I recently explored TinyFish, a web agents API. What... stood out wasn’t hype. It treats the web like infrastructure. Natural language goal in → multi-site execution → structured data out. Less “AI magic.” More systems thinking.show more

Web Scraping is dead. Web Agenting is here. Writing... selectors (div > .class > span) breaks every time a site updates. Building custom bots for every new target is a waste of engineering hours. TinyFish turns the entire real-time web into a single API. Input: Natural Language ("Find availability for X"). Target: 1 or 100 URLs. Output: Structured JSON. This isn't a simulation. It visits the Real-Time Web. 1./ One API, Many Sites - Same contract whether you hit 1 URL or 50. You focus on the Goal (Business Logic). TinyFish handles the How (Navigation, Clicks, Inputs). 2./ Real Automation - It doesn't just "read." It interacts. It fills forms, navigates multi-step flows, and handles dynamic JS content. 3./ Production Ready - This is the same infrastructure used by large enterprises, now exposed as a clean developer primitive. Logs, error handling, and structured data are built-in. The web is finally a proper API.show more

THE LLM WORLD ISN’T JUST CHATGPT ANYMORE. It’s an... entire ecosystem. Think of it like a tech stack: → Models GPT Claude Gemini Llama → Frameworks LangChain LlamaIndex DSPy → Tools MCP Vector databases Web search Code execution → Applications AI agents Coding assistants RAG systems AI automation And they all connect. Model → Context → Tools → Memory → Actions That’s why building with AI is becoming less about “which model is best?” And more about: How do all these pieces work together? The model is only one part of the system. ------- Check out these AI resources to get started. Inside you'll find: • 1,000+ AI prompts • Curated AI tools • Automation workflows • Productivity systems • Real-world use cases and examples Download here: -------show more

After trying BytePlus Seedance 2.0 with native 4K output,... what stood out wasn’t just resolution—it was how stable and natural the image feels in motion. Fine textures, reflections, and subtle details don’t break apart between frames. They stay consistent, which gives the footage a more cinematic and grounded feel rather than a purely technical upgrade. Combined with native 10-bit color, the result offers smoother gradients, stronger grading flexibility, and a more refined post-production workflow. Overall, it feels less like a quality bump and more like a step toward genuinely production-ready AI filmmaking.show more

Think about what this actually replaces. Game sales become... subscription-based world creation. DLCs become real-time environment customization. Studios become world generation systems. Buzzy is not a gaming tool. It is a preview of what the entire industry infrastructure looks like when AI removes the bottleneck between imagination and execution. One photo in. A full AAA world out. The pipeline just collapsed into a single step.show more

I still see regular people have no clue how... we use AI to code They think it's like AI Agents and lots of hype bs But for me most of it isn't very difficult or deep or fancy but it's simply A LOT of autocompleting and prediction now Small things like this a few mins ago: Nomad List's weather API robot that pulls the weather every day to show on the site, sometimes it hits an error on the API side, and it sends that to my Telegram Then I wanna know "ok for what city is it erroring?" The moment I just put my cursor on "Bad API reply" it already knows what I want and autocompletes to "Bad API reply for city $city['name']" which will tell me for example "Bad API reply for Bangkok" Basic stuff like that saves me a lot of seconds and minutes in a day and it adds up!show more

🚨 Alibaba just open sourced a GUI agent that... lives inside your webpage and controls it with natural language. It's called Page Agent and it's not a browser extension. It's pure JavaScript no Python, no Puppeteer, no headless browser, no screenshots. Just one script tag and your web app understands natural language. Here's what it actually does: → Embed it with a single tag or npm install → Control any web interface with plain English commands → Text-based DOM manipulation no OCR, no vision models needed → Bring your own LLM (GPT, Claude, Qwen, anything) → Ships a built-in UI with human-in-the-loop support → Turn 20-click ERP/CRM workflows into one sentence → Optional Chrome extension for multi-tab agent tasks → Works on any web app SaaS, admin panels, internal tools Companies are charging $30/month for AI copilots built on this exact idea. This is 3 lines of code. Your users. Your interface. The AI copilot layer for every web app just got open sourced. 1.6K stars. 100% Open Source. (Link in the comments)show more

🔥 Solaris AI Copilot is now open & free... for everyone. No more LLM keys. Tell Copilot what you want to automate on Solana in plain language. It builds, validates, and dry-runs the workflow against live data before you execute. 16 integrations are live across swaps, perps, onchain + market data, indicators, memecoins, smart money, RWAs, stocks, alerts, privacy, x402 and more. Built in: • Multi-run automations • Duplicate-trade protection • Failure recovery • Execution proofs • Pre-execution safety checks Next: turning workflows into standalone apps.show more

