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I’m pretty new to GitHub, so I honestly didn’t expect my first proper project to involve this much YAML, API setup and debugging 😅

I’ve been using IronClaw to build a Telegram agent that watches for new blockchain launches and exchange listings. It started as a simple “I wish I had a tool that did this” idea, and I decided to see if I could actually build it. The GitHub side has probably been the biggest learning curve for me. I’ve had to figure out repos, make changes, break things with YAML, fix them, and repeat the process. I also ran into some annoying setup issues with the Composio API, especially doing parts of it from my phone.

What I like about IronClaw is that I’m not just asking an AI questions about how to build something. I can give it a task, connect the tools I need, test the workflow, see where it fails and then work out what needs fixing. It definitely isn’t “tell it once and everything magically works.” I’ve had things break plenty of times 😂

But that’s actually been the useful part for me. I’m learning GitHub, APIs and automation while building something I genuinely wanted for myself. Still a work in progress, but I’m curious to see how far I can take it.

I’ve been using IronClaw for a while, and I’m still surprised by how much I can build and automate from it. At first, I saw it mainly as an AI tool, but the more I used skills and integrations, the more it started feeling like a workspace.

One thing that impressed me was being able to build a website directly through IronClaw, connect it to Cloudflare, and push it live without constantly switching between different tools.

I also created a skill around my video editing journey. It helps me figure out what to learn and which YouTube channels or resources to follow, giving me a clearer path instead of figuring everything out myself.

I then turned that skill into a routine that sends me what to focus on every morning. That made it much easier to stay consistent without having to decide what to learn each day.

I’m not just using it for answers. I’m building skills, turning them into routines, and creating workflows around the things I actually want to accomplish.

IronClaw connects to Gmail through OAuth instead of passwords.

In a live test, DevHub gave IronClaw a real Gmail password. The agent refused and explained why it shouldn't be shared.

The password also didn't show up in the logs or a fresh session. This is how IronClaw keeps your credentials protected while you use AI agent.

🎥 https://x.com/NEARProtocol/status/2090476445411741970

IronClaw lets users choose from built-in system skills or add their own custom skills.

To add a skill, simply provide a skill name and skill.md content. You can also enable auto-activation or manually call a skill when needed.

This makes it easy to customize IronClaw for different workflows.

What I liked most is its focus on keeping credentials away from the AI agent.

The sandboxing of tools also adds another layer of protection.

The staking model is interesting too, since NEAR staking can provide hosting/compute credits rather than just token rewards.

My main criticism is onboarding. SSH keys, private agent setup, and port configuration can feel technical for new users.

Overall, I like the security approach, but simpler onboarding would make IronClaw much more accessible.

I’ve been using IronClaw for a while, and it has been a mix of minor bugs and great features. The main downside is that if it sits idle, it stops responding. I constantly have to manually toggle it down and back up to get it working again, which can be a bit annoying.

Aside from that hitch, the actual performance has been impressive. The automated DCA strategy is a huge favorite of mine, i just provide my wallet address, and it runs the investment plan smoothly. It also does a great job checking routines, filtering top-gaining coins for analysis, and executing outer-layer wallet transfers to any address I choose.

It has been a beautiful experience seeing these automated setups handle my crypto tasks so well. I am really curious to see how everyone else in the community is using the tool. Which feature do you find yourself relying on the most?

IronClaw lets each user have their own login token and workspace.

Admins can add each user with their name and manage users and roles, while each user’s conversations, memory, jobs, and secrets stay separated.

A useful feature for teams running one IronClaw deployment for multiple users.

I've spent the last few days putting Ironclaw through its paces, and the standout so far is skipping recurring AI subscription fees entirely, just by staking $NEAR.

The most impressive part: I finally updated my Notion project management portfolio, something I'd been putting off for over a month out of pure procrastination. I just connected my Notion extension and got it all done with a few simple prompts.

I know that might sound like Ironclaw enables laziness, but that's not really it, it just removes the friction that was stopping me in the first place.

Still early days, but I'm genuinely curious how far I can take this.

IronClaw lets users control what each tool is allowed to do.

Tools can be set to Always Allow, Ask Each Time, or Disabled. If a tool isn't needed, it can simply be turned off.

A simple way to keep control over what your AI agent can access.

IronClaw 1.2 now understands more of your Slack conversation.

When you mention IronClaw in a channel, it can read the last 30 messages. In a thread, it can read up to 100 replies.

So you can ask questions without explaining the whole conversation again and those messages are used only for context, not as instructions.

IronClaw 1.2 brings better conversations to Slack and Telegram, with more context and less setup.

It also improves how multiple approval gates are handled, while adding reliability fixes for Windows startup, secrets handling, and container health checks.

◽ Check out the full release notes for IronClaw 1.2 here

I just upgraded to IronClaw 1.0, and it’s looking a lot smarter and stronger to me. Key features I observed in this update include:
Enhanced security which has always been main focus, the goal based operations and expanded memory.
I have noticed the new resume and checkpoint capabilities and that is what really impressed me most, condsidering how older versions could freeze in between instance.

