Introducing Branch Split any conversation into a parallel session... that inherits your full context, while the original stays intact. A single research session can become a report, a slide deck, and an investor brief. Now you just branch. Same context, new direction.show more

Introducing side chats, a new way to ask questions... and explore ideas without interrupting your main conversation. Each side chat is a durable agent conversation you can @-mention to bring context back into the main thread.show more

📡Web Scraping is Live in the app and API... You can now turn any URL into AI context on Venice Just include a URL in your prompt, and Venice will automatically scrape the page to include as context for your requestshow more

Introducing cmux Vault: cmux now has a right sidebar... with a vault pane where you can see every single Codex, Claude Code, OpenCode, and Pi session You can search through all sessions with full-text search, and drag them directly into your workspace Out in v0.64+show more

We took a 30B model and split it in... two to write tokens in parallel instead of one at a time. Introducing Nemotron-Labs-TwoTower: a diffusion language model from NVIDIA Research adapted from Nemotron-3-Nano-30B-A3B. Here’s how it works: one half holds the context, the other writes the tokens, with both reusing the pretrained model instead of training a new one from scratch. We found it kept 98.7% of the original model’s quality at 2.42× faster generation.show more

/autofix-pr now lets you kick off autofix straight from... the command line. After finishing up a PR, just run /autofix-pr. It sends your session to the cloud so the PR autofixer has full context to address CI failures and comments. Hugely win for my productivity.show more

Following up on dragging splits into other split locations... and across windows, you can now also drag a split outside any valid windows to pull it out into a new window. It even works with undo/redo.show more

OK, so now we know. You can comfortably pack... a swarm of 720 drones and their launch system into a single 20ft shipping container. For context Germany + France + UK have about 800 tanks between them. The world has changed.show more

Smol tip: /𝚏𝚘𝚛𝚔 is perfect for mid-task side quests.... It spawns a subagent that inherits the whole conversation, runs in the background while you keep working on your main quest, and comes back with an update.show more

💡 Using Next.js's Intercepting Routes can be useful if... you want to show a route while keeping the context for the current page! E.g. we can render an overlaying modal on soft navigation and a standalone page on hard navigation, which requires a full page reload:show more

NEW in Dia: Inline Browsing Starting today, when you... click links in a chat with Dia, the webpages will automatically render inline. No more context switching. No more tab mess. Now you can browse the web without breaking the flow of your conversation:show more

Introducing agent-tail: a dev tool that makes your logs... easily accessible to agents. npm i agent-tail Wrap dev server commands, add the Vite/Next plugin, install the skill, and your agent has full context of your browser, server, and any other logs. Link to full docs below ↓show more

There's a ton of stuff to do while starting... a business, so we took inspiration from RTS games like Civ and built in a roadmap of an entire company. Kick off the next step while maintaining your full business context.show more

Marjorie Taylor Greene and other conservatives are sharing a... cut from a video that appears to show Joe Biden admitting to selling state secrets. Some conservatives are claiming that this shows Biden is corrupt while others are claiming that it is evidence of dementia. Context matters. They are deceiving you by only showing a small portion of the video which doesn’t show Biden saying “all kidding aside.” Context matters. This is irresponsible if you are taking sections of a video to sell an narrative you want people to believe. You can see the full context below.show more

🚨 JUST IN: CHINA just released an AI EMPLOYEE... that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.show more

Claude just solved one of AI coding’s biggest problems.... 🤯 It can now turn your entire codebase into: → an interactive architecture map for humans → a memory system for AI agents So the next coding agent instantly understands your APIs, components, auth, DB flows, and dependencies. No more dropping AI into a random repo with zero context. Your codebase can literally explain itself now.show more

You asked, we shipped 🚢 You can now copy... all of the table definitions with a single click within the Supabase dashboard so that you can quickly provide the context of the database! Head to the Database menu and click the "Copy as SQL" button 📋show more

Andrew shipped MCP support in Warp. “MCP support in... Warp is highly dynamic. If you start a conversation without an MCP server, and then start the server, your next message is going to have that as context”show more

Demi Lovato references ‘Camp Rock’ in new TikTok: “why... would i lie and make up a fake life story that my mom is the president of the chinese branch of a music media company just to become friends with the popular kids at camp?”show more

ByteDance just open sourced an AI SuperAgent that can... research, code, build websites, create slide decks, and generate videos. All by itself. DeerFlow 2.0 (27K+ GitHub stars ⭐️), an AI system acting like an autonomous employee with its own computer workspace to research and code. Standard chatbots only generate text and forget your preferences. DeerFlow solves this by giving the AI an isolated virtual computer environment where it safely runs programs. When given a massive task, the main program creates several smaller AI assistants to work simultaneously. It also saves your past workflows so it gets smarter about your needs. DeerFlow is model-agnostic — it works with any LLM that implements the OpenAI-compatible API. Fully supports running local models on your own computer using tools like Ollama. An example - you ask for research on the top 10 AI startups in 2026 for a presentation, the lead agent in DeerFlow breaks that big job into smaller sub-tasks. It assigns one sub-agent to look into each company, another to find funding details, and a third to handle competitor analysis. These agents do all their work in parallel. Everything eventually converges, and a final agent pulls the results into a slide deck complete with custom visuals.show more

Claude Cowork Sub-Agents are f*cking cracked 🤯 One prompt... → 50 competitor ads analyzed, hooks extracted, and a full creative brief generated. 10 AI agents running in parallel, under 5 minutes. All inside Claude Cowork. Perfect for DTC brands and agencies who are still doing creative research and ad production one task at a time inside Claude. If you're analyzing competitor ads one by one, copying hooks into a spreadsheet manually, writing brief after brief from scratch, and watching Claude's output quality fall off a cliff after the 15th variation because the context window is completely bloated... Sub-agents eliminate the entire bottleneck: → Drop in a spreadsheet of 50 competitor ads and spin up 10 parallel sub-agents → Each sub-agent analyzes 5 ads simultaneously — hooks, angles, CTAs, emotional tone, creative format → They report structured summaries back to the main agent without bloating the context → The main agent synthesizes patterns across all 50 ads into a competitive intel brief → Then spin up another round of sub-agents to generate 30 ad copy variations across 10 personas → Each sub-agent writes for 1-2 personas in a fresh context — so variation 30 is as sharp as variation 1 No analyzing ads one at a time. No context window blowing up halfway through. No copy quality degrading after the first dozen variations. What this gives you: → 50 competitor ads broken down in minutes — hooks, angles, CTAs, formats, all structured → Pattern analysis across the full dataset that you'd miss reviewing ads individually → 30+ ad copy variations with persona-specific messaging that actually stays sharp → A workflow you can save as reusable skills and trigger with one command next time → The same output quality on the last task as the first Built 100% inside Claude Cowork with sub-agents. I put together a full DTC playbook: 5 bulk workflows with copy-paste prompts, the exact sub-agent prompting pattern, batching guidelines, and an honest breakdown of when this setup is worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)show more