In 2025, the AgentFlayer exploit highlighted a new category... of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.show more

I stopped thinking of AI audio as "voice generation."... After testing Seed Audio 1.0, it feels less like a traditional TTS model and more like an AI audio creation engine for building complete scenes. One prompt handled the dialogue, emotion, ambience, music, and sound effects—giving the visuals a natural rhythm to follow. I tried it across several storytelling scenarios. Try it: 🧵 Results below: BytePlus Luminashow more

That’s why using Tails OS, Whonix, or Kodachi (this... looks like it might be the one- can anyone recognize the interface?) with automated data self-destruction is always a smart move… In the footage, two police officers can be seen “working” on the suspect’s computer. One pulls out a flash drive and plugs it in, only for the data to start self-destructing and wipe everything… As reported, the suspected owner of the deep-web marketplace escaped punishment thanks to a police officer’s mistake and was recently released.show more

Agent Skills are now live for GOAT BitVM2 nodes.... Run a challenger, bridge in, peg out, upgrade your node - all through natural language. No CLI. No manual setup. Tell an agent what you want and it executes end-to-end. Recently shipped Testnet fixes: → Resolved peg-in processing delays → Fixed node stalling edge case → Improved edge case handling across the board → More accurate bridge-out stats Skills: Full Testnet guide:show more

I remember spending weeks digging through government sites, tracking... procurements, and building databases of China’s provincial leaders in my previous life as a journalist. The grind was real—slow and frustrating. I want to offer my friends in media and research with free structured web data with AgentQL . Need to track gov policies, procurement data, or economic trends? We just went live, and I’m excited to see how this can support the important work journalists do every day. Reach me out:show more

I just built a complete SEO audit plugin in... Claude Code that replaces your $200/mo Ahrefs subscription 🤯 One Claude Plugin audits any store: technical SEO, product schema, content, Core Web Vitals, and AI-search readiness. Parallel agents, a 0-100 score, and a dashboard that renders right in the panel. All inside Claude Code. So I pointed it at Ridge .com, one of the sharpest DTC operators out there. It came back 56/100, and what stood out wasn't a knock on them at all: Ridge has a better AI-commerce setup than 99% of stores. A real llms.txt, an agent-discovery sitemap, a live MCP endpoint, genuinely ahead of the curve. And even on a store that dialed-in, the audit surfaced fixable gaps in ~90 seconds: → Room to add product structured data → A mobile Core Web Vitals score worth tightening → A thin meta description on a high-traffic collection Perfect for e-comm operators and SEO agencies who are sick of paying $200/mo for tools that bury the real issues, running quarterly audits that take a week, and shipping reports nobody can act on. So I put together the full playbook to build your own. The complete guide to building this Plugin in Claude Code: branded to you, tuned to exactly how you audit, repeatable across every client. The kind of audit you run in minutes and hand over as a deliverable that looks like it cost thousands. What's inside: → The architecture (orchestrator + parallel sub-agents) → How to fetch any store past Cloudflare → The 0-100 scoring + falsifiable-findings framework → How to ship the HTML dashboard for client demos → The full build, start to finish Want the playbook for free? > Like this post > Comment "SEO" And I'll send it over (must be following so I can DM)show more

I didn’t expect AI to make ad creation this... fast. Just tested Pollo AI Marketing Studio to see what it can do. Tried making a sports streaming app ad from a single product image. No editing. No timeline. No production setup. Just picked a video format and it generated a full video ad in seconds. What stood out wasn’t just the output,, it was how simple the whole process is now. What used to take multiple steps and tools can now be done in a single workflow. Curious how others see this, would you use something like this for ads?show more

From idea to animated animal movie in minutes. I... tried the new Animal Drama Agent on insMind, and the experience was wild. One simple prompt was enough to generate consistent characters, a complete multi-scene storyboard, and cinematic AI video sequencesall in a single workspace. It feels less like prompting and more like directing your own animated film.show more

Big news for everyone who loves making videos! 🎉... CapCut just dropped Seedance 2.5! Now you can generate your AI clips AND edit them in the exact same workspace. No hassle, just pure creativity! ✨ What’s fresh: Control scenes by timestamp Input up to 50 references Generate up to 90 seconds Green screen friendly Multi-language support Check it out ⬇️ 💻 Web: 📱 App: #CapCut #Seedance25 #CapCutai #CapCutDidThatshow more