As enterprise AI stacks grow increasingly complex, the race is on to simplify data pipelines, unify developer work surfaces, and tame ballooning token costs.
They explore RegattaDB's unified engine for OLTP, analytical, and vector workloads, Atlassian's expanding AI lifecycle strategy, and Mitch's eight-layer AI Stack framework highlighting why "presence is not completeness." They also discuss the industry drama surrounding Moonshot AI's 2.8-trillion parameter Kimi K3 open-weight model, Anthropic’s distillation accusations, and the economic shift toward local models.
To close out, Brad shares key takeaways from migrating to Google's Anti-Gravity CLI and what new agent workspace protocols mean for future developer workflows.
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