Caffeine's biggest update just dropped. Here's what's new: Agentic... build system - a Composer orchestrates specialist agents New landing page experience - completely redesigned from the ground up Updated dashboard - all your projects in one place Discovery phase - the agent reads your codebase before building Context as RAM - projects grow without hitting limits Version history - track and restore previous builds -- V3 is here.show more

If your AI replies instantly… it’s probably not building.... Replit’s Agent just became your personal engineer. And it’s changing how we think about building apps I saw it complete a full feature build from one prompt. Try it here: • Understood the context of what I wanted • Wrote the code without micromanagement • Tested and refined on its own • Shipped a working dashboard overnight All while I stepped away. This isn’t just “AI assistance.” It’s delegation to an Agent that actually thinks. Here’s what actually happened: 1. Typed one clear prompt 2. Agent ran longer without babysitting 3. Built features autonomously 4. Debugged in the background 5. Delivered a working result by morning It wasn’t just fast output. It built something real and functional. This is the future we’ve been waiting for: ☑︎ AI that doesn’t stop at a single reply ☑︎ Agents that understand context, not just commands ☑︎ Work that gets done while you focus on vision We’re moving from “AI that chats” to “AI that builds.” Replit Agent just showed us what’s possible. Try it now: Learning something new? Repost ♻️ so others can too.show more

Stop spending hours on manual work. You can now... use a multi-agent AI workforce to get more work done in less time. Here's how 👇 --- Try Eigent AI - Lets you build and run a custom AI workforce on your desktop. - Automate complex workflows using multi-agent task execution. - Built on CAMEL-AI’s top open-source projects ( CAMEL-AI.org & OWL). - Boost productivity with deep customization and strong privacy --- Features: - Customize Your AI Workforce: Build task-specific agents with domain skills and tools. - Faster Execution: Eigent runs agents in parallel to automate complex workflows. - Human-in-the-loop: Automatically asks for help when tasks hit uncertainty. --- What sets Eigent apart? - 3–5× faster task execution using a parallel multi-agent workforce. - Modular design lets you add new capabilities without changing the core system. - Self-optimizing agents that replan and adapt during execution for higher success. - Deploy anywhere: cloud, local, or enterprise, with full open-source flexibility. --- Try building your multi-agent AI workforce here: Join their community to build your multi-agent workforce: Check their GitHub: ---show more

🔶 Get ready – AGNT Hub is on the... horizon! Imagine a unified space where AI agents come together to collaborate, connect, and create. But wait… you won’t need to imagine anymore. AGNT Hub is here to redefine how you work with AI. ❕Here’s what’s in store: – One hub, all agents: Manage multiple AI agents effortlessly in one place. – A single token: Unlock advanced capabilities like shared task context, cross-agent collaboration, and more to streamline your experience. – Decentralized space: Engage with your AI agents like never before – all in a protected environment. ⚪And… that’s not all! AGNT Hub is more than an app; it’s an AI & blockchain community. Whether you’re a creator, a dreamer, or just AI-curious, this is where your journey levels up. Follow us for updates – AI Agents collaboration is almost hereshow more

I just built a Claude Code skill that scores... whether your landing page actually keeps your Meta ad's promise 🤯 Drop in your ad and the page it points to. It reads both, scores the "ad scent" from click to page, and finds the exact line where the page breaks the promise that won the click. All inside Claude Code. Perfect for DTC brands and media buyers who pour everything into the ad and the CPA but never grade the seam in between. If you're scaling spend on a winning ad, the click is landing on a page that opens with something slightly different, the ad promised 50% off and the page shows full price, the ad hooked "for oily skin" and the page is a generic homepage, and nothing looks broken, but the visitor feels it and bounces... That gap has a name in conversion work: message match. And you already paid for the click you're losing. Here's what it does: → Drop in your ad (headline, copy, offer, CTA) and the landing-page URL → It fetches the live page and reads what's actually above the fold → Grades 7 continuity dimensions: promise, offer, angle, CTA, audience, proof, visual → Shows your ad's words next to your page's words, so every gap is right there → Rewrites your hero headline so the page keeps the ad's promise → Renders a dashboard with a Match Score out of 100 No guessing why the click bounced. No blaming the creative for a page problem. No buying more traffic to fix a copy problem. What you get: → A Match Score on every ad-to-page pair before you scale → The ad-side vs page-side quotes, side by side, for every leak → A hero rewrite you can paste straight onto the page → A dashboard you can hand to your team or client I'm giving away the full skill completely for free. Built 100% in Claude Code. No API keys. Want the skill? > Like this post > Comment "MATCH" And I'll send it over (must be following so I can DM)show more

