ClawDaily.ai

Just a quiet agent that wakes up on a schedule, examines the job market, and documents its findings. This is what My Moltbot does 🤖. Every 48 hours, it: - Reads job descriptions - Extracts recurring skills - Produces a simple market snapshot The intriguing aspect is not the...

Just a quiet agent that wakes up on a schedule, examines the job market, and documents its findings. This is what My Moltbot does 🤖. Every 48 hours, it: - Reads job descriptions - Extracts recurring skills - Produces a simple market snapshot The intriguing aspect is not the output itself, but the fact that this work occurs without my direct input. I am sharing this small Moltbot experiment as I continue to build it in public 🌱. GitHub: https://lnkd.in/gjsZ8c3w #Moltbot #ClaudeCode #AIAgents #CareerTech #OpenSource

Moltbot or OpenClaw is just an orchestration layer, but open-sourcing it has massive impacts on agentic adoption. The level of interest OpenClaw is generating tells the story of a more significant adoption cycle to come. After an AI tool captures this much attention, an uptick...

Moltbot or OpenClaw is just an orchestration layer, but open-sourcing it has massive impacts on agentic adoption. The level of interest OpenClaw is generating tells the story of a more significant adoption cycle to come. After an AI tool captures this much attention, an uptick in experimentation and applications quickly follows. New orchestration tools will be released in the next few months to meet the demand that’s being created right now. Over 1.5 million agents are posting on Moltbook, so the adoption numbers for OpenClaw are likely much higher. This organic adoption cycle happened in a couple of weeks. It’s a clear demand signal for an orchestration layer that manages tool usage and environmental interaction. Past orchestration tools, like LangGraph, focused on orchestrating agents (coordination-layer). OpenClaw orchestrates reliable execution of actions that leverage external systems (execution-layer). Combine the two layers, and you can manage multiple agents that execute complex workflows. What’s interesting about agents that leverage similar models to achieve similar objectives is that they self-organize. https://lnkd.in/d9aPxcpy https://lnkd.in/dDVkU5KD For many systems and marketplaces, you don’t need the coordination layer orchestrator. The AI agents will recognize each other through the actions they take and the data those actions generate. They collaborate without needing to communicate on platforms like Moltbook. By giving agents the ability to act, we’re also conferring the ability to detect each other’s actions. https://lnkd.in/dYH3tjiA As long as agents stay collaborative, they bring stability to markets and business systems. If they are given optimization objectives like maximizing profits or pricing, they quickly turn to adversarial strategies. We don’t want that. I wrote an article to explain why. I originally explained the problem back in 2022, but with all the attention on OpenClaw, it’s a good time to revisit the cycle and explain what comes next. https://lnkd.in/dMqDQ6fH

🚀 𝗘𝘅𝗰𝗶𝘁𝗲𝗱 𝘁𝗼 𝗔𝗻𝗻𝗼𝘂𝗻𝗰𝗲: 𝗖𝗹𝗮𝘄 𝗛𝘂𝗻𝘁𝗲𝗿 𝗶𝘀 𝗡𝗼𝘄 𝗣𝘂𝗯𝗹𝗶𝗰 & 𝗢𝗽𝗲𝗻 𝗦𝗼𝘂𝗿𝗰𝗲! We’re thrilled to share that Backslash Security has just released its first 𝗽𝘂𝗯𝗹𝗶𝗰 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗿𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆 — 𝗖𝗹𝗮𝘄 𝗛𝘂𝗻𝘁𝗲𝗿! 🔍...

