AI-powered coding assistants are becoming a core part of modern development workflows. At the same time, many teams are increasingly concerned about where their code goes, how it’s processed, and who has access to it. By combining OpenCode with Docker Model Runner, you can build a powerful AI-assisted coding experience while keeping full control over your data, infrastructure and spend. This post walks through how to configure OpenCode to use Docker Model Runner and explains why this setup enables a privacy-first and cost-aware approach to AI-assisted development. What Are OpenCode and Docker Model Runner? OpenCode is an open-source coding assistant…
Author: drweb
GitLab today made generally available an agentic artificial intelligence (AI) platform that automates software engineering tasks ranging from planning to application security. Coinciding with the release of version 18.8 of the core GitLab platform, the GitLab Duo Agent Platform initially provides access to seven AI agents that DevOps teams can assign a range of tasks […]
Security Is a Developer Experience Problem, Rooted in Our Foundations If we want better security outcomes without slowing teams down, we should start where software actually starts. That requires secure foundations, like hardened images, that are safe by default. With better foundations, security becomes quieter, development becomes smoother, and the entire system works the way it should.
Let’s get the obvious out of the way right up front. AI isn’t a person. Thank you, Captain Obvious. We’re all on the same page. And yet, when we announced that AI is Techstrong’s “Person of the Year” for our Predict 2026 virtual event on January 15, a few folks felt compelled to remind us […]
Why a “protected repo”? Modern teams depend on public container images, yet most environments lack a single, auditable control point for what gets pulled and when. This often leads to three operational challenges: Inconsistent or improvised base images that drift across teams and pipelines. Exposure to new CVEs when tags remain unchanged but upstream content does not. Unreliable workflows due to rate limiting, throttling, or pull interruptions. A protected repository addresses these challenges by evaluating images at the boundary between public sources and internal systems, ensuring only trusted content is available to the build process. Routing upstream pulls through a Nexus…
Sklearn’s LogisticRegression is great for pure prediction tasks, but when I want p-values, confidence intervals, and detailed statistical tests, I reach for Statsmodels instead.The library gives you two main options for binary classification: Logit and Probit. Both model the probability that an observation belongs to class 1, but they use different link functions to transform the linear combination of predictors into probabilities between 0 and 1.Statsmodel Beginner’s Learning PathWhy Statsmodels When Sklearn Exists?Statsmodels comes from the statistics world, not the machine learning world. When I fit a model with statsmodels.api.Logit(), I get back an object that behaves like what you’d…
Decorators are a concept that can trip up new Python users. You may find this definition helpful: A decorator is a function that takes in another function and adds new functionality to it without modifying the original function. Functions can be used just like any other data type in Python. A function can be passed to a function or returned from a function, just like a string or integer. If you have jumped on the type-hinting bandwagon, you will probably want to add type hints to your decorators. That has been difficult until fairly recently. Let’s see how to type…
Austin, TX / USA, 14th January 2026, CyberNewsWire
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Explore the challenges of AI agents in DevOps pipelines, highlighting the importance of model-aware detection to improve security and reduce vulnerabilities.