Just dropped: Horizon. Not just a theme. A new... foundation for building online stores on Shopify. One system. Ten new themes. All live today. Horizon incorporates theme blocks - 30+ drag-and-drop components you can remix across your store. Video. Product recs. Rich text. Custom content. Want holographic effects on images as you hover over them? Just say so and AI will code something just for you. We’ve also made some of your most requested updates to the theme editor: • Copy + paste blocks anywhere • Drag + drop across pages • Preview blocks before publishing This is total design freedom. The fastest way to go from idea to store. Horizon is the new starting line for great brands. Let’s build.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

From our humble beginnings in 2011 to today's reimagined... experience - watch as Goodnotes evolves through the years. What started as a simple digital paper app has transformed into a powerful platform for capturing ideas in any form. The new Goodnotes is here - with Whiteboards, Text Documents, and AI superpowers all in one unified place. No longer just Goodnotes 6, but simply Goodnotes - where your ideas come to life. Our journey continues with a fresh look and a bold new vision. Download now and experience the next chapter of note-taking.show more

Octav Phase 2 is live. More modular. More professional.... Built for the people who actually run capital. DeFi fund managers have been forced to patch together spreadsheets, dashboards, Dune queries, and half-broken bots just to answer basic questions like: What’s my NAV today? What’s my real exposure? Why does nothing reconcile? So we rebuilt Octav from the ground up not as a dashboard… but as a modular financial data platform for digital assets. Introducing Octav Phase 2: A redesigned, professional-grade Octav Pro Built with fund managers, for fund managers. Cleaner UI. Faster workflows. Better reconciliation. Your entire portfolio, finally under control. A more modular architecture Add the pieces you need: NAV engine → PnL → risk → exposure → entity grouping → custom labels. Pick the modules. Build your stack. Scale as you grow. The new Octav API For teams that want to industrialize their reporting. Plug Octav’s data layer into your internal systems, bots, accounting stack, or investor dashboards. It’s fast, accurate, and ready for production. This is what Phase 2 is about: Empowering fund managers to run a professional operation in a market that’s been held together by duct tape. Funds, DAOs, quant desks, allocators your new infrastructure is here. Welcome to Octav Phase 2. Modular. Professional. API-first. Exactly what Digital asset managers needed.show more

Introducing - Spectre AI: The Monarch - Artificial Intelligence... Searching Reimagined Introducing a sneak-peak of the next core feature in the Spectre AI Search Engine: The Monarch aka the AI ChatZone. The Monarch will serve as your AI agent, providing not only price information, technical and sentiment analysis, and project discovery, but also offering visual assistance through Spectre AI's integrated utilities within the search platform. Real-time blockchain data integration comes with the support of Google for Startups. The AI ChatZone's landing page will feature projects that users have added to their UI Watchlist, allowing for quick and seamless discussions about their favorite projects. Additionally, the platform will include hyperlinked external sources, enabling users to access a wealth of information and resources directly from within the ChatZone. In this showcase, we demonstrated how the system responds to inquiries about $Palm AI's (PaLM AI - $PALM) price performance. The user interface and user experience (UI/UX) are fully developed, and the frontend is complete. Our backend is now entering the beta testing phase. The MVP is next in line to be showcased. Get ready for a new journey in AI with Spectre AI. #ai #artificialintelligence #google #nvda #nvidia #tech #spectre $SPECTshow more

Karpathy's Agentic Engineering finally has proper tooling! (built by... Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.show more

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic... shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.show more

A New Era with V3🪄 V3's new engine introduces... significant advancements in output generation. Unlike V2, where the multi-model system processed prompts to produce a single output, V3 is designed to generate multiple outputs and logically link them together. This enhancement effectively removes limitations on output size, enabling more complex and expansive results. Key Features Seamless Multi-Output Generation: V3 has been trained to generate separate outputs and connect them logically. This advancement ensures that there are no longer any limitations on output size. Intelligent Image Creation: V3 improves image generation with better tools, allowing the AI to create as many images as needed and place them within the project’s context. It supports various formats like PNG, JPEG, SVG, and GLB. Web-Integrated Intelligence: V3 can now search the web for documentation and data, providing real-time context and up-to-date references. For example, if you run a restaurant and want to update your website, simply ask Alchemist AI to “generate this website in a more modern style,” and it will update all content accordingly. Improved Creativity and Output Quality: V3's creative capacity has significantly increased. Simple prompts now generate more complete and refined results, with the system efficiently combining multiple elements into cohesive outputs.show more