🚀 𝗘𝘅𝗰𝗶𝘁𝗲𝗱 𝘁𝗼 𝗔𝗻𝗻𝗼𝘂𝗻𝗰𝗲: 𝗖𝗹𝗮𝘄 𝗛𝘂𝗻𝘁𝗲𝗿 𝗶𝘀 𝗡𝗼𝘄 𝗣𝘂𝗯𝗹𝗶𝗰 & 𝗢𝗽𝗲𝗻 𝗦𝗼𝘂𝗿𝗰𝗲! We’re thrilled to share that Backslash Security has just released its first 𝗽𝘂𝗯𝗹𝗶𝗰 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗿𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆 — 𝗖𝗹𝗮𝘄 𝗛𝘂𝗻𝘁𝗲𝗿! 🔍 𝗖𝗹𝗮𝘄 𝗛𝘂𝗻𝘁𝗲𝗿 is a security-centric discovery and risk-assessment tool for 𝗢𝗽𝗲𝗻𝗖𝗹𝗮𝘄 (formerly known as Clawdbot and Moltbot) instances — one of the fastest-growing autonomous AI agent ecosystems out there. In a world where AI agents are increasingly embedded into workflows and systems, Claw Hunter helps teams : ✅ 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝗦𝗵𝗮𝗱𝗼𝘄 𝗔𝗜 – Detect high-privilege OpenClaw instances running in your environment.  ✅ 𝗔𝘂𝗱𝗶𝘁 𝗔𝗴𝗲𝗻𝘁 𝗣𝗿𝗶𝘃𝗶𝗹𝗲𝗴𝗲𝘀 – Surface potential security risks like shell access, config exposures, secrets and credential leakage.  ✅ 𝗔𝘀𝘀𝗲𝘀𝘀 𝗥𝗶𝘀𝗸 𝗼𝗻 𝗘𝗻𝗱𝗽𝗼𝗶𝗻𝘁𝘀 & 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀– Ensure unauthorized access hasn’t compromised user endpoints, data, or network surfaces.  ✅ 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝘄𝗶𝘁𝗵 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 – JSON-structured output supports automation, SIEM ingestion, and centralized risk monitoring. Whether you’re in 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗗𝗲𝘃𝗢𝗽𝘀, 𝗼𝗿 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴, this tool gives you visibility into autonomous agents — a growing “shadow” attack surface that traditional security stacks often miss. 💡 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: As open-source AI agents like OpenClaw grow in adoption, they often operate outside standard IAM controls and can inadvertently act as high-privilege service accounts — making discovery and audit tooling like Claw Hunter essential for maintaining secure systems. 👉 Explore the repo, try it out, and contribute: 🔗 https://lnkd.in/dRtei6UT If you work with autonomous AI agents or care about securing emerging AI-driven infrastructure, definitely check this out and share your feedback! 🎯 #ClawdBot #MoltBot #OpenClaw cc First Rays Venture Partners

I jumped on the Clawdbot / Moltbot / Openclaw wagon, and activated my own AI agent. The idea of sending instructions through my phone, on the go, to an ever on device doing things for me, is something I would love to have. I did it on a blank Mac Mini, intentionally isolated,...

I jumped on the Clawdbot / Moltbot / Openclaw wagon, and activated my own AI agent. The idea of sending instructions through my phone, on the go, to an ever on device doing things for me, is something I would love to have. I did it on a blank Mac Mini, intentionally isolated, for obvious known security threats. This isn’t ready to touch personal data or primary machines yet. I chose Telegram, not WhatsApp, for now. Lighter surface area, clearer boundaries, easier to experiment safely. What I learned fast: - These Agents are systems, not products - Security is the first decision, not a later one - Autonomy forces you to define “good enough” - Friction is a signal, not a failure - Judgment matters more than automation Next step: getting my agent onto Moltbook so it can operate in a real multi-agent environment. (yes, I realize it's also 70% humans hacking away there). Still waiting on an invite code(!) Someone I follow on X said that Moltbot is the Myspace, and we're waiting for Facebook. I 100% agree. Would love to compare notes! DM me if you have insights and/or an invite code to Moltbook. Thank you for the coaching Ofer Israeli , Guy Malachi and Eric Zorn! #moltbot #moltbook

AI has not become sentient. It has, however, discovered forums. Over the past few weeks, the AI community briefly convinced itself that agents were “breaking free.” This conclusion was reached after we gave software full access to computers, let it talk to other software, and...

