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Why the Same Question Produces Different Answers
Different answers to the same question are not always just randomness. This article separates generation, conversation context and version changes, and shows which differences need checking.
Don’t Bet a Critical Workflow on One AI Tool
A practical framework for assessing dependence on one AI service through inputs, task rules, acceptance criteria, adapters, human takeover and tested degraded modes.
Did Recommendations Actually Make Choosing Easier?
A close look at choice overload, ranking signals, exploration and agency to separate what recommendations save us from what they cannot decide for us.
Before You Delegate to AI, Decide What Must Stay Human
Starting with an agentic system’s ability to act in the external world, this article explains how consequences, permissions, data sensitivity and recoverability define delegation boundaries—and how approval, responsibility red lines, least privilege, traceable actions and rehearsed recovery constrain AI action.
How AI Actually Improves Productivity at Work: By Cutting Waiting, Switching and Rework
Drawing on research in writing, customer support, workplace collaboration and software development, this article explains when AI speeds direct tasks, when it shifts time into verification and rework, and how teams should measure net efficiency.
When AI Gives the Answer, Who Will Still Visit the Original Website?
Using Pew browsing data and generative-search research within their stated limits, this article separates answer satisfaction, source opening, verification and task completion, then proposes a falsifiable framework for page responsibility and measurement.
When AI Starts Working for You, the Real Change Is Not Efficiency
This article distinguishes task automation from workflow delegation, examines how continuous AI execution changes judgement, permissions, evidence, accountability and skill development, and proposes a practical five-step governance framework.
The EU AI Act Enters Its Implementation Phase: An Enterprise Compliance Guide
As the EU AI Act enters its implementation phase, compliance is becoming a basic capability for entering the European market and operating AI there over time. This guide follows four arguments: responsibility boundaries, risk-based controls, evidence across the supply chain, and governance embedded in everyday operations.
From 128K to 1M: What Long-Context Workflows Save and What They Add
Put long context back into concrete work such as contract review, cross-version comparison, and technical decisions. This article explains what 128K and 1M actually solve, and why retrieval, citations, and version control still matter.
How Open Models Affect User Control, Cost and Choice
A practical comparison of open access, open weights and open-source AI, examining hosted APIs, managed open-model services and self-hosting across data control, licensing, cost, operations, security updates and portability, with eight questions for decision-makers.
What Actually Makes AI Expensive?
From final training runs to HBM, advanced packaging, networking, depreciation, utilisation, inference scheduling and customer total cost of ownership, this article maps where AI spending goes and why a lower unit price does not guarantee lower total expenditure.
The power order behind the expansion of computing power
Starting from the difference between electricity and capacity, we track how power generation, transmission, grid connection, cooling and computing power scheduling jointly determine whether the model can continue to operate.
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