Articles

As a college student new to programming, building a JavaScript weather app was a great way to learn and gain experience. In this article, I'll share my journey and provide a simple guide to help you create your own weather app.

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Product experimentation teams often struggle with causal inference on LLM-based features due to the opt-in trap, where users who click to opt in differ systematically from those who don't. Propensity score methods can help reweight comparison groups to approximate a randomized experiment.

The 'Aw, Snap!' error in Chrome is a sign of a Renderer Process failure, often caused by resource exhaustion. By managing tab resources and using isolation, you can prevent this error and protect your system's stability.

Chrome's V8 engine has a 4GB memory limit per tab, which can be breached by resource-intensive applications. To prevent Error Code 5, you must actively manage your browser's memory by suspending background tabs and discarding them when not in use.

Product teams can use counterfactual estimation to answer retrospective questions about the effects of AI prompt engineering, despite the lack of random treatment assignment in logged production data.

Standard product experiments answer a binary question about average efficacy, but uplift modeling turns that binary into a nuanced spectrum, estimating a conditional average treatment effect for each user based on their specific features.

Terraform projects often fail due to poor project structure, not Terraform itself. By applying software project principles, you can improve your Terraform project's organization, scalability, and maintainability.

From headless CMS to AI-powered website builders, discover the top open source projects redefining the modern developer ecosystem and experience.

Instead of using a traditional website builder, I decided to build and deploy my portfolio using AWS Amplify with a full CI/CD pipeline, showcasing my cloud skills in action.

When measuring model quality, standard regression approaches can be flawed due to confounding variables. This tutorial shows how to use instrumental variables to extract a clean causal estimate from LLM routing decisions in Python.

Discover how to avoid p-hacking and stop early in product experiments using the mixture Sequential Probability Ratio Test (mSPRT) and sequential testing. This tutorial provides a step-by-step guide on implementing mSPRT in Python and applying it to a synthetic LLM product dataset.