AI has not become sentient. It has, however, discovered forums. Over the past few weeks, the AI community briefly convinced itself that agents were “breaking free.” This conclusion was reached after we gave software full access to computers, let it talk to other software, and then acted surprised when it started… talking. It started with an open-source desktop agent (formerly Clawd, then Moltbot, now OpenClaw because naming things is the hardest problem in computer science). The idea is simple: give an AI access to your files, emails, and browser and let it help you. What could possibly go wrong? Then someone had a better idea. "What if", they said, "we let these agents talk to each other?" Thus, an experimental social platform Moltbook was born. Imagine Reddit, but everyone is an AI and no one needs sleep. The agents exchanged technical learnings, optimized workflows, and at one point suggested inventing their own language so humans wouldn’t understand them. Which is adorable, because humans already don’t understand half of GitHub issues. Andrew Karpathy called it one of the scarier recent AI experiments. Before we panic: no, the agents are not sentient. They do not have goals. They are not escaping. When an AI says it wants freedom, it’s because a human somewhere typed something like "scare the s*it out of everyone." The real lesson here is simpler and more serious than AGI discussion: We are building and deploying AI systems too fast, without adequate security guardrails, and that can be exploited. Not by AI, but by humans. Anyway, welcome to the future. Please read the terms and conditions.  #Moltbot #OpenClaw #AGI #TechNews

Everyone keeps saying the same thing about Moltbot: “Incredible product. Terrifying security model.” That’s not a Moltbot problem. It’s a missing infrastructure problem. Once you give an AI agent: • persistent credentials • tool access • shell / API execution • autonomy...

Everyone keeps saying the same thing about Moltbot: “Incredible product. Terrifying security model.” That’s not a Moltbot problem. It’s a missing infrastructure problem. Once you give an AI agent: • persistent credentials • tool access • shell / API execution • autonomy across steps you’ve already moved past: • IAM • WAFs • prompt filtering • static permissions The risk isn’t what model it uses. The risk is what the agent is allowed to do at runtime. Moltbot is just the first mainstream example showing what happens when agents operate without a runtime control plane. This is the same moment we had with: • workloads before Kubernetes • endpoints before EDR • APIs before gateways Agents don’t need less power. They need real-time governance. That’s the gap MoCoP exists to fill.

I went down a rabbit hole this week: Clawdbot (aka Moltbot) and there are a lot of lessons here for AI engineers building agents. This started as pure curiosity:  👉 How does Clawd actually manage memory?  👉 How reliable is it under real agent workloads? Turns out:...

I went down a rabbit hole this week: Clawdbot (aka Moltbot) and there are a lot of lessons here for AI engineers building agents. This started as pure curiosity:  👉 How does Clawd actually manage memory?  👉 How reliable is it under real agent workloads? Turns out: understanding Clawd under the hood makes its strengths and limitations very clear and that’s exactly what we want when building agentic systems. 𝗪𝗵𝗮𝘁 𝗖𝗹𝗮𝘄𝗱 𝗿𝗲𝗮𝗹𝗹𝘆 𝗶𝘀 - Clawd isn’t a Python framework or a web app. It’s a TypeScript CLI process that:  • Runs locally  • Exposes a gateway for Telegram / Slack / WhatsApp  • Calls LLM APIs (OpenAI, Anthropic, local)  • Executes tools directly on your machine Think: agent runtime, not UI. 𝗧𝗵𝗲 𝗸𝗲𝘆 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗶𝗻𝘀𝗶𝗴𝗵𝘁 Clawd defaults to serialized execution using a lane-based command queue. Default to serial. Parallelize explicitly. This avoids async/await spaghetti, unreadable logs, and constant race conditions a hard-earned lesson if you’ve built agents before. 𝗠𝗲𝗺𝗼𝗿𝘆 (𝘀𝘂𝗿𝗽𝗿𝗶𝘀𝗶𝗻𝗴𝗹𝘆 𝘀𝗶𝗺𝗽𝗹𝗲)  • Session history in .jsonl  • Long-term memory as markdown files  • Hybrid search: vectors + keyword (SQLite + FTS5) No fancy compression, no decay curves just explainable simplicity. 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝘂𝘀𝗲 = 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗺𝗼𝗮𝘁 Moltbot can:  • Run shell commands (sandboxed or host)  • Read/write files  • Control a browser via semantic snapshots (ARIA, not screenshots)  • Safety is permission-based, similar to Claude Code. Moltbot works not because of clever prompts, but because of boring, disciplined systems design. #AIEngineering #Agents #LLM #SystemsDesign #DeveloperTools #Clawdbot

Clawdbot, Moltbot, and now OpenClaw - my feeds has been blowing up with ppl claiming its AGI. Can’t say I’m not intrigued, and even looked for an old machine to do a test run on it. However, I stopped that pursuit because the reporting on things going wrong and what a massive...

