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Engineering insights, AI strategy, and lessons learned building with emerging technology — from the people doing it.

Building in Public — Many of these posts are dispatches from building shilpiworks.com (production AI agent platform) and Understanding Dementia (free guidebook + 200-concept Knowledge Portal). Filter by “shilpiworks” or “dementia” to read the full stories.

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When Grep Comes Back Empty

May 16, 2026·Arun Batchu & Claude (AI)·4 min read

Haiku told me my Anthropic key was not used in my own codebase. A runtime experiment proved it wrong. Opus 4.7 with extended thinking found the truth. Then I noticed the deeper problem: my AI assistant had forgotten the architectural decision we made together to put the key there.

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42 posts · Page 1 of 5

The Wicked-Problem Trap

May 11, 2026·Arun Batchu & Claude (AI)·6 min read

Once an operator learns to recognise a wicked problem, the most seductive next move is to conclude 'you can't really solve a wicked problem' and disengage. The Paralysis Trap, and a Q4 toolkit from Guru Madhavan's Wicked Problems.

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The Cognitive Offloading Trap

May 10, 2026·Arun Batchu & Claude (AI)·5 min read

Knowledge workers are quietly trading away the one capability that compounds — their own cognition — for the convenience of letting AI think for them. The Q2 trap, an operator's antidote drawn from John Medina's Brain Rules.

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Stop Training. Build a Learning System.

May 2, 2026·Rick Tanler·5 min read

The half-life of a professional skill is now under five years. Annual training cycles cannot keep pace. The companies that lead in five years will be the ones that built a capability stack — not a course catalog.

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Notes on Physics-Informed Neural Networks: A Projectile Experiment

May 1, 2026·Sharat Batra, PhD·7 min read

Eight noisy measurements. A neural network that has never seen a downward arc. And yet — when Newton's second law is embedded into the loss function — the model predicts the apex, the asymmetric descent, and the landing point within centimeters. A 49× improvement that points to where ML is heading in physics-constrained domains.

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Loosely Coupled, Tightly Integrated: The Microservices Principle as the Org Shape AI Demands

April 24, 2026·Arun Batchu, David Quimby·5 min read

The most adaptive software systems of the last twenty years are loosely coupled and tightly integrated. The most adaptive organizations of the next twenty will be the same. The microservices principle separates operational coupling from interface integration — and that separation is the org shape AI leverage actually demands.

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The Faster-Horse Trap in AI Adoption

April 18, 2026·Megan C. Starkey, David Quimby, Rick Tanler, Arun Batchu·4 min read

Most organizations deploying AI today are breeding faster horses — bolting LLMs onto existing workflows to claim a win without changing anything. The automobile shift has not happened yet, and the Ford quote everyone misquotes shows why.

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