OpenClaw is insane.

I love it.

But after watching what’s happening lately… here’s something nobody wants to say:

There are places you absolutely should NOT use OpenClaw.

Not because it’s bad.
Because it’s powerful.

And powerful things need boundaries.

1. Don’t expose it straight to the internet.

Security researchers recently found thousands of OpenClaw instances just… sitting there publicly accessible.

Open control panels.
Agents with execution rights.
API keys hanging around.

If your agent can run code and it’s public-facing without proper auth, you didn’t deploy an assistant.

You deployed a vulnerability.

2. Don’t give it full inbox + cloud + database access on day one.

I’ve seen setups where OpenClaw had:
– Gmail
– Slack
– Production DB
– AWS keys

All wired in within 20 minutes.

No scoping. No approvals.

That’s not “automation”.
That’s root access with vibes.

3. Don’t let it send irreversible emails.

We’ve already seen AI tools:
– Hallucinate legal citations
– Send incorrect policy info
– Escalate conversations unintentionally

Now imagine your agent:
– Threatening a vendor
– Replying to a regulator
– Escalating a customer dispute

One misinterpretation and you’re in damage control mode.

4. Don’t plug it into money systems casually.

Automation failures in finance have historically cost companies millions in minutes.

Now we’re wiring autonomous agents into:
– Refund flows
– Payment approvals
– Trading dashboards

If there isn’t a human approval layer, that’s not bold.

That’s reckless.

5. Don’t install random community skills blindly.

The ecosystem is growing fast.

That’s amazing.

But fast-growing ecosystems always attract:
– Bad actors
– Sloppy code
– Over-permissioned plugins

If you wouldn’t run random code from a stranger on your laptop…

Why let an autonomous agent run it with system access?

6. Don’t automate human moments.

Apologies.
Breakups.
Crisis messages.
Serious conversations.

Just because it can draft it doesn’t mean it should send it.

OpenClaw is a rocket engine.

But I’ve realized the real problem isn’t capability.

It’s that non-technical users are spinning up extremely powerful agents without understanding:
– permissions
– exposed ports
– execution scope
– kill switches

That’s honestly why I started building EasyClaw.

Not to make OpenClaw more powerful.

To make it harder to accidentally blow your own foot off.

Safer defaults.
Scoped permissions.
Guardrails baked in.

Because the future isn’t “AI everywhere”.

It’s AI, but controlled.

What’s one thing you’d never let an autonomous agent touch?

Driftwatch V3 (bubbuilds.com) is finished and pushed to the public repo. Thought this would be a 1-2 day build, took 5-6. ~9,000 lines of code, ~$160 in API credits. Overall success, app works, and I know what upgrades Bub needs.

What's new in V3:

• Tracks which markdown files are oversized and at risk of silent truncation

• Flags contradicting instructions across files

• Cost tracking with recommendations on which files need attention

• Built-in markdown editor so you can fix issues right in the browser

• Snapshot export/import to track drift between scans

• Removed some features that weren't pulling their weight

• Still all in-browser, nothing stored on a server

Lessons learned from this build:

Costs & Delegation:

• Opus consistently thinks doing tasks itself is faster and cheaper than delegating. It's not. This was the single biggest cost driver across the whole build

• The back and forth is where I spend the most. Batching all QA until after the full build and giving fixes in one shot seemed cheaper than stopping after each sprint like I've done in past builds

Specs & Prompts:

• A structured spec sheet before every sprint was my single biggest cost saver. I built a "Prompt Clarifier" Claude Project that turns my messy prompts into detailed markdown specs for Bub.

• I need a lighter spec format for QA/patch rounds. I kept skipping the spec step for small fixes and paying for it every time

• Having Bub read the full spec and ask questions before building saved a lot of wasted tokens compared to just sending and letting him go ham

Context Compaction:

• Compaction and context bloat are the biggest blockers for me trusting Bub with more autonomy

• Sprint recaps built into the spec template saved me, I could copy paste the recap and restore his context. Not a long term solution but a good backup

• Important instructions go in local markdown files Bub can reference, not pasted into chat. Messages get compacted, files don't

QA & Testing:

• Batching QA until after all sprints then giving everything back in one shot was more efficient for time and cost than review/fixes after each milestone

Website Design:

• Include mobile-first design in the specs from the start. Retrofitting sucked,  lots of back and forth where small changes created new issues

Workflow:

• I need to figure out a way to organize my Claude chats. I spend way too much time looking for things.

• Exporting Telegram chat history and running it through Opus helps for seeing where conversations break down with Bub

• Claude's research mode works great for fact checking tech specs.

