STRATEGIC INTELLIGENCE FOR AI DECISION-MAKERS

·28 May 2026·AI sticker shock hits corporate America - Companies begin to question the payoffs of toxenmaxxing.

Signals:

• →Unchecked AI spending is creating unsustainable costs without delivering clear, measurable business returns.
• →Indiscriminate AI deployment often fails to prioritize high-value revenue-generating tasks over trivial activities.
• →Leaders must shift from experimental "tokenmaxxing" to disciplined, efficient, and strategic AI implementation.

·23 May 2026·There is no self-evidence: - There is no self-evidence: A physics of emptiness realisation 1∗ 2 3,4,5 Lars Sandved-Smith Chris Fields Thomas Doctor 6,7,8 1 Ruben Laukkonen Jakob Hohwy May 23, 2026 1Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Australia 2Allen Discovery Center, Tufts University, Medford, MA, USA 3Kathmandu University Centre for Buddhist Studies, Rangjung Yeshe Institute, Kathmandu, Nepal 484000: Unlocking the Tibetan Buddhist Canon for All, Fremont, CA 94539, USA 5Center for the Study of Apparent Selves, Kathmandu 44600, Nepal 6Flourishing Intelligence Program, Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK 7Department of Psychiatry, University of Oxford, Oxford, UK 8LIFE, London, UK Abstract Anysystemthatpersistsmustminimisesurprisal, therebygatheringevidencefor its own generative model, a process known as self-evidencing.

Signals:

• →Demonstrates that self-environment boundaries are unmeasurable, rendering ontological claims about a separate self groundless.
• →Models contemplative practice as a formal process of reducing rigid, unevidenced structural priors.
• →Predicts that emptiness realisation enhances cognitive flexibility and shifts neural dynamics toward criticality.

·Introducing Claude Opus 4.8 \ Anthropic - Our latest model, Claude Opus 4.8, is an upgrade to our Opus class of models, with stronger performance across coding, agentic tasks, and professional work, and the consistency to handle long-running work.

Signals:

• →Opus 4.8 offers improved reasoning, reliability, and honesty for complex, high-stakes professional workflows.
• →New dynamic workflows and effort controls allow organizations to optimize AI performance and costs.
• →Enhanced agentic capabilities enable more autonomous, large-scale technical tasks with greater accuracy and efficiency.