AI Training 👉 https://sanny-recommends.com/learn-ai You are wasting time doing things your browser should already be handling. Jumping between tabs, copying and pasting, repeating the same searches, clicking through the same workflows over and over again. That’s not a productivity problem, it’s a tooling problem. And there’s a brand new free tool that changes how this works completely. Tandem is a new open source AI browser built specifically for humans and AI to work together inside the same environment. This is not a chatbot in another tab. It’s not a Chrome extension. It’s a completely separate browser designed from the ground up for AI collaboration, and that changes everything about how you interact with the internet. What makes Tandem different is how it works alongside Open Claw. Open Claw is the AI agent doing the thinking and acting, while Tandem is the environment it operates in. You browse normally, and at the same time the AI can see what you’re doing, understand context, and actually take actions inside the browser. Inside Tandem, you get a full workspace. On one side, you’ve got built-in panels for tools like Gmail, Telegram, WhatsApp, Slack, and more, all running persistently without switching tabs. On the other side, you’ve got the Wingman panel, where your AI agent lives. It can read pages, navigate, extract data, summarize content, and help you complete tasks in real time. But the most important part, and the thing most people completely miss, is the security model. Giving AI access to your browser is risky if it’s not designed properly. Tandem was built with that as a priority. It includes multiple layers of protection like request filtering, credential leak detection, behavior monitoring, and a system that stops the AI and asks for your approval when something looks risky. Everything runs locally on your machine. That means your data, your sessions, and your activity stay under your control. Nothing is being routed through random cloud services, and the AI only acts within boundaries you approve. That’s a huge difference compared to most AI browser tools out there.

AI Training 👉 https://sanny-recommends.com/learn-ai AI agents just took a massive leap forward, and if you’re still thinking in terms of chatbots, you’re already behind. Tools like Manus and Open Claw aren’t just answering questions anymore, they’re actually doing work on your computer. Writing code, organizing files, running tasks, all without you manually stepping in. This is a completely different level of automation, and it’s happening right now. Manus just dropped a new feature called My Computer, and this is what’s got everyone talking. Before this, Manus was powerful but limited because everything ran in the cloud. You had to upload files, you couldn’t access your local setup, and that created friction. Now, Manus runs directly on your machine, meaning it can interact with your files, your apps, and your system in real time. AI Training 👉 https://sanny-recommends.com/learn-ai What makes this update so important is what it unlocks. Manus can now execute terminal commands, organize your files, build and run apps, and interact with your local environment just like a real user would. You give it a goal, and it figures out the steps and executes them. That’s the shift from AI assistant to AI agent. At the same time, Open Claw is still one of the most powerful open source AI agent tools out there. It runs locally, connects to apps like Telegram and WhatsApp, and gives you full control. But it comes with a cost, not money, but complexity. Setup takes time, you need technical knowledge, and security is entirely on you. This is where the real difference shows. Manus is built for usability. You install it, give it a task, and it works. Open Claw is built for control. You configure everything yourself, customize it fully, and run it exactly how you want. One is plug and play, the other is build your own system. AI Training 👉 https://sanny-recommends.com/learn-ai

AI Training 👉 https://sanny-recommends.com/learn-ai Claude just dropped a massive update called Skills 2.0, and it completely changes how AI workflows actually work. If you’ve ever built AI workflows before, you’ve probably run into the same problem. Something works perfectly one day, then breaks a few days later. You tweak prompts, test again, still inconsistent. Then a model update drops and everything resets. That entire cycle is what this update is designed to fix. Claude Skills 2.0 turns workflows from static instructions into self-improving systems. Instead of just writing a Skill.md file and hoping it works, skills can now test themselves, measure performance, and automatically improve when something fails. That’s a completely different way of working with AI. There are two key types of skills you need to understand. The first is capability uplift skills, which help Claude do things it normally struggles with, like handling complex document formats or structured outputs. The second is encoded preference skills, which capture your specific workflows, like how you create content, review documents, or run processes. These are the ones that become incredibly powerful over time because they reflect how you actually work. AI Training 👉 https://sanny-recommends.com/learn-ai The biggest upgrade in this release is the Skill Creator system, which now runs in four modes. First is create mode, where you describe what you want and Claude builds the skill plus initial test cases. Then comes eval mode, which runs structured tests and tells you if the skill actually works. After that is benchmark mode, which measures performance across all tests so you can track improvements. And finally, improve mode, which is where things get crazy. Improve mode looks at failures, identifies patterns, and rewrites the skill automatically to fix them. Then it reruns the tests to confirm the fix actually works. This means your AI workflows can now improve themselves without you manually debugging everything. It’s essentially a feedback loop built directly into the system.

AI Training 👉 https://sanny-recommends.com/learn-ai Most people using AI for coding run into the same problem. You ask the AI to build something, it jumps straight into writing code, and at first it looks impressive. Then you run it and everything breaks. Files are wrong, logic is off, and you’re stuck fixing things that shouldn’t have gone wrong in the first place. Google just introduced a solution to that problem with a major update to Gemini CLI called Plan Mode, and it completely changes how AI works with your code. Instead of rushing into execution, Gemini CLI now starts by thinking first, mapping everything out before touching a single file. Gemini CLI itself is Google’s open-source AI tool that runs directly in your terminal. You can install it with one command and use it to read files, write code, run commands, and interact with your entire project. It runs on Gemini 3 and even has a free tier with up to 1000 requests per day, so you can use it without paying anything. The big change is how Plan Mode works. When you activate it, Gemini CLI enters a strict read-only state. It physically cannot modify your files. Instead, it explores your codebase, analyzes your project, and builds a structured implementation plan before doing any work. This alone solves one of the biggest issues with AI coding tools, which is acting too fast without understanding the full context. While in planning mode, the AI reads your files, searches your codebase, and even looks up relevant information if needed. It then creates a detailed step-by-step plan in markdown format. Before anything happens, you review that plan, edit it, and approve it. Only then does the AI move into execution. Another powerful part of this update is how Gemini CLI asks questions during planning. If it reaches a decision point, it doesn’t guess. It stops and asks you directly. That means you’re guiding the architecture before any code is written, instead of fixing mistakes after the fact.

AI Training 👉 https://sanny-recommends.com/learn-ai AI-Powered SEO System 👉 https://sanny-recommends.com/join-seo-elite If you’re using Open Claw and your AI agent keeps forgetting everything between sessions, you’re not alone. One of the biggest issues people run into when setting up Open Claw is memory persistence. Every time the agent resets or starts a new conversation, it behaves like it has never met you before. It forgets your goals, your context, and the instructions you gave it earlier. For anyone using AI agents to manage communities, automate workflows, or handle support tasks, that kind of memory loss can completely break the experience. The reason this happens is because Open Claw is designed to start sessions clean unless memory persistence is configured correctly. By default, the system doesn’t automatically carry context between sessions. That means when a reset happens, the agent simply starts from scratch. Many users also ran into additional memory issues after early 2026 updates where certain launcher versions caused memory compaction problems or stale context errors. The real solution is something the community built called a three-layer memory architecture. Once you implement it, your agent stops acting like a stranger every session and instead builds a persistent knowledge system that grows over time. The first layer is core identity memory. This is where you define the fundamental rules of the agent. It usually lives in files like soul.md, agents.md, memory.md, and user.md. These files define the agent’s personality, its role, and who it is serving. For example, you might define the tone of the assistant, the goals of the system, and the type of tasks it should handle. This layer stays short, clear, and written in simple present-tense statements so the agent can quickly understand its purpose.