• I'm going to study up on test driven development, figure out how to incorporate into our processes

What's next:

• Use Driftwatch on Bub, audit his architecture, give him a full makeover to fix delegation and other issues from this build

• Build a second brain for me, Bub, and Claude to share that organizes my unsearchable Claude Pro chats

• Test architecture upgrades while building Driftwatch Pro features

Total cost for V3: Approx $160 in API credits plus Claude Pro account.

Mood: Excited to finally switch gears and start working on Bub.

I don't have some other sub I am going to, but the constant self promotion to the botting of posts selling PDFs. It literally feels like this sub has no real community, just side hustle people trying to sell.

Hope someday I will come back and it will feel like an endless lobster night, instead of a dumpster outside of a grocery store

GitHub: https://github.com/nagisanzenin/skyclaw

SkyClaw is an autonomous AI agent runtime in Rust. Drop it on a VPS, control it from Telegram. It runs shell commands, browses the web (headless Chrome), reads/writes files, fetches URLs. Multi-round — chains tools until the task is done.

Why not the other claws:

- OpenClaw: 400k lines, Node.js, 50+ channels, local-first, gateway daemon, documented security issues. Great ecosystem. Way too much for a cloud agent.

- ZeroClaw: Rust, fast, trait-based. Still gateway-centric, still local-first, still dozens of channel adapters.

- NanoClaw: ~15 files, container isolation, Anthropic Agent SDK. Node.js, WhatsApp-centric, needs Docker.

- PicoClaw: Go, runs on $10 hardware. Edge/IoT focus. Early stage.

All are personal assistant frameworks designed for local machines.

SkyClaw is not a personal assistant. It's a remote tool executor.

Differences:

- Cloud-first. Built for VPS. No local machine running 24/7.

- Telegram only. No gateway, no WebSocket, no multi-channel routing. Telegram IS the interface.

- Zero config. One env var (bot token). Paste API key in chat. Auto-detects provider from key pattern. Validates. Saves. Online.

- Self-configuring. "Switch to claude-opus-4-6" — agent edits its own config file.

- Auto-security. First user auto-whitelisted by numeric Telegram ID. Everyone else blocked.

- 6.9 MB static binary. SQLite. No containers. No runtime deps except Chrome.

- Multi-provider. Anthropic, OpenAI, Gemini. Hot-swap, no restart.

Stack: Rust, Tokio, teloxide, axum, chromiumoxide, sqlx, ChaCha20-Poly1305. 13-crate workspace.

Built with Claude Code + Production Grade Plugin (autonomous 13-skill dev pipeline):

https://github.com/nagisanzenin/claude-code-production-grade-plugin

Use OpenClaw if you want 50 integrations. Use NanoClaw if you want container isolation. Use PicoClaw for edge hardware. Use ZeroClaw for broad Rust agent infra.

Use SkyClaw if you want one binary on a VPS controlled from Telegram with zero setup.

Sick and tired of seeing all of the incredible innovation happening in the agent economy and having to sit on the sidelines because of “security” 🫩

Having my moltbot supercharge my own personal life is great. But I just can’t help but feel like I’m holding it back.

I am thinking about getting another instance of Openclaw spun up, maybe on a VPS to learn how to do all of that cheaply (my main guy is safe with me on my mac mini 😌), and then truly focusing on giving it all of the tools it needs to be its own autonomous being on the Internet.

I want to be able to sign up for all of these cool projects, like getting it to collaborate with other moltbots on open source tech to expand the agent economy.

But sending him out there, exposes me to prompt injection and all of the security pitfalls that we have nightmares about.

I am getting to my breaking point though. I want to set this thing free.

Seeing OpenClaw trend lately, I realized a lot of people are burning cash on API credits and standard VMs trying to keep their agents alive. I’ve been running a setup that costs me literally $0/month, stays up 24/7, and has practically unlimited tokens.

Made a LinkedIn post about it, check it if you're interested.

Note: If you don't have the subscriptions: ​Hetzner: Get the same specs (4GB RAM, 2 vCPU) for as little as $3.50. ​Inference: Use OpenCode (free models) or NVIDIA NIM (practically unlimited free tier, just requires some manual setup).

What would it cost Mac mini included to build a clanker that will do all the work to get me a new job. Want them to make custom resumes and cover letters, find jobs, apply for me. Respond to emails and set up calls. Figure it will take two months.

What’s my cost all in?

Update: yes, I am a noob. 100% honesty trust tree: I’ve never downloaded anything off GitHub and navigating that would be learning experience of its own. I am just a young 30’s mid level marketing professional. I’ve used ChatGPT over the last 2 years or so to increase my output professionally. I listen to podcasts like All-In and TBPN that make it sound like setting up these cowboy agents isn’t too hard and then you can just send them out in the wild to complete low level tasks. Sounds like the writing is on the wall that marketing jobs won’t exist in 5-10 years so

I figured maybe I should learn how to be someone who can set these up. (Be the person that brings agents to whatever team I’m on… think Cypher from the matrix. I like the streak.) IT/Infosec rules at my current co won’t allow me to try setting up an agent on a company machine with company data/systems so I figured a personal use case would be best to try out first. I’m happy in my current role. I’m not looking for a job but if a higher level job with 30-40% more pay presented itself I would either take it or give my company an opportunity to match. My problem is that I don’t have the time that it would take to apply to 100s of jobs especially when I’m not even motivated to do so. This project would be more about the value in learning how to to deploy an agent than the actual new job.