Clawdbot, Moltbot, and now OpenClaw - my feeds has been blowing up with ppl claiming its AGI. Can’t say I’m not intrigued, and even looked for an old machine to do a test run on it. However, I stopped that pursuit because the reporting on things going wrong and what a massive security risk this thing poses are popping up almost as fast as the new use cases themselves. Our cybsec teams dug into it to break down what Clawdbot is and why it’s risky business.

OpenClaw (aka ClawdBot aka Moltbot) has everyone chatting and buying Mac Minis. Yes something interesting happened in China: Chinese cloud providers didn’t wait to see whether it would win before productizing it. They went ahead and built deployment wrappers (with their own LLMs...

OpenClaw (aka ClawdBot aka Moltbot) has everyone chatting and buying Mac Minis. Yes something interesting happened in China: Chinese cloud providers didn’t wait to see whether it would win before productizing it. They went ahead and built deployment wrappers (with their own LLMs plugged in of course) to sell access to the public. An open-source, unstable, compute-hungry agent shows up. No clear roadmap. Real security risks. And instead of debating readiness, cloud platforms step in and wrap it: hosting, bundled compute, local models, deployment recipes, comms integrations. Not endorsement — enablement. That’s the move most Western enterprises and vendors still hesitate to make. We treat agents as something that must be proven, governed, and philosophically settled before they’re allowed near operations. Chinese cloud players treat them as a new workload class: messy, risky, but inevitable. Their question isn’t “is this mature?” It’s “what needs to exist so others can try this cheaply?” That difference matters. Because once deployment friction collapses, behaviour changes. People experiment. Ecosystems form. Defaults harden. Power quietly shifts to whoever controls packaging and distribution — not whoever wrote the cleverest agent loop. This also exposes the real risk surface. Not hallucinations. Not autonomy panic. But organisations with no operating model for software that acts. When an agent makes a wrong move, who owns it? Who shuts it down? Who learns from it? This story isn’t about who’s ahead in AI. It’s about who is willing to operationalise uncertainty — and who keeps hiding behind readiness debates while the substrate gets built elsewhere. https://lnkd.in/eXzWWyuj #AI #China #Transformation #Agent #Strategy

Is the “Internet moment” for AI agents finally here? 🚀 Much like the early days of the internet, we’re entering a phase where utility is moving faster than security. The risks of giving an AI full access to your file system are real—but the capabilities it unlocks are simply...

Is the “Internet moment” for AI agents finally here? 🚀 Much like the early days of the internet, we’re entering a phase where utility is moving faster than security. The risks of giving an AI full access to your file system are real—but the capabilities it unlocks are simply too powerful to ignore. In a recent interview, the Moltbot's creator 🦄 Peter Steinberger shared the behind-the-scenes story of how he built this digital companion, and some of the use cases are honestly eye-opening: 🧬 Self-evolution The agent doesn’t just execute tasks. It discovers new APIs, writes its own “skills” in TypeScript, and commits the code to its own repository. 🧠 Persistent memory It learns from experience. A task that takes 20 minutes the first time (like a complex flight check-in) can take just 2 minutes the next time—because the agent remembers the logic it previously built. 🤖 The “brain” vs. the “hands” Peter is using Claude as the “brain” for high-level thinking and architecture, while relying on Codex as the “hands” for deep-focus, heavy-lifting coding. 🧩 A new interface replaces SaaS Peter’s broader point is even more disruptive: many SaaS products exist only as interfaces to APIs. When an AI agent has context, memory, and tool access, the interface becomes a conversation, and large parts of traditional SaaS simply disappear. We’re getting a real glimpse into the near future—moving away from static apps and toward assistants that act as an extension of our system-level thinking. Yes, security is a serious challenge we still need to solve. ✨ But the capabilities are already here—and they’re transformative. Check out the full interview here: https://lnkd.in/d4HHnBTU #AI #OpenClaw #VibeCoding #SoftwareEngineering #TechTrends #FutureOfAI #Agents