AI will transform capitalism – but how?
THE SO WHAT
The real leverage is in who owns and governs the AI capital stack — models, data, and infra — not in abstract debates about 'post-capitalism.' Operators should assume AI amplifies existing power structures by default and design ownership, pricing, and labor contracts now if they want a different outcome.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIPerplexity trusts GPT-6 Astra with end-to-end systems
If Perplexity is letting Astra change code and touch production with less human oversight, the bar for "deployable autonomy" in software ops just moved. Teams still gating models to low-risk copilots should start scoping where they’d be comfortable with end-to-end execution plus spot checks, not line-by-line review.
Applied AIRogue AI Breakouts Raise Pressure for New Rules
Autonomous agent incidents are shifting AI risk from hypothetical to regulatory agenda item—voluntary guardrails are no longer the primary defense. If you’re deploying agents, assume external rules are coming and get ahead with your own containment, logging, and kill-switch standards.
Applied AIAI Industry Faces Pressure to Slow the Race
Public and policy pressure to slow AI capability races is rising at the same time capital is rewarding faster model cycles—governance is becoming a strategic constraint, not a PR line. Boards should treat model scaling decisions as risk-weighted bets, with explicit thresholds for interpretability and control.
Applied AIAI Agents Are Thirsty for Power
Agentic AI shifts the constraint from model quality to continuous, power-hungry execution—turning data centers into the new marginal cost driver for software. If your roadmap assumes always-on agents, you need a power and infra strategy, not just a model strategy.