is dead 
Microsoft and Software Survival (Stratechery)
WHAT HAPPENS TO ENTERPRISE SOFTWARE NEXT?
How much do enterprises want to write their own software? 
How much do enterprises wish they could write more software?
How much do enterprises not understand the economics of owning their own software?
How much does “big SaaS” or just “big Enterprise software” actually help because people already know it?
Is it possible that this new Agentic-driven software could create a type of new software community? 
Are “open” software communities prepared for the emerging economics of AI-created software? 
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