92 stories
An open-source, local, read-only MCP server that checks your request before Google quietly hands back nothing Ask the Google Search Console API for clicks filtered by country us and you get zero rows. No error, no warning, just nothing. It's not the only one.
TL;DR Muse Wonder and Muse Wonder Full are a frontier model family from Meta built for agentic work, released on 12 October 2026 with a 1M-token context window and a thirteen-page model card published the same day.
A common way to give a support bot knowledge is to let your agents save their good answers. A ticket gets solved, the agent clicks save, and the answer joins a set the bot retrieves from when a similar question comes in. Many support tools offer some version of it. We built ours.
This edition of the LLM Inference Digest covers new developments from 2026-10-07 to 2026-10-14 across arXiv, the vLLM and Hugging Face blogs, Together AI, Modal, and Latent Space.
"Can you train ChatGPT on our documents?" is one of the most common requests we get. It's a fair question, but it usually mixes up two different techniques. In most cases what the business needs isn't training at all. It's retrieval-augmented generation, or RAG.
A team red-teaming their own log-reading AI assistant found something that should worry anyone who's bolted an LLM onto an internal tool: planted instructions inside log lines could get the model to embed a database password in a Markdown link.
A support ticket comes in: "I was charged twice this month, please refund one of them." Most teams send that to a chat model with a prompt like "Classify this ticket.
The future of local AI is agentic and requires multiple agents to share one machine: one agent summarising your emails overnight, one watching your health data and one doing the shopping, while you are still able to chat and ask questions in between.
Model price changes detected for Alibaba, Baidu, Chutes, Decart, Inceptron, Reka and StreamLake. Details below.
The Local LLM Lab — Part 10 One controlled experiment. One number. One verdict. Every homelab has a moment like this: the GPU is at 100%, the fan is screaming, and you have no idea which of the twenty services on the box is doing it.
The Whisper in the Machine: My First Encounter with AI's 'Authenticity Crisis' I did an experiment last week. I fed one of OpenAI's models a dozen of my published articles—the ones I felt truly captured my voice, my rhythm, my weird little syntactical habits.
I built a stack of six image APIs in two weekends. Six clients, six rate limits, six ways a generation can silently fail. Last Tuesday I ran the same prompt through all of them and stacked the results in a grid. Five out of six were beautiful. One was correct. The brief was simple.
You face high cloud bills when you run powerful AI agents every day. Qwen3.5 gives you frontier-level multimodal reasoning locally. You combine it with OpenClaw for persistent agent workflows and Ollama for simple local serving.
One-line summary: By the end of this tutorial, you'll have Kong AI Gateway 2.0 automatically stripping PII from every LLM request using the ai-sanitizer policy. Names, emails and phone numbers get swapped for synthetic values, and your application code doesn't change.
Originally published on Codeloop Software. Quick answer: MCP (Model Context Protocol) is an open standard created by Anthropic that defines how AI applications connect to external tools and data sources — like USB for AI, you build one MCP server and any MCP-compatible client can use it.
Originally published on Codeloop Software. Quick answer: In 2026, a custom single-purpose AI agent (lead qualification, support deflection) costs $1,500–$5,000 to build plus $300–$800/month to run.
If you spend any time around coding agents in 2026, you've absorbed the advice: use multiple agents. One plans, one implements, one reviews. The implication runs one direction. Two agents beat one, and if two are good, three should be better.
The Whisper in the Machine: My Encounter with an AI's Hidden Mark. I'll open with a personal anecdote – perhaps a moment of mild paranoia while reviewing an AI-generated text, only to discover later the subtle hints of an underlying 'fingerprint.' This hook introduces the central tension: the…
Showing 18 of 92 stories
Load more storiesGet the top AI news and tools straight to your inbox every week.
Weekly · AI news from Dev.to AI
Join 15,000+ AI enthusiasts