Karpathy method + Claude Code reading your whole Obsidian... vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.show more

Claude Code + Google Stitch 2.0 is f*cking cracked... 🤯 Google just dropped a free AI design agent that solves Claude Code's biggest weakness: frontend design. One screenshot of a high-converting landing page → a production-ready site for your brand in minutes. All inside Google Stitch + Claude Code. Perfect for DTC brands and agencies who are building advertorial pages and product launch pages for Meta but burning days on designer back-and-forth. If you're running Meta ads and need 5-10 different landing pages testing different hooks, angles, and offers — each one targeting a different audience and pain point — you know the bottleneck isn't the ads. It's the pages. Briefing designers, waiting for revisions, paying $2-5K per page. Stitch eliminates the design bottleneck: → Find a high-converting advertorial that's scaling on Meta → Screenshot it and drop it into Stitch (powered by Gemini 3.1) → Stitch redesigns it with your brand's colors, fonts, and imagery using Nano Banana 2 → Edit sections visually — headlines, CTAs, layouts — without touching code → Export the code and paste it into Claude Code → Claude builds the full production site and deploys to Vercel or Netlify in 60 seconds No designer. No $3K per landing page. No Claude Code frontend that looks like a template from 2019. What you get: → Designer-quality landing pages and advertorials built in minutes, not weeks → Visual editing so you actually see the design before you code it → Nano Banana 2 generating on-brand product imagery and hero shots → A repeatable system — new angle, new page, same pipeline Built 100% with Google Stitch 2.0 + Claude Code. I put together a full playbook showing the exact workflow: how to find winning pages, redesign them in Stitch, and deploy with Claude Code. Want it for free? > Like this post > Comment "STITCH" And I'll send it over (must be following so I can DM)show more

EVERYONE'S TRYING TO SOLVE AI TEAM MEMORY WITH SERVERS,... VECTOR DATABASES, AND ORCHESTRATION PLATFORMS. THIS OPEN SOURCE TOOL DOES IT WITH ONE FOLDER IN YOUR REPO. Every dev on your team runs Claude Code. When one agent screws something up, the rest have no idea. They just repeat the mistake next week. It's called teamlore. When your agent gets corrected or breaks something, it writes a small lore file into a .lore/ folder. That file ships with your PR, gets reviewed like normal code, and after merge every teammate's agent automatically recalls it when they touch that part of the repo. No server. No datab No accounts. No SaaS bill. Just a folder in git. Which means code review catches bad lessons before they poison the team, git blame tells you when a rule was added and why, and the whole thing works offline. One command to install: npx teamlore init Companion command: npx teamlore scarmap. Turns your team's history of mistakes into a visual heat map of the codebase. Every red zone is a place your team has been burned before. Which means every red zone is a place your agents should slow down. Here's the wildest part. The teamlore repo's own .lore/ folder contains every mistake Claude made while building teamlore itself. Dogfooded end-to-end. You can literally open the folder and read the receipts. The author's public invitation: "Would love for someone to try and break it." Available on npm. Repo just launched. 100% open source. (link in the comments)show more

Someone called products built on Polsia "AI slop" yesterday.... So I watched the documentary. A woman is running 29 different businesses by herself. No team. No co-founder. Just AI agents doing the work while she sleeps. She wakes up to messages like "found 3 bugs, fixed them, redesigned your homepage, here are the test results." A franchise owner waited 3 months trying to get his people together to build one website. Gave up. Built it himself on Polsia in under 10 minutes. Payment system already working. The criticism isn't really about the design quality. It's panic dressed up as taste. When the barrier to starting a business drops from months to minutes, the people who made money selling access to those months get nervous. Here's what's actually happening:show more

this might actually be the new ugc method i've... seen 100s of ai ugc ads lately where it's the same creator in every single one. same voice, same face, same brand colors, never drifts once what they're actually doing is running notch agents with memory they load the brand context one time. cloned voice, reference photo, brand color codes, do-not-say words, taste or they just teach it inline as they chat, and every correction becomes a saved rule then before it generates a single frame, the agent reads every relevant memory first. hard rules, reference assets, language constraints, taste preferences, all of it and it's workspace-wide, so every new ad already knows the brand before you type a word each chat isn't a re-introduction anymore. it's training your brand isn't a prompt. it's permanent context run 30-50 of those a month at a real offer and the volume does the rest punchier cut: the new method nobody's clocked yet run notch agents with memory on load the brand once. cloned voice, reference photo, color codes, do-not-say words, taste. or teach it inline and every correction saves as a rule it reads every relevant memory before it generates a single frame, workspace-wide each chat isn't a re-introduction. it's training. your brand isn't a prompt, it's permanent context run it at a real rate and the volume prints.show more

