Twin1 AI launched with $20 million in seed funding to build AI-powered digital twins that retain an individual knowledge worker’s expertise and can answer questions or act on that person’s behalf within permissioned workplace systems. The company says its named customers report Twin1 handling 30% to 50% of the communications work those workers would otherwise do themselves. Twin1 will use the funding to hire in San Mateo and London, expand sales and marketing, and roll out a self-service version after its enterprise product.
Matt Pocock released the /wayfinder skill to help an AI agent plan projects whose end state is unclear by handling multi-session planning instead of requiring upfront session management. The article says Pocock’s earlier “AI Skills for Real Engineers” project has over 220,000 stars on GitHub. The skill introduces a structured “map” plus ticket-and-session terminology to reduce confused behavior and make specs more detailed for AFK-style agent work.
The Neuron Team is hosting a live YouTube livestream to break down recent AI model and tool launches for non-developers in plain English. The stream starts at 10 AM PT / 1 PM ET and covers items including Qwen 3.8, Unsloth Studio, local AI hosting, Cursor Origin, and the DeepSeek Harness. The result is a guided, practical explanation of which tools to care about, what they do, and when to use them based on audience questions.
Amazon expanded Policy in Amazon Bedrock AgentCore by adding a new natural-language-to-Dogwood “Policy Authoring” capability that enforces agent action constraints applied in real time by the Dogwood monitor in the AgentCore Gateway. The launch adds temporal and trajectory controls, including restrictions like rate limiting, prerequisites, and sequential ordering of tool calls, with an example rule for limiting refunds to amounts of $2,500 or less during 9:00 AM–5:00 PM UTC. Teams can now import policy documents written in natural language and have them automatically converted into syntactically and semantically correct Dogwood specifications that constrain deployed AI agents.
Ben’s Bites reports poll results and argues that personal AI agents mostly consist of a folder of files plus tools wired into an agent platform. The post references 996 total votes in its poll about whether readers use a personal agent. It shifts the focus from complex agent systems to setting up a simple “personal agent” by organizing context files and pointing to whichever tool the user prefers, with Slack and other apps positioned as more collaborative interfaces for agents.
Mistral released Agentic Search, a retrieval layer that lets AI systems search, navigate, read, and verify information inside complex enterprise documents using a multi-step loop. It reported 3x correctness on FinanceBench financial filings, raising accuracy from 26.7% to 86%. The approach cuts turns, token use, and latency compared with one-shot RAG by replacing repeated broad searches with targeted navigation-based inspection of evidence.
Guideless, a Lithuanian AI platform for software training and workflow documentation, raised €1 million in pre-seed funding to expand its technology and international reach. The round closed at €1M and includes backers Superhero Capital plus FIRSTPICK VC and angel investors from Vinted. The startup will accelerate product development, hire, and push expansion into the UK, wider Europe, and the US.
Vercel’s programming language for AI agents is being discussed in a link-style post. The text provides 0 concrete figures, dates, or benchmarks. As a result, there’s not enough information here to determine what the language changes or enables in practice.
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