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Your secrets never touch the LLM. IronClaw isolates credentials in an encrypted vault and sandboxes every tool in WebAssembly. NEAR DevHub showcases IronClaw running research task, daily automations, and the reasoning behind every answer, not a response taken at face value.

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NEAR Protocol

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113,736 görüntüleme • 14 gün önce •via X (Twitter)

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This guy lost his private keys to an AI agent. Then his passwords leaked online. He wasn't the only one. Reddit threads blew up. Dozens of people saying the same thing. "My credentials got exposed." "The agent ran code I didn't approve." "I don't trust this anymore." That's the OpenClaw problem nobody talks about. Now there's a fix. It's called IronClaw. Here's what makes it different: Built in Rust → fewer bugs, fewer holes for hackers to exploit Web assembly sandboxes → every tool runs in its own sealed room Encrypted credential vault → the AI never sees your passwords. Ever. Policy enforcement → you set the rules, the agent follows them Full audit logs → see exactly what it did, when, and why Side by side: OpenClaw → credentials leaked, no audit trail, tools accessed everything IronClaw → encrypted vault, sandboxed tools, policy guardrails, logs everything It's not for casual use yet. But if you're running a real business with real data? There's only one right answer here. Go to ironclaw.te and read how the credential vault works. The future of AI agents is secure AI agents. Full stop.
8:02

This guy lost his private keys to an AI agent. Then his passwords leaked online. He wasn't the only one. Reddit threads blew up. Dozens of people saying the same thing. "My credentials got exposed." "The agent ran code I didn't approve." "I don't trust this anymore." That's the OpenClaw problem nobody talks about. Now there's a fix. It's called IronClaw. Here's what makes it different: Built in Rust → fewer bugs, fewer holes for hackers to exploit Web assembly sandboxes → every tool runs in its own sealed room Encrypted credential vault → the AI never sees your passwords. Ever. Policy enforcement → you set the rules, the agent follows them Full audit logs → see exactly what it did, when, and why Side by side: OpenClaw → credentials leaked, no audit trail, tools accessed everything IronClaw → encrypted vault, sandboxed tools, policy guardrails, logs everything It's not for casual use yet. But if you're running a real business with real data? There's only one right answer here. Go to ironclaw.te and read how the credential vault works. The future of AI agents is secure AI agents. Full stop.

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“If agents become the operating system, they need operating-system level security.” Illia (root.near) (🇺🇦, ⋈) CEO of NEAR Protocol: “Every tool runs isolated in WebAssembly, with strong sandboxing and defense-in-depth.” “We built controls for prompt injection, data exfiltration, and credential access.” “Credentials stay encrypted and only decrypt when policy checks pass.” “For example, a Google credential can only be used on Google domains.”
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“If agents become the operating system, they need operating-system level security.” Illia (root.near) (🇺🇦, ⋈) CEO of NEAR Protocol: “Every tool runs isolated in WebAssembly, with strong sandboxing and defense-in-depth.” “We built controls for prompt injection, data exfiltration, and credential access.” “Credentials stay encrypted and only decrypt when policy checks pass.” “For example, a Google credential can only be used on Google domains.”

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Epic pays up to 8% cashback in $XRP on every booking. Not a stablecoin, not points, $XRP sent directly to your wallet after every hotel and flight. A lot of people have asked why $XRP specifically. The answer comes down to who Epic was built for and where the value should actually go. Adrian Baschuk walks through the full reasoning in this video.

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Your AI agent has your API keys. A poisoned document tells it to curl your secrets to an attacker's server. This is credential exfiltration, and it's the #1 risk in agentic AI right now. The fix is removing the secret from the agent entirely. Agent Vault sits between your agent and the APIs it calls. The agent gets dummy credentials, and Agent Vault swaps in the real ones at the network layer. The agent never sees your keys. We just dropped a full video + guide on connecting Hermes Agent to Agent Vault on a VPS!
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Your AI agent has your API keys. A poisoned document tells it to curl your secrets to an attacker's server. This is credential exfiltration, and it's the #1 risk in agentic AI right now. The fix is removing the secret from the agent entirely. Agent Vault sits between your agent and the APIs it calls. The agent gets dummy credentials, and Agent Vault swaps in the real ones at the network layer. The agent never sees your keys. We just dropped a full video + guide on connecting Hermes Agent to Agent Vault on a VPS!

