Maya Chen

Your LLM can technically read a novel. Whether it actually processes that novel is a different question entirely.

Most developers treat temperature as a creativity dial. It's actually reshaping token probabilities in ways that compound across every word the model generates.

Microservices promised independence and scale. For many teams, they delivered complexity and fragility instead. Here's why — and how to tell if you're already stuck.

A medical AI startup learned the hard way that high confidence scores don't predict accuracy. They predict familiarity. That distinction costs lives.

Developers optimize the code they understand best, not the code that's actually slow. Profilers exist to fix this. Most teams don't use them.

Writing code is a creative act with a blank canvas. Debugging production is forensic work with half the evidence missing and a clock running.

A deep dive into how the LLVM project exposed a class of bugs that experienced engineers had written confidently for years, and what that teaches us about trusting our own mental models.

Caching is supposed to make your app faster. But a misconfigured cache doesn't just slow things down — it serves confidently wrong answers to the users who matter most.

A crash tells you something is wrong. A silent bug lets you keep shipping broken software for months before anyone notices.

The attention mechanism that makes LLMs powerful also makes them scale quadratically with context length. Here's what that means for your infrastructure bill.

Longer prompts should mean better answers. Often they produce worse ones. Here's the actual mechanism behind context window degradation.

The internet doesn't know your name. It knows your numbers. Here's how five layers of addressing get data from a server in Frankfurt to the right tab in your browser.

Removing a feature is technically simple and organizationally brutal. Basecamp has done it more deliberately than almost anyone. Here's what they learned.

Adding features is celebrated. Removing them is agonizing. Here's why deletion is the most underrated skill in software.

Adversarial inputs look dangerous. The prompts that actually break LLM applications look completely ordinary — and that's the whole problem.

Engineers obsess over load balancers while their actual bottlenecks hide in databases, connection pools, and application code. Here's where to actually look.

A legal tech company spent months optimizing prompts that the model never fully received. What they discovered changed how their entire engineering team thinks about context.

A major streaming platform's 2021 outage traced back to a single bastion host. The lesson isn't about redundancy. It's about what we decide doesn't count as infrastructure.