Coté

Tag: AI

  • Employee avoiding AI, doing manual work instead

    A new global survey of 3,750 executives and employees across 14 countries, conducted by SAP subsidiary WalkMe for its fifth annual State of Digital Adoption report, finds that more 54% of workers bypassed their company’s AI tools in the past 30 days and completed the work manually instead. Another 33% haven’t used AI at all.…

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  • AI won’t fix your broken culture

    Expecting AI to improve dysfunctional parts of your business probably won’t go well: The strongest candidates are workflows that repeat at meaningful scale, have clear ownership, and can be measured for quality, risk, and business value. 🔗 How to manage AI investments in the agentic era

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  • Anthropic Cowork usage by business function - business process & operations leads at 33.4%

    Normie AI Usage: Figures & Findings

    Programmers are still the dominant users of UI and, thus, drive AI use cases. The much larger market are “normies,” people outside of the IT department who are doing “knowledge work” and other tasks in organizations. I asked the AI to pull together a list of what those activities are and the momentum around them.…

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  • Taste Is in the Spec (Cooking Is Not the Recipe)

    The big problem is that the slop will be in how the software works. The flow. The defaults. The thousand tiny decisions about what to make easy and what to make possible. An agent has no opinion about whether this should be one screen or three. It has no taste. 🔗 Taste Is in the…

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  • Harness engineering is the new DevOps

    Are we going to see harness engineering teams? Yes: these are already emerging. It’s too early to say, but that feels wrong in the same way that DevOps teams were a misunderstanding of DevOps-the-movement. My belief is that while there is friction in having every team create their own harness, that friction is generative and…

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  • training your replacement

    Yes: the work is moving from writing code to specifying, verifying, and curating knowledge. But: the code is the better spec. Their point: code is the only artifact that’s unambiguous, executable, and – this is the big one – deterministic. A prose spec is fuzzy and an agent will interpret it a little differently every…

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  • AI Fiction in the Wild

    Analysis of 573K WildChat conversations finds over a third involve fiction generation, dominated by power users obsessively iterating on fanfiction and erotica. Summarized by AI. 🔗 AI Fiction in the Wild

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  • The Mills Review: AI and the future of retail financial services

    The FCA-commissioned review argues retail finance is shifting toward continuous AI delegation with general-purpose LLMs operating outside regulatory oversight. Proposes seven foundational reforms, including an AI-enabled agentic supervisory model and trusted agent frameworks. Summarized by AI. 🔗 The Mills Review: AI and the future of retail financial services

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  • How NatWest is using AI

    The NatWest CIO goes over how they’re using AI with some use cases. Some: “Today at NatWest, over 40% of all code is either AI-generated or AI-assisted.” AI use: “If you’re a relationship manager, if you’re a branch manager, or you’re sitting as a teller in the branch, whatever that role is, you’ve got better…

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  • 6 use cases for agentic AI in major IT incident management

    Six ways to use an AI operations assistant in major IT incident management, aimed at improving team efficiency, sharing knowledge and delivering immediate value. Summarized by AI. 🔗 6 use cases for agentic AI in major IT incident management

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  • Reducing token usage

    Better Defaults (not Usage Caps) — Engineers can choose any model they want, but defaults matter. We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task. 91% of our employees were never hitting their usage…

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  • “this is the voice of American business that is being channeled through me”

    “Livid” was the word he used to describe enterprise customers who are “paying for tokens that create no value,” while handing over their data to the major firms and, in the end, taxing the public who will end up paying for it in some form. The reason, he ventured, was the “models have completely… irresponsibly…

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  • Signals for 2026

    The technology trends being watched for the new year, written three years into the generative AI era. Summarized by AI. 🔗 Signals for 2026

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  • AI in SRE Practice: Engineering Reliable Operations

    Argues Site Reliability Engineering faces a paradigm shift as AI adoption spreads through the software development lifecycle. With AI coding assistants accelerating code generation and deployment velocity, and organisations targeting up to a 4x productivity increase, traditional manual practices become unsustainable. Summarized by AI. 🔗 AI in SRE Practice: Engineering Reliable Operations

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  • The Intellectual and Moral Failing of Anti-AI Alarmism

    A critique of AI alarmism that argues human agency and responsible use of technology are overlooked by fear-driven public intellectuals. Summarized by AI. 🔗 The Intellectual and Moral Failing of Anti-AI Alarmism

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  • Question of sovereignty – debating what it means to keep control in the AI age

    This is a summary of Europe’s growing focus on AI and cloud sovereignty as a response to U.S. political volatility, vendor lock-in, and the operational risks posed by AI dependency. Summarized by AI. 🔗 Question of sovereignty – debating what it means to keep control in the AI age

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  • 🤖 Findings and CIO Retention Guide: Gender, Priorities, and Exit Triggers in High Tech

    🤖 Findings and CIO Retention Guide: Gender, Priorities, and Exit Triggers in High Tech

    Original: Beyond the Pipeline: A Gender Lens on Priorities and Exit Triggers in the High-Tech Industry by researchers at The Academic College of Tel Aviv-Yaffo, Communications of the ACM. Summarized by Claude AI on July 2, 2026. The Findings Men are far more committed to staying. 44.9% of men selected “no intentions to leave” vs.…

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  • Enterprise AI Gets Uber-ed, Smaller Models Cut Energy 90%, and Stop Building Innovation Labs – Related to your interests, Wednesday

    Enterprise AI Gets Uber-ed, Smaller Models Cut Energy 90%, and Stop Building Innovation Labs – Related to your interests, Wednesday

    Also: Target’s RAG pipeline, the 13-person B2B buying group, Uber on AI dev productivity, and prompt injection as role confusion. ICYMI Original content published since last time. War for Talent – Software Defined Talk #578 – “This week, we discuss Fable follow-up, Gartner’s AI Governance MQ, and the war for AI talent. Plus, Matt and…

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  • Cloud CISO Perspectives: How Google Cloud Security uses AI internally

    How Google Cloud’s security organisation uses AI internally, following its AI Threat Defense announcement, working toward autonomous software development lifecycle security. Summarized by AI. 🔗 Cloud CISO Perspectives: How Google Cloud Security uses AI internally

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  • A Theory of Prompt Injection (and why you should study roles)

    The research explains that language models identify token roles through writing patterns rather than secure structural tags. The study demonstrates how ‘malicious text sounding like a higher-privilege role’ enables injection attacks, and that role boundaries function as critical infrastructure isolating competing objectives within AI systems. Summarized by AI. 🔗 A Theory of Prompt Injection (and…

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