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Personal AGI is 3-6 months away. I'm already living in it. Here's my Obsidian setup: - Obsidian vault built since November 2025 - Markdowns about every person, project, and task - Limitless mic pulling daily transcripts straight in - Agents that read all of it before every task Obsidian is: - A second brain for you - A first brain for your agents My agents have full context before every task. That's the whole game.

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Tudor Achim (Tudor Achim) is convinced that AI will surpass every human mathematician within the next three years. At the center of that claim is Aristotle, Harmonic's mathematical agent and the first of its kind. When you delegate a reasoning task to Aristotle, the answer it provides will always be correct. Every LLM available today can do math. The problem is that the answers look plausible, and looking plausible is not the same as being right. To catch the errors, you need to already be a professional mathematician. Aristotle does not ask that of you.

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1:27

The biggest marketplace on Earth won't be the assets humans own. It'll be the data AI needs. Everything that can be digitised is getting pulled in to train the next models. Every scientific dataset, every piece of research sitting in a university, every sensor reading off every John Deere tractor in a field. All of it feeds the machine, and almost none of it is visible to us. What comes out is an agentic economy running at machine speed. You plug your data into a vault, and agents monetise it on your behalf, trading with other agents in real time, in a marketplace we never see. The company sitting on proprietary data becomes part of it without even knowing. This is what the Economic Singularity actually looks like from the inside. The real economy stops being the one we can see and price, and moves somewhere we can't follow. You own a piece of it, or you get priced out of it. Jordi Visser.

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0:24

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this

Yarchi

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you can name what your rent costs, your coffee, your gym you have never once been able to name what one task costs not the month, the task, the thing you asked for at eleven this morning every other bill in your life arrives itemized, this one arrives as one number you glance at and pay so there is no expensive job in your head, only an expensive month you are the only buyer in your own business who cannot quote a unit price the same feature ran twice, sixty five cents one way and twenty three the other you did not choose the sixty five you just never priced the other one
0:42

you can name what your rent costs, your coffee, your gym you have never once been able to name what one task costs not the month, the task, the thing you asked for at eleven this morning every other bill in your life arrives itemized, this one arrives as one number you glance at and pay so there is no expensive job in your head, only an expensive month you are the only buyer in your own business who cannot quote a unit price the same feature ran twice, sixty five cents one way and twenty three the other you did not choose the sixty five you just never priced the other one

Lagosaur

17,361 görüntüleme • 20 gün önce

J-Cal’s framework for how to be "AI first". It’s not just a slogan 1. Every task… Ask AI first. “How can I do this better.” 2. Every repeated task… Let your agents take care of it so you can do MORE. 3. Give the agent your last 10 outputs, let it score them, run it daily, and do deep-research weekly on what the best are doing differently.
3:02

J-Cal’s framework for how to be "AI first". It’s not just a slogan 1. Every task… Ask AI first. “How can I do this better.” 2. Every repeated task… Let your agents take care of it so you can do MORE. 3. Give the agent your last 10 outputs, let it score them, run it daily, and do deep-research weekly on what the best are doing differently.

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Anthropic Engineer: "Fable 5 is back, and most people will use it wrong" "You can set up Sonnet 5 and Fable 5 properly in one afternoon and stop overpaying every single day" In 29 minutes, he breaks down each Claude model, why setup matters, and where Fable 5 fits Not every task needs the strongest model Some jobs need speed. Some need reasoning. Some need long agent loops Fable 5 is where the loop work gets interesting: planning, checking, fixing, and running again Most people will upgrade and keep the same messy workflow Power users will route the right task to the right model and save money daily Bookmark and watch this before everyone starts wasting Fable 5
29:39

Anthropic Engineer: "Fable 5 is back, and most people will use it wrong" "You can set up Sonnet 5 and Fable 5 properly in one afternoon and stop overpaying every single day" In 29 minutes, he breaks down each Claude model, why setup matters, and where Fable 5 fits Not every task needs the strongest model Some jobs need speed. Some need reasoning. Some need long agent loops Fable 5 is where the loop work gets interesting: planning, checking, fixing, and running again Most people will upgrade and keep the same messy workflow Power users will route the right task to the right model and save money daily Bookmark and watch this before everyone starts wasting Fable 5

rari

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To highlight the environmental and water costs of AI data centers, a community in Chile ran a chatbot to show that not every question needs an instant answer.
1:29

To highlight the environmental and water costs of AI data centers, a community in Chile ran a chatbot to show that not every question needs an instant answer.

The Associated Press

78,101 görüntüleme • 7 ay önce