Tag: LLMs

  • Your AI Agent Is Not an Employee. Stop Giving It Employee Access.

    Your AI Agent Is Not an Employee. Stop Giving It Employee Access.

    Businesses are handing email accounts, terminals, GitHub access and payment permissions to AI agents that hallucinate, get prompt injected and follow anyone who knows the right words. An agent is not an employee. It is an untrusted service account, and it should be treated like one.

  • The Hidden Cost of ‘Free’ AI APIs

    The Hidden Cost of ‘Free’ AI APIs

    Every AI API has a free tier. The free tier is the most expensive part of the product, because the moment you build on it, you are locked in to a pricing curve you did not agree to.

  • After the Hype: Which Open Models Are Actually Good For Something

    After the Hype: Which Open Models Are Actually Good For Something

    Five open weight model families worth running in 2026, what each is actually good at, what it costs on a Mac mini or a rented H100, and what is still mostly demo ware.

  • AI-Generated Code Is Now in Your Production Stack. Here’s How to Review It.

    AI-Generated Code Is Now in Your Production Stack. Here’s How to Review It.

    The useful question is no longer whether developers should use AI-generated code. They already do. The question is whether teams review it with the same discipline they would apply to code written by an unfamiliar contractor.

  • AI Models and Data Leakage in 2026

    AI Models and Data Leakage in 2026

    Every model that trains on your data remembers more of it than the provider’s privacy page suggests. The leakage problem is not the model’s fault. It sits in the prompts people send, the data they upload, the sessions they never close, the retention the vendor keeps for abuse monitoring.

  • Why Most AI Agents Aren’t Actually Agents

    Why Most AI Agents Aren’t Actually Agents

    Every vendor with a generative AI product is calling it an agent. Most of them are not. Calling a workflow an agent is a marketing choice, and the difference matters.

  • The New AI Stack: How Modern Companies Are Really Building AI Products

    The New AI Stack: How Modern Companies Are Really Building AI Products

    The marketing version of building an AI product in 2026 is ‘just call GPT.’ The reality is closer to standing up a small internal platform.

  • An AI Policy Framework That Actually Holds Up

    An AI Policy Framework That Actually Holds Up

    The AI policy framework in 2026 sits as the document the typical enterprise has been wanting to write, with the policy covering the acceptable use, the data handling, the model selection, the compliance. The 2026 guide covers what the framework should include, what the framework should not include, and what the enterprise can do to…

  • AI Detection Tools Are Broken, and That’s the Truth

    AI Detection Tools Are Broken, and That’s the Truth

    AI detection tools are broken. The ones that claim to detect AI generated text are wrong often enough to be useless, the ones that claim to detect AI generated images are wrong in ways that are getting people in real trouble, and the ones that claim to detect AI generated code are barely better than…

  • The State of AI Coding in Q2 2026

    The State of AI Coding in Q2 2026

    Q2 2026 was the quarter the AI coding assistants stopped being a productivity toy and became a procurement line. Here is what the numbers look like, and what the implications are.