Abhishek Shankar's Blog

Agent Native Landscape

  1. A typology of CMS-as-agent-substrate patterns that work vs the ones that don't

    The framing most teams reach for when they start building agentic workflows on top of a content management system is architectural: the CMS is the database, the agent is the…

  2. Erdős's Conjecture Fell to a Closed AI Loop. That's the Story.

    On May 20, 2026, OpenAI published an eighteen-page PDF containing a proof that disproves a conjecture Paul Erdős posed in 1946. The closed-loop pipeline that produced it — AI-written prompt, AI-generated proof, AI-graded verification, human review only at the end — is the structural story the press coverage is missing.

  3. The Three Pillars Autonomous Research Keeps Mis-Building

    Autonomous research agents have six pillars. Three operational, three epistemic. The epistemic ones — search, memory, verification — are built wrong.

  4. The Substrate Triad — Memory and Identity Aren't Enough

    The substrate of a persistent agent is three things, not two. Memory is dumb storage. Identity is compressed posture. Continuity is the bridge — the layer almost no production system implements deliberately.

  5. The Averaging Tax — Why Class Conditioning Isn't a Feature

    Class conditioning isn't a control feature added to flow models — it's the mathematical fix for a contradiction the unconditional formulation can't solve. The same logic explains why the action in generative AI keeps moving up to the conditioning layer.

  6. Spark and the end of the chat-first era

    Spark is not Gemini's new agent mode — it's the second tab inside the Gemini app, and the structural admission that the chat-first era is ending. Search-first taxed merchants for attention; chat-first taxed users for cognition; agent-first taxes the action itself, and Google has just shipped the front door.

  7. The Pirated Corpus Was Always a Balance-Sheet Item

    Anthropic's $1.5 billion settlement is being read as a deterrent. It is much closer to a tariff — a price tag on an arbitrage that produced an asset worth more than the tariff itself, and an arbitrage that is now closed for everyone else. The corpus is gone; the model remains; the second mover faces a different trade entirely.

  8. How Subquadratic Won by Giving Up on Replacing Transformers

    Subquadratic architectures won by surrendering. They stopped trying to be transformers and became the substrate transformers run on top of — in a 3:1 ratio that is starting to look uncannily empirical.

  9. Anthropic, OpenAI, and the New Species of Services Firm

    Services firms do not sell skill. They sell institutional predictability — a composable thing made of definable primitives — and the unit of sale is the primitive bundle, not the consulting hour. When the bundle changes, the firm changes.

  10. The Frontier Stopped Being the Model

    The May 12, 2026 alphaXiv trending feed has zero new-model papers in the top twenty. The unit of progress in AI has moved out of the pretrain and into the loop — distillation pipelines, self-evolving agent runtimes, discovered test-time procedures. This piece argues the frontier-lab moat shrinks to the distillation step, with three falsifiable predictions for the next twelve months.

  11. You Can't Buy Sonnet

    The $5,000 AI mini PC market sells against a model nobody is offering. A structural map of why the hybrid stack is the only architecture that survives — and what to actually do in May 2026.

  12. The Skill Reuse Layer Nobody Admits They're Building

    Production agentic AI isn't a reasoning problem. It's a systems engineering problem. And the companies that admit it first will own the 2026-2028 window.