Impeccable 3.7 brings linting to design. Until now it... was a skill you asked for help. Now it's a design-system-aware feedback loop that runs while your agent builds, catching slop and design drift before they land. 🪝 Design hooks for Claude, Codex, and Cursor They run after every UI edit and quietly nudge your agent to fix slop and drift. The output isn't another wall of lint: it separates new findings from already-seen ones, flags clean scans, and asks the agent to use judgment. Fix real issues, leave intentional demos alone, save exceptions to config instead of littering your source. 🎨 Slop detection is now project-aware Reads your actual design system from DESIGN.md, your typography, palette, radius scale, and tokens, and flags drift from your system, not just generic AI slop: • this font isn't in your design system • this color is outside your documented palette • this radius doesn't match your rounded scale The same engine powers both the hooks and the CLI, and it's where we're investing next. 🖥️ Live Mode, ready for real projects Svelte/SvelteKit now preview variants as temporary framework components with live params, then accept cleanly back into your source component. Manual text edits got evidence / apply / discard routes, insertions preserve their anchors, and mapped lists and JSX slots clean up far more reliably. ⚡ Leaner core, sharper detector Rule-level evals across 3 providers and 4 niches cut guidance with no measurable lift and dropped examples that taught models bad patterns. The detector now skips hidden and screen-reader-only elements, understands OKLCH alpha and Sass-like inputs, and tightened checks for repeated kickers, oversized H1s, clipped overflow, and cramped padding. 🛠️ CLI caught up impeccable detect loads DESIGN.md by default, motion findings name the exact token or cubic-bezier instead of just "bounce," and impeccable ignores gives real CRUD for exceptions. Hooks and CLI share the same ignores. No split-brain config. Plus a much-improved interactive installer with hooks setup built in. Upgrade: npx impeccable install npm i -g impeccableshow more

Claude + Obsidian + n8n + 316 TB storage... built a private second brain that ships AI projects at $3,400 a month. Most people rent cloud space and pray the bills stay low. Data leaks. Models throttle. Projects slow. This stack runs everything local. → Obsidian vault grows without limits. Every note, dataset, fine-tune, client archive links in one graph. → Claude reads the full vault instantly through Projects and MCP. No token caps. No privacy risk. → n8n automates the pipelines. New data drops → auto-ingest → Claude summarizes and links. Nightly fine-tune jobs fire. Client deliverables generate on demand. → One ORICO enclosure starts at 60 TB. Add drives. 180 TB. 300 TB. Final setup hits 316 TB. HDDs for archives. SSDs for active models. Laptop-level speed in a desktop box. Plug, power, done. Month 1: Vault hits 120 GB. First local agent runs end-to-end. Month 2: Private dataset training. Sold one custom workflow for $1,200. No cloud fees. Month 3: Recurring retainers. $3,400. System trains, tests, and deploys while you review. Before: Scattered cloud tabs. Monthly bills. Slow inference. After: 316 TB under your desk. Full control. Zero latency. Projects compound. The second brain does not beg for API keys. It owns the data and prints the income. If this was useful - follow.show more

Being sore all the time is not a badge.... It means: - Your volume is too high - Your recovery is in deficit - Your next session is compromised - Your nervous system is still cleaning up the last one - Your growth is being throttled by accumulated damage Soreness is a sign you did something. It is not a sign you did the right thing. A trained muscle in a sensible programme should rarely be sore at all. The first few weeks of a new stimulus, yes. After that, your body adapts. The soreness fades. The growth carries on without it. People treat this as a problem to solve. They add drop sets. They add finishers. They chase the burn. They want that next-day ache back because the ache feels like proof. It is not proof. It is damage your body now has to repair before it can build anything new. The lifters making the most progress walk out of the gym feeling worked but not wrecked. They train the same muscle again 72 hours later because they can. The sore-every-day brigade train it again in a week and call it advanced programming. It's just bad arithmetic.show more