5 entries
This article argues that 2026 marks a fundamental shift from generative AI (passive, read-only text generation) to agentic AI (active, autonomous systems that plan and execute work). The author contends that AI engineers must move beyond prompt engineering and embrace systems engineering, treating AI as operational infrastructure that performs end-to-end tasks rather than conversational oracles that simply generate responses.
This article argues that AI value comes from redesigning workflows rather than inserting AI tools into existing organizational structures. The author contends that traditional org charts show hierarchy but obscure how work actually flows, and proposes work charts as a management tool that makes workflows, decisions, handoffs, and accountability visible for effective AI transformation.
This article argues that Retrieval Augmented Generation (RAG) has become a strategic imperative for enterprises in 2026, addressing critical challenges like LLM hallucinations, outdated outputs, and high retraining costs. RAG bridges the gap between large language models and organizational knowledge by retrieving verified, real-time data at the moment of generation, ensuring outputs are accurate, compliant, and trustworthy without requiring constant model retraining.
This is a documentation hub for GitHub Copilot adoption and best practices at NAV (the Norwegian Labour and Welfare Administration). The site provides news updates, tools, guidelines, and usage statistics for AI-driven development, focusing on custom agents, skills, and organizational implementation of GitHub Copilot across teams.
Collects over 12,000 open-ended metaphor responses from a nationally representative US sample across 12 months, developing a systematic framework to quantify how people conceptualise AI. Finds that Americans increasingly perceive AI as warm, competent, and human-like, with attributions of warmth and human-likeness rising significantly in the year after ChatGPT's release. Demographic variation matters: women, older individuals, and people of colour are more likely to attribute human-like qualities, and these perceptions strongly predict trust and willingness to adopt AI.