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Claude now marks AI-generated content. But it does not mark everything the same way. Anthropic currently uses embedded watermarks for text and signed C2PA provenance metadata for supported files. Code sits somewhere in between: it is still text, but its structure gives the watermark fewer places to work. I went into detail about Claude’s watermarks […]
How to Remove Claude Watermarks from Text, Code, and Files Read More »
Developers launch new models every week, but most barely change how you work. Kimi K3 is different—not because of benchmark charts, but because of a few small API changes that fundamentally affect how you use it. The first is reasoning_effort, which defaults to maximum, alongside 131,072 max_completion_tokens. Ask K3 to rename a variable, and it
7 Kimi K3 Features That Make Every Other Model Feel Outdated Read More »
Long-running AI agents often spend most of their time on routine execution rather than difficult reasoning. After making a plan, they may perform hundreds of tool calls, file reads, validations, commands, and formatting steps, so using a frontier reasoning model for every action can become unnecessarily slow and expensive. NVIDIA’s Nemotron 3.5 Lightning takes a
NVIDIA Nemotron 3.5 Lightning: The AI Agent Workhorse Read More »
About a month ago, Baidu (often called the “Google of China”) introduced Unlimited-OCR, an advancement over DeepSeek OCR. The model was designed to transcribe long, multi-page documents with high accuracy while delivering fast and stable inference. Unlike conventional vision-language OCR systems, Unlimited-OCR addresses a major bottleneck in long-document transcription: the rapidly growing Key-Value (KV) cache,
How Baidu Unlimited-OCR Works: Solving Long-Document Transcription Read More »
In the rush to automate evaluation, from grading student code to ranking research papers, we have embraced Large Language Models as judges. They are fast. These units are cheap. They scale. However, at a workshop at DHS 2026, Bhaskarjit Sarmah made a point that stuck with me: “you can’t trust LLM as a judge. I
First, pick the line that applies to you. Since August 2nd, 2026, Claude marks all content during generation. For instance, text receives a hidden watermark, while files receive a signature. Anthropic committed to the EU AI Act’s Code of Practice on Transparency of AI-Generated Content. Consequently, all content generated by Claude models will carry a
You have probably heard by now. Claude Code burns through usage limits! But most of us live in the web app… distant from the terminal app, around which the buzz is about. Maybe that was enough to make you curious. Maybe you already knew exactly what it was and just want it running on your
How to Install Claude Code: A Step-by-Step Guide Read More »
Claude can review data, check code, write reports, and prepare presentations, but teams still end up repeating the same structure, validation rules, company standards, and final-check instructions in every conversation. That repetition wastes time and often leads to inconsistent results. Custom Skills solve this by packaging reusable instructions, workflows, templates, scripts, examples, and reference files
How to Create Custom Skills in Claude: A Step-by-Step Guide Read More »
Anthropic has released Claude Opus 5. The fourth model in two months, if you are keeping count. Most people are not. This one matters more than the count suggests. Opus is the workhorse tier, the model that does the actual paid work, and it just got a step change rather than a bump. Anthropic’s own
Claude Opus 5: Near-Frontier Intelligence, On a Dial Read More »
For months, Claude Code has been the go to terminal coding agent for developers. Then Grok Build arrived in beta on May 14, 2026, giving developers a second serious option and raising a new question: which one actually performs better? I tested both agents on the same real world coding tasks using identical prompts to
Grok Build CLI vs Claude Code: I Tested Both So You Don’t Have To Read More »
