The article explores the concept of 'efficiency' and how the relentless pursuit of optimisation can lead to unintended consequences. It begins with the example of hospital bed occupancy in England, where 95% of beds were occupied during flu season, leaving no room for unexpected surges in patients. This illustrates the first trap of optimisation: removing slack from systems, which makes them vulnerable to disruptions. The second trap is having a narrow definition of 'best', as seen in Milton Keynes' roundabout-heavy road system that prioritised traffic flow over passenger comfort. The third trap involves conflicting optimisations, demonstrated by the 2010 Flash Crash in US financial markets where automated trading algorithms caused extreme volatility. The article then connects these traps to artificial intelligence, warning that AI systems might remove human oversight, focus narrowly on measurable metrics while ignoring judgment or empathy, and interact in unpredictable ways when multiple systems collaborate. The authors argue that the challenge isn't just finding the best answer but deciding what 'best' really means and knowing what not to optimise away. The piece concludes by emphasising that while optimisation has brought significant societal benefits, avoiding these traps is crucial as optimisation becomes more powerful.

The Real Question Is Why Some Systems Reward Exploitation While Others Reward Contribution

Kiloampere busbars, 2,000 V solar platforms, hollow-shaft robot joints and nanoamp standby budgets are pulling magnetic sensing in directions no single sensing principle can follow. Ask a traction inverter designer, a robotics engineer and someone building a battery-powered water meter what they need from a magnetic sensor, and you will get three answers with very little overlap. The inverter designer is measuring current across an enormous range, from a few amperes in control circuits to several hundred amperes or more in the traction inverter and battery main circuit, carried on busbars that will never pass through a PCB.

A practical 10M events/day webhook delivery architecture: partition keys, retry storm control, per-tenant isolation, idempotency storage, replay UX, and reliability SLOs.

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12 common problems. 12 solutions every backend developer should know.

🧩 *DESCRIPTION* A dashboard reads 99.99% uptime, green across the board — and underneath, every third response is quietly wrong. Up the whole time and wrong some of the time are two different guarantees, and most engineers only learn the gap between them once it's already broken something in produc

Cadence Design Systems Inc. has introduced the Maestro AI Model Portfolio, a collection of domain-specialized artificial intelligence models designed to power agentic workflows across semiconductor and system design. The portfolio integrates specialized models with Cadence AI Super Agents, electronic design automation (EDA) and system design automation (SDA) tools, and reinforcement learning (RL) to improve engineering outcomes and accelerate development. The Maestro AI Model portfolio combines post-trained large language models (LLMs), trained decision models, and self-improving agent skills. It is designed to work with Cadence AI Super Agents, including AuraStack, …