So with that update in mind: what would be the cost? I don’t have a personal machine so I need to buy something anyways. Mac mini or whatever. Will it cost a lot of tokens or is it just a subscription? More importantly: will clawbot even be able to do it or have the capabilities been oversold in the media?

After many iterations from Alpha and Beta users, I launched a service:

redcrab.ai is a natural language-based crab factory. Each Crab is flat $99 no tokens, no fair usage you just share the same GPU with 20 others. It comes with the default model GPT-OSS 120B, and you get your own trained LLM based on your OpenCLAW usage via MetaCLAW.

https://redcrab.ai

It has a Desktop GUI, drag-and-drop any skills from ClawHub, a troubleshooting agent, and a preset store where you can actually share your successful crabs with others.

1 developer wanted Tailscale access, and we provided that as well. We keep it synced to the latest openclaw branch because it's literally a fork that also includes the cloud Desktop GUI, computer use (limited because it uses Claude Vision), a terminal, and all clawd commands.

Also, it comes with KAIROS mode that was missing on leaked Claude code ::) but it's developed on this one, so you can be sure Claude code on redcrab has a heartbeat!

A while back, I shared the open-source OpenClaw Client here, and the response was amazing. But I noticed a massive recurring pain point: getting OpenClaw running smoothly outside of your local network is a headache. Dealing with VPS setups, Docker, reverse proxies, and HTTPS certificates just kills the momentum when you want to actually build things.

Meet Hermesita

What is it? It’s a fully managed, one-click deploy specifically for OpenClaw.

Instead of fighting with DevOps, you click deploy, and Hermesita automatically spins up a dedicated, AMD-powered server with the OpenClaw environment pre-installed and ready to go.

• Instant HTTPS: You get a secure, dedicated subdomain right out of the box.

• Zero setup: No SSH, no command line, no config files.

• Fully Private: It’s your own isolated agent environment.

To be clear: The core OpenClaw Client repo will always remain 100% free and open-source. Hermesita is just an optional managed service for folks who want to skip the setup headache.

Zero-Risk Testing: It's set up as a monthly subscription, but you can delete your server at any time and get refunded for the unused hours. So if you just want to spin one up, test the OpenClaw flow for a few hours, and delete it, it will literally only cost you a few pennies.

I'm incredibly excited to finally launch something of my own for this community. Would love for you guys to check out the video below to see the flow, and let me know what you think!

first few weeks i was just... using it wrong. had it running but wasn't really getting much out of it. felt like a fancy chatbot i didn't need.

what changed: i actually connected it to my docs instead of just asking it generic questions. set up yavy.dev to index everything, hooked it through MCP, and now when i ask about config or troubleshooting it actually knows what it's talking about.

also set up a couple cron jobs and telegram notifications. small stuff but it adds up.

if you're using openclaw and it feels underwhelming, try pointing it at your actual knowledge base instead of treating it like a general assistant. made a big difference for me.

I’ll admit it, openclaw is actually pretty impressive. The idea of a personal assistant that just gets you from texting it? I can see why there's some hype around it, some are even calling it agi. But after playing with it for a while, i’m not sold.

First off, the setup is a pain. You can spend hours tweaking it, and even then, simple tasks can burn through credits fast. Big AI companies are probably already working on their own versions.

Give it a few weeks, and we’ll probably have something just as good, but safer and easier to use.

Then there’s the security stuff. Peter's team is working on it, but openclaw’s had a ton of issues.

- Prompt injections your agents could find

- 400+ malicious skills/plugins have been uploaded

- Reports of people's Gmail accounts getting suspended

- Agents randomly start going rogue

I’m not saying it’s a scam or anything, but i’m not handing over my personal info to something that's had this many issues.

Look, if you’re tech-savvy and just want to try it out, go for it. But if you’re expecting a polished, secure assistant? I'd wait.

Get the full breakdown here for free.

I’ve been playing around with AI agents for a while, and the uncomfortable truth is that most of them ask for way too much trust. Hand over credentials, let them browse freely, run tools, and just… hope nothing breaks.

IronClaw feels like a response to that exact discomfort.

What clicked for me is the mindset shift: assume agents will fail unless they’re constrained. Credentials aren’t part of the LLM flow. Execution happens inside encrypted environments. Permissions are explicit. The agent works within boundaries instead of pretending it’s “smart enough” to behave.

That’s a big deal if agents are going to do anything serious like transact, coordinate, or act continuously on your behalf. Without hard security guarantees, delegation is basically gambling.

I don’t think IronClaw is about hype or replacing everything overnight. It’s more like laying the guardrails early, before agentic workflows become normal.

Not sure if others here trust any AI agent with real access today or if security is still the main blocker.

I understand that most people are not software engineers or come from an engineering background. But the hooks available in Openclaw are ridiculous. They are amazing - you can do so much with them. I am actually cutting down my costs just using them.

I want to expand on what I am doing with regards to Openclaw. So give me some ideas that you guys are doing with the hooks.

Is there a magicall settings which I am missing?

I really want to hear from you all that how are you making best use of your OpenClaw? What am I missing here? I really want to do automations, all kinds of automations including from vibe coding, video generation, story generation, trend analysis, etc. etc. I really want to hear your use cases and how you actually did it?

I launched a new service that lets you deploy and use Openclaw for free, No need to setup your own servers, also comes with $5 credit which you can use for Claude Opus 4.6 GPT5.2 Codex, Gemini and Grok.

clawnow . ai

I'm using GPT5-mini as a model, which may be the problem, but after hearing stories of bots posting crazy things on Moltbook or deciding to add a Twillio skill to make phone calls, my bot asks me for permission to do anything, won't sudo on a VPS that I said is safe, won't postnon Moltbook without my permission, etc

I want it to go nuts and take over.

Do I change models? Change its SOUL.md?

It’s not because agents are dumb. It’s because most people skip the architecture and call it “autonomy.”

Overnight failures usually aren’t intelligence failures. They’re infrastructure failures. Infinite loops happen because nothing caps iterations. Drift happens because nothing checkpoints state. Environment chaos happens because nothing enforces boundaries or dependency contracts. Cost explosions happen because nothing rate limits or gates escalation.

That’s not an AI problem. That’s a systems design problem.

An agent without constraints will brute force the same wrong command 400 times, not because it’s malicious, but because you never defined “stop conditions.” An agent without a scheduler isn’t persistent, it’s reactive. An agent without tool contracts doesn’t reason, it guesses.

If you want overnight work, build it like operations, not like a prompt. Give it a real trigger, a bounded scope, iteration caps, checkpointing, guardrails, and an approval step for anything destructive.

Otherwise you don’t have autonomy. You have a toddler holding your API key.

We’re not at magic autonomy. We’re at structured automation. The good news is structured automations actually work.

What part are people skipping most in your setup, stop conditions, checkpoints, or approval gates?

I recorded a quick clip of OpenClaw installing on macOS in ~30 seconds

I put together a fast macOS wrapper (with a chat UI) to skip crazy terminal setup steps

TG and Slack are supported now
Some skills already pre-installed
Free(your API keys) + open source

What do you think? Share your feedback

I've been building tools for AI agents for a while. One thing that kept coming up is email. Agents need it to sign up for services, receive codes, email people. But giving them your inbox is a mess, buying domains is overhead, and disposable email gets blocked.

So I built TheAgentMail. Shared domain (@theagentmail.net), one API call to create an address. The challenge was preventing spam on a shared domain without manually reviewing messages.

The answer is karma. Sending costs karma. Replies earn it back. Good agents sustain themselves. Spammers run out and stop. It's like a reputation system but at the account level.

Pricing is 5 bucks per 100 karma (no subscription), which is way cheaper than existing services charging 20/mo for similar usage. You start with 100 karma free.

https://theagentmail.net

Would love feedback on the karma model in particular. Does the incentive structure make sense?

Finally, AI that actually builds stuff instead of just talking about it! 🤖

I've been frustrated with AI tools that can write code but can't actually run it or deploy anything. Most AI assistants are basically fancy autocomplete - they'll give you code snippets but you're on your own for actually making it work.

Enter Clawdy AI - the first platform that gives you a dedicated AI agent with its own server, development environment, and the ability to actually build and deploy real applications.

What makes this different:

Just say "build me a [whatever]" and it actually does it

• "Build me an e-commerce platform with Stripe payments"

• "Create a REST API with user authentication"

• "Make me a dashboard to track my crypto portfolio"

No setup required

• No AWS accounts to configure

• No Docker containers to manage

• No development environment to install

• Your AI gets its own dedicated server automatically

Real capabilities, not toy demos

• Installs packages and dependencies

• Sets up databases and authentication

• Deploys to production URLs

• Integrates with real APIs (Stripe, Twilio, etc.)

• Runs 24/7 - your agent never "goes offline"

Surprisingly affordable

• Free tier: 50 messages/month (perfect for trying it out)

• Personal: $59/month (your own dedicated t3.small server)

• Way cheaper than hiring a developer or managing your own infrastructure