Daniel Walsh

AI systems can fail while every normal engineering signal looks fine. The app is online. Error logs are clean. Tests pass. No exception gets thrown. Yet the answer is wrong, the agent used the wrong tool, response quality has dropped, or the monthly model bill has suddenly tripled. That is the awkward reality of software … Read more

If I’m building an AI system, using Claude Code, Codex, or working with an agent such as Hermes, I don’t want to rely on prompting alone. Prompts matter, but the workflow shape matters just as much. That’s where agentic design patterns come in. I think of each pattern as a small workflow graph. It defines … Read more

AI coding agents are becoming a normal part of software work. I use them to explain unfamiliar code, draft changes, find bugs, and move much faster through repetitive tasks. Yet every time I point an agent at a folder, I need to ask a more basic question first: what data is leaving my machine, where … Read more

People often treat an AI model as if it is the entire product. They compare Claude, Codex, Gemini, and local models, then assume the biggest model produces the best result. That misses a major part of what makes an AI coding agent useful. I can take the exact same model, give it the same task, … Read more

Unsloth has released a new 4-bit version of Qwen3.6 that it describes as up to 2.5 times faster. The release uses NVIDIA’s NVFP4 format, and it can run locally on a single Blackwell GPU. That immediately caught my attention, because the headline number sounds excellent, but data center benchmark figures don’t always map cleanly to … Read more

A few weeks ago, Anthropic published a 36 page playbook on securing AI agents like Claude Code. The timing matters. On one side, I can now give agents far more access than even a year ago. They can read files, call tools, connect to APIs, send messages, write code, and make decisions without stopping every … Read more

DeepSeek keep doing something I wish more AI labs would do. They push model performance forward, then they open source the useful part. This time, the release wasn’t a new language model. It was something more practical for anyone running local AI or serving models in production. It was DSpark, and the key thing to … Read more

Google recently shipped a new open spec called the Open Knowledge Format, or OKF. Their core argument is simple and, frankly, hard to disagree with. Large language models are no longer held back mainly by raw intelligence. They’re held back by context. If a model doesn’t understand your app, your business, your systems, or your … Read more

Baidu recently released an open weights vision language model called Unlimited-OCR, and the name tells you the pitch straight away. The idea is simple. Feed it a long document and let it transcribe the whole thing in one pass, page after page, without the usual slowdown that hits most models as output grows. That grabbed … Read more

Sakana AI and OpenRouter both made a big claim recently. Their message was simple: a single giant model may not be the best way to get frontier level results anymore. That’s a bold claim on its own. The twist is what sits underneath it. Sakana’s Fugu is presented like a model, but the interesting part … Read more