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This article examines the friction that arises when users shift from exploratory conversation with AI tools to precise task delegation. Through direct observation of seven people working with AI, the author identifies three interaction styles (collaborative, commanding, over-explainers) and reveals how conversational fluency in AI interfaces creates false expectations of shared understanding, leading users to accept suggestions that drift from their original intent.

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Firsts: The Demo - Doug Engelbart Institute

This webpage documents Doug Engelbart's legendary 1968 demonstration at the Fall Joint Computer Conference, where he and his team showcased revolutionary interactive computing technologies including the mouse, video conferencing, and collaborative editing. The page serves as a portal to archived footage, retrospectives, and historical materials commemorating what became known as "The Mother of All Demos," emphasizing both the technical innovations presented and the ambitious vision of augmenting human intellect that motivated the work.

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Agentic AI design patterns: 2026 edition

This article presents a comprehensive architectural framework for agentic AI systems in 2026, arguing that most AI failures stem from architectural problems rather than model quality. The author defines four canonical design patterns (Reflection, Tool Use, Planning, and Multi-Agent) and emphasizes that agentic AI represents a paradigm shift from monolithic systems to distributed, observable, and bounded agent architectures.

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From generative to agentic AI: a roadmap in 2026

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.

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From Org Chart to Work Chart: Where AI Value Really Comes From

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.

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State of RAG & GenAI

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.

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Tri-System Theory (Shaw & Nave, 2026)

Vincent Rump introduces the Tri-System Theory (Shaw & Nave, 2026), which extends Kahneman's dual-process model by proposing a third cognitive system β€” artificial cognition (AI) β€” that actively participates in human reasoning and decision-making. The post argues that humans increasingly defer to AI outputs with minimal critical reflection, a phenomenon the authors call "cognitive surrender," which improves decision quality when AI is correct but degrades it when AI is wrong β€” while trust remains consistently high either way. This raises urgent questions about human autonomy, expertise, and responsibility as cognition becomes a hybrid, human-AI process.

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LLMs corrupt your documents when you delegate

Microsoft researchers introduce DELEGATE-52, a benchmark of long document-editing workflows across 52 professional domains. Even frontier models (Gemini 3.1 Pro, Claude 4.6 Opus, GPT-5.4) corrupt about 25% of document content by the end of these workflows, and agentic tool use does not improve performance. The paper argues current LLMs are unreliable delegates: they introduce sparse but severe errors that compound silently over long interactions.

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The AI Draft: A Process Essay Nobody Asked For

Frank A. Kalman, a formally trained journalist, argues that using AI as a collaborative drafting partner is not a betrayal of craft but an honest extension of a writer's editorial process. He frames AI as a responsive thinking partner whose "wrongness" is productive, pushing the writer to clarify what they actually mean. The piece is a transparent, process-level account of how an experienced writer uses voice memos, AI chat, and iterative editing to reach a finished essay, positioned against the performative outrage of writers who conflate the suffering of drafting with the value of writing itself.

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Announcing: "Supercharged Human?"

Tactical Tech is a Berlin-based international non-profit that develops creative interventions, toolkits, and training programs to help individuals, communities, and educators critically understand the socio-political and environmental impacts of digital technologies. Its flagship announcement, "Supercharged Human?", targets teens and educators with ready-to-use AI literacy resources designed to foster critical engagement rather than passive adoption. The organisation frames its work around building civil society capacity to resist misinformation, digital extractivism, and uncritical AI use.

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Don't show me your AI. It is rude!

Marek Tuszynski (Tactical Tech) argues that the synthetic intimacy people develop with generative AI tools (an 'ELIZA effect') makes critical conversation about AI almost impossible: dependency forecloses critique. The piece curates 30 resources mapping AI's labor exploitation, environmental costs, military use, and concentration of power, framing AI critique as a moral and political project rather than a technical one.

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Visualising birdsong as a three-dimensional data array

A short Instagram reel by Lucio Arese visualises the song of a hemp bunting (Linaria cannabina) as a scatter plot, where pitch, amplitude, and timbre map directly to spatial position and density. The post argues that birdsong is not creativity but a tightly structured signal carrying territorial, genetic, and hormonal information: a 'biological blockchain' rather than a song.

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Recording robin interactions for visual models of shared manifolds

A process post by Lucio Arese: he is recording many interactions between robins and using the material to build visual models of 'shared manifolds' between multiple individuals, alongside reading the literature on territorial interactions. The work continues his project of treating birdsong as data; the new dimension is multi-individual rather than single-bird.