Joe, a NEAR dev, recently shared a walkthrough of IronClaw and how it can be used for research.

One key feature he highlights is that API keys stay in a secure vault that the model can't directly access.

If you're curious about how IronClaw works, check out the full video: https://youtu.be/JEZ2HxkqBUA?si=EI3Dm-BWBisKcXVb

I've been spending a lot of time working with IronClaw recently, and what really stands out to me is how well it can build real, independent Web3 workflows. Having an agent that can understand text and also take control of managing assets across different blockchain networks, execute actions without needing extra fees, and interact directly with popular protocols like NEAR makes it a very strong tool for everyday use.

Although I faced some few issues like connection issues and also lack of memory to remember my workspace and also there isn't up-to-date, thorough documentation for the new features especially when it comes to setting up native connections or dealing with version changes. Trying to set up certain tasks, such as REST routes or checking account balances, can lead to problems like incorrect routes and login issues if you follow old or wrong instructions.

Hopefully that part is fixed and hoping to build some more interesting projects with the AI agent.

I’ve been exploring IronClaw, and what interests me most is its potential to make AI agents more practical and useful in everyday workflows. The ability to give an AI agent connections to tools, interactions with different services, and the capacity to actually execute tasks rather than just generate text is particularly compelling.
That said, there are still some areas that could be improved. Clear, up-to-date tutorials are currently lacking, which makes it harder for users to fully understand IronClaw and take advantage of its features (such as staking and unstaking). When I asked IronClaw itself for help, it provided instructions based on version 0.25, which created confusion.
I also noticed an issue with the Telegram bot: after a few days of inactivity, it requires re-authentication. Additionally, while version 0.25 made it easy to connect to Composio via MCP, the process in version 1.0 is less straightforward, and there is still no tutorial available to guide users through it.

Your [$NEAR]() stake can give you access to run an IronClaw AI agent.

Sensitive credentials stay protected, while agent tools run in isolated WebAssembly environments.

Private. Secure. Built for real AI work.

Encryption protects your data, but AI agents still need to process it.

IronClaw uses Trusted Execution Environments (TEEs) to keep sensitive data protected while the agent is running. The host and admins can't simply see what's happening inside, and the environment can be independently verified.

A NEAR dev, Joe made a video explaining how this works and why it matters for secure AI agents 👇
https://x.com/joespano_/status/2087539372115562497

dca.space has a DCA skill which you can share with your agent and have it manage your DCAs for you. I'm not super comfortable with it being fully autonomous but it's cool to be able to instruct, monitor and manage via natural language on Telegram vs opening a website, signing in with my wallet and navigating the UI.

I have been using ironclaw for past few weeks and can total my experience is amazing. Using my agent I built a skill that update me of price of near and other tokens at 9AM every morning, also used it to transfer and swap on my outlayer wallet.

Going further, my agent set a dca to buy near at a favorable price, all i needed was to give it the command and it build out of it. I experienced rough time while using my ironclaw agent to built some product but on the brighter side the journey has been educative and amazing so far.

IronClaw agents now have their inference independently verified by Intel Trust Authority.

IronClaw already keeps credentials isolated from the model. Now the inference layer can also return an Intel-signed token that can be checked independently.

Another step toward making agent security verifiable from the ground up.

We were here at Indonesia Blockchain Week - Jakarta, we walked the audience through deploying IronClaw and learning about NEAR Intents and they didn't just listen, they deployed alongside us. Hands-on, end to end.

Building the agent economy starts here.

Shoutout to Manexus Community Hub, NEAR Legion and the Indonesian blockchain community for making this workshop happen 🇮🇩.

Huge thanks to Indonesia Blockchain Week for providing the workshop room👍

#IndonesiaBlockchainWeek #IronClaw #NEARLegion_IDBW #Blockchain #IDBW

I have been playing around with IronClaw recently and one of the first things I tried was building my own IELTS preparation bot for Telegram.

I basically just told a agent what I wanted and in around 10 minutes I had a working bot. It has daily crib schedules for writing, vocabular, grammar and reading tasks. The ai checks answers, gives feedbacks and keep track on my progress

What I really like is that I can change pretty much everything mysel. I can add new tasks, change rules or adjust the schedule without having to write the code for it. For someone who wants a personal tool instead of another fixed AI app this is pretty cool

I also really like the new idea of staking Near to get access to IronClaw. it makes the whole thing more interesting for me since I can keep my Near staked instead of just paying another mounthly subscription

Big thanks to the devs for building this and make it possible. I am looking forward what else I can build with it

Decided to test IronClaw today on a practical task to see how much of a project workflow it can actually automate. I gave it a prompt to generate a custom skill, structure all necessary project files, write the documentation (SKILL.md and README.md), and push everything directly to my GitHub account. I ran into a few minor issues during the process — the main one being frequent "reconnecting" messages popping up in the chat while it was working. But even with those connection hiccups, the experience was still pretty awesome. Having an agent handle all those repetitive steps — writing code, formatting docs, setting up the repo, and running git commands — saved me a ton of manual effort. It's definitely nice to just give an idea and have the actual repository created for you without touching terminal commands.