Claude

The job search has long been a one-way mirror - companies deploy AI to filter applications while candidates manually juggle spreadsheets, tailor cover letters, and hope their resume gets past the automated screener. Career-Ops flips that script entirely. Built on Claude Code, it’s an open-source system that gives job seekers their own AI advantage: intelligent evaluation of opportunities, automated customized applications, and systematic candidate strategy. The Problem It Solves The traditional job search is a grind of low-signal noise. You find 30 job postings. You read them. You customize a resume. You write a cover letter. You track applications in a spreadsheet. You wait. You compare offers using gut feel and spotty spreadsheet columns. The process burns time and attention - exactly when you need both to think clearly about your career. ...

Anthropic released Claude Mythos Preview on April 7, 2026 - and immediately announced it won’t be publicly available. The reason? It’s too dangerous. Despite being the most powerful AI model yet, scoring double-digit improvements over competitors across nearly every benchmark, Mythos is restricted to just 12 major tech companies for defensive cybersecurity work through Project Glasswing. But before diving into why, let’s look at what makes Mythos so exceptionally capable. ...

After six months of daily use, here is how the two heavyweights of AI-assisted coding compare: the terminal-native Claude Code and the IDE-integrated Cursor.

I genuinely think a lot of people still underestimate how fast the AI developer tooling ecosystem is evolving. A good example of that is the new Code Review feature in Claude Code, which Anthropic just released in research preview. Docs: https://code.claude.com/docs/en/code-review At first glance it sounds like another “AI reviews your code” feature. We’ve had plenty of those. But when you look closer, this one is actually quite different. Most automated code review tools are basically static analysis with a large language model wrapped around them. They skim the diff, leave a few comments, maybe point out a style issue or a possible bug. ...

I keep running into the same problem with Claude Code Pro ($20/month): I burn through the usage limits faster than I expect. The obvious solution is upgrading to the $200/month plan, but that feels excessive for how I actually use it. So I started exploring alternatives. What I’ve realised is that the best approach isn’t replacing Claude Code entirely - it’s building a hybrid AI developer stack where different models handle different types of work. ...

Most people still talk about chatbots and large language models as if they are the same thing. They are related, but they are not identical. A chatbot is the product experience. A large language model is the reasoning engine underneath. Once you separate those two layers, the AI landscape becomes much easier to understand. Quick Answer If you only want the short version: an LLM is the underlying model a chatbot is the product wrapped around that model the best choice depends on the task, the interface, and the context you need Chatbot vs LLM At A Glance Question LLM Chatbot What is it? The model itself The user-facing product Main job Generate and transform language and other modalities Make the model usable in a workflow Typical interface API, SDK, model endpoint Chat UI, app, assistant product Common extras None by default memory, files, search, tools, voice Best for automation, integration, custom systems everyday use, exploration, fast collaboration The Simple Distinction A large language model (LLM) is a model trained to predict and generate language. In practice, modern LLMs can also handle code, structured data, reasoning tasks, and increasingly multimodal inputs such as images, audio, and video. ...