ParaSure

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Agentic AI could reshape how economic activity gets coordinated. At @EconClubNY, @jerallaire explains why that could lead to more efficient organizations and new models for how corporations operate.

⚡️ LATEST: a16z's Marc Andreessen says AI agents will excel most in complex, edge-case-heavy domains like SaaS migration, precisely where humans struggle the most.

AI is the new engine of trade. AI-related goods made up a staggering one-third of global trade growth in 2025, driven by demand for semiconductors and data-center equipment. Explore the data: mck.co/GeopoliticsTra…

The Gulf is open for business! 💧 Copious amounts of moisture will stream northward into the United States over the next few weeks, benefiting drought-affected areas. However, this will also increase the risk of flooding and severe weather in the Plains and Midwest.

🚨 BIG: AI agents are already scanning hundreds of prediction markets per second, outpacing any human trader.

📍 AI will not eliminate roles. It will stratify capability. McKinsey signals that the agentic organization demands new talent architectures. The shift is not headcount reduction. It is skill redistribution. 1️⃣ Competitive Shift General managers evolve into M-shaped orchestrators of hybrid workflows, integrating AI, domain depth, and socioemotional judgment across systems. 2️⃣ Structural Blind Spot Firms assume existing managers and specialists can absorb agentic tools without redefining role expectations, incentives, and accountability. 3️⃣ Strategic Risk Organizations that fail to realign talent profiles will experience coordination breakdowns as AI capabilities outpace managerial integration capacity. This is not reskilling at the margin. It is re-architecting workforce design. Are you preparing leaders to supervise agentic systems, or asking legacy roles to govern a new paradigm? mckinsey.com/capabilities/p… @corixpartners @Transform_Sec @Corix_JC @ILoveBooks786 @COSTESLionelEr @ramonvidall @RLDI_Lamy @FrRonconi @timo_vi @Nicochan33 @NathaliaLeHen @TCyberCast @arigatou163 @VivMilanoFSL @bulbi59 @BulbiT3ch @sonu_monika @MathildaLoco @faryus88 @bbailey39 @BindIdeas971 @FmFrancoise @quepasachico @sustainrach @iamtunslaw @Grzebalski86888 @EduFirst @DailyThailand2 @rameshambastha @DonaldGavis @ricardo_ik_ahau @miguelgonzalezr @sulefati7 @ALouiseLavalett @Tech2Specialist @ozsilverfox @i_gestio13730

📍 AI agents are not scaling evenly. They are concentrating authority in specific industries. As McKinsey highlights, AI agent scaling is highest in technology, media, telecom, and healthcare. This is not sector enthusiasm. It reflects where organizations are structurally able to hand over control to systems. 1️⃣ Control Point: Industries with modular workflows and strong data infrastructure can embed agent autonomy faster. Decision authority shifts from roles to systems in these environments. 2️⃣ Structural Blind Spot: Most sectors assume adoption is transferable. It is not. Without standardized processes, clean data layers, and clear ownership, agents cannot take on execution responsibility. 3️⃣ Concentration Risk: Early movers will compound advantage by embedding AI into core operations. Others remain stuck in assistive use cases, widening the capability and control gap. This is not industry variation. It is a signal of which organizations are structurally ready to redesign authority. The real divide is not who adopts AI agents. It is who can trust them with decisions. Which parts of your organization are structurally ready to give up control? via McKinsey & Company mckinsey.com/capabilities/q… @corixpartners @Transform_Sec @Corix_JC @ILoveBooks786 @COSTESLionelEr @ramonvidall @RLDI_Lamy @FrRonconi @timo_vi @Nicochan33 @NathaliaLeHen @TCyberCast @arigatou163 @VivMilanoFSL @bulbi59 @BulbiT3ch @sonu_monika @MathildaLoco @faryus88 @bbailey39 @BindIdeas971 @FmFrancoise @quepasachico @sustainrach @iamtunslaw @Grzebalski86888 @EduFirst @rameshambastha @DonaldGavis @ricardo_ik_ahau @sulefati7 @ALouiseLavalett @ozsilverfox @i_gestio13730 @BCAgroup @kkruse @9SManagement @O_Berard

NEW AI report from Google. Every prior intelligence explosion in human history was social, not individual. These authors make the case that the AI "singularity" framed as a single superintelligent mind bootstrapping to godlike intelligence is fundamentally wrong. This is directly relevant to anyone designing multi-agent systems. They observe that frontier reasoning models like DeepSeek-R1 spontaneously develop internal "societies of thought," multi-agent debates among cognitive perspectives, through RL alone. The path forward is human-AI configurations and agent institutions, not bigger monolithic oracles. This reframes AI scaling strategy from "build bigger models" to "compose richer social systems." It argues governance of AI agents should follow institutional design principles, checks and balances, role protocols, rather than individual alignment. Paper: arxiv.org/abs/2603.20639 Learn to build effective AI agents in our academy: academy.dair.ai

software-as-a-worker

Private Equity Giant Vista Equity released their 2026 outlook on Agentic AI. Here are a few statements that caught my eye:

We have been surpassed: AI written output exceeded human written output in 2025