New agent mode and IDE enhancements in Code Assist!... → Agent mode: Analyzes full codebase to handle multi-file tasks from one prompt IDE Enhancements: Control context via .aiexclude, attach terminal output & enjoy a smoother UIshow more

Hermes Agent has a new Blank Slate setup mode.... The default Quick/Full setup modes work great for most, but if you would rather build your agent from the ground up you can now start with just a provider, model, file operations, and terminal, then manually add in anything else.show more

Qwen Code v0.14.0 dropped - Control it remotely from... Telegram, WeChat, or DingTalk - Cron jobs built in - Sub-agent model selection - New Qwen3.6-Plus flagship with 1M token context - /plan mode maps out all files and steps before executionshow more

Finally, we're so excited to bring Project Mariner capabilities... to AI Mode in Search, Agent Mode in Google Gemini, and as a standalone web app. This will allow the products you know and love to intelligently manage complex multi-step tasks on your behalf.show more

I gave EvoX Agent one prompt and asked it... to build me a game. This is what came out 👇🏼 A playable browser game called Neon Dodge: built from scratch in Code Mode with movement, obstacles, scoring, increasing difficulty, and a full restart loop. Here’s how it happened.show more

3.5 Soon: Up to 8+ Layers, 16 LLMs in... Parallel🪄 A fully parallel, multi-layered system with 8+ orchestration layers handling everything from prompt parsing and tool execution to code generation and live editing—all powered by 16+ LLMs running in sync for real-time, adaptive creation. ➡️v1: Single agent, single output ↕️v2: Multiple agents, single output 🔃v3: Single agent, multiple outputs 🔀v3.5: Multiple agents, multiple outputs — scalable, context-aware, and built for real-time builds🔨show more

A Closer Look at Alchemist AI v3.5🔎 In v1,... one agent handled everything. You’d enter a prompt like “make a snake game” and get a single block of code—one input, one output. v2 introduced multiple agents with specialized roles: prompt refinement, frontend, backend, and review. It brought more structure, but the process was still linear. Each step produced a single output. With v3, a single agent could handle multiple tasks. It generated HTML, CSS, JavaScript, searched for assets, and more—all in one go, while maintaining full context. Now in v3.5, we combine both models. Multiple agents work in parallel, each capable of producing multiple outputs at once. The prompt compiler adapts based on what you're building. A 3D game? It prioritizes game engines, rendering, and mechanics. A website or 2D app? It shifts focus to relevant frameworks and tools. The tool handler can call several services simultaneously, feeding context-aware data into the code generator for real-time execution. From single-output generation to parallel, adaptive workflows. In the next breakdown, we’ll dive into the architecture behind our proprietary engine in v3.5.show more

We've updated /fork in Claude Code /fork now runs... a background agent with your exact context (system prompt, tools, history, model) and prompt cache. The result gets returned to your session. /branch (the old /fork) still copies the transcript to a new session you drive.show more

This opens up a completely new workflow for artists... when it comes to shooting music videos. Take one performance and place it into multiple locations from multiple angles. By combining Kling 2.6 Motion Control with our Multi-Angle Fashion Shoot agent, we generate multiple angles from a single reference image and use them to drive the performance. Full workflow + agent below 👇show more

Redefine your workflow with Teamily AI, the team brain... built for 10X productivity. Instant Multi-Agent Teams Describe your goal and Teamily AI assembles a pro agent team to execute in parallel, fast from idea to done. Why Teamily: - Persistent Memory, keeps context - Autonomous Agents, coordinate via @-mentions - Pro Workspace, Studio, Automations, Meeting Minutes - Agent Market, deploy from the "Discover" tab 🌐 🍎 🤖show more

THIS DEVELOPER USED OPENCLAW AGENTS TO RUN HIS B2B... BUSINESS VIA TELEGRAM AND MADE $15,000/MONTH he doesn't write prompts from scratch or use generic browser interfaces. he runs a multi-agent framework through a mobile chat. the agents write code, test deployments, and update sites in real-time while he just hits approve the setup is straightforward: - spin up Coolify on a free cloud instance to host your own self-hosted agent panels - link the agent loop to a Telegram gateway to approve code edits from your phone - deploy specialized skill files directly to limit token waste and context decay - containerize the terminal execution using Docker to prevent security breaches if you are still running local agents without container safety, you are leaving money on the table. read the 30-day battle between OpenClaw and Hermes Agent to see who actually wins in production Full breakdown and migration playbook ↓show more

you don't need to re-explain your codebase's architecture to... your agent every session. most tools stop at telling you what broke. sentrux is a real-time architectural sensor, it watches your codebase as a live treemap and turns file structure and dependencies into one continuous quality score. the loop is simple: codebase > agent scans structure and dependencies > sentrux scores 5 root cause metrics into one signal > agent sees exactly where risk concentrates > next session starts from a live map instead of a blind grep the binary carries zero built-in language knowledge, all 52 languages live in plugin.toml and tags.scm query files, so a new language needs zero rust code. small catch: it only scores the structure, it won't tell you why the cycle happened, that part's still on you. built pure Rust with no runtime dependencies, specifically so it could sit as one binary between an agent and a codebase without adding friction.show more

BREAKING 🚨: ANTHROPIC IS WORKING ON ITS OWN ALWAYS-ON... AGENT SOLUTION CALLED CONWAY! CONWAY WILL HAVE A SEPARATE UI INSTANCE, WILL BE ABLE TO OPERATE BROWSER, CONNECTORS, CLAUDE CODE (EPITAXY?) AND COULD BE INVOKED VIA WEBHOOKS. IT WILL ALSO SUPPORT EXTENSIONS, AN UPCOMING CNW ZIP STANDARD FROM ANTHROPIC TO BUILD CUSTOM TOOLS, UI TABS, AND CONTEXT HANDLERS! LET CLAUDE COOK 🔥show more

New Feature Live!🚨 Introducing Prompt Assist—a feature designed to... streamline your prompt-writing experience with Alchemist AI. Prompt Assist integrates a speed-oriented AI model that analyzes your input as you write, offering contextually relevant suggestions in real-time. Here’s how it works: • Real-Time Suggestions: Prompt Assist dynamically processes your input, predicting next steps from your initial wording. Press Tab to accept suggestions and seamlessly complete your prompt. • Smart Context Analysis: The feature leverages natural language processing models to understand the structure and intent of your prompt, this ensures the suggestions remain precise and useful.show more

LangGraph. CrewAI. Agno. Which one to pick? The good... news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.show more

You can now delegate tasks to GitHub Copilot coding... agent from any page on GitHub 🤖 Open the new Agents panel in one click, write a simple prompt, then hit Enter. GitHub Copilot works in the background, and opens a PR for your review. No interruptions to your workflow required. ✅show more

MOONSHOT JUST CLONED CLAUDE CODE AND MADE IT FREE.... It's called Kimi Code CLI. Open source, MIT license, maintained by the lab that shipped K3 yesterday. And it does things Claude Code doesn't: → drop a screen recording into the chat as input → built-in coder, explore, and plan subagents, each in its own context → plan mode before it touches a single file → MCP servers configured by the agent itself via /mcp-config → plugs into Zed, JetBrains, and VS Code → one binary, no Node setup, starts in milliseconds The CLI costs $0. K3 behind it starts at $3 per million tokens. Grab it for free👇show more

wow.. this new AI agent for UI design is... crazy I just use HeroUI to create a fully functional project management app in mins using only text prompts test link below, reply "prompts" I’ll send you the full prompt + tricks tutorial & examples:show more