After using OpenClaw for over two months, I keep getting the same question: is it overhyped? A post from Miles Stoer caught my eye this morning — he argued that most people shouldn’t use OpenClaw and that he’s moved his workflows to Claude Code instead. So I wanted to give you my honest, unfiltered take on where OpenClaw actually shines and where it falls short.
The Short Answer: It’s Not Overhyped, But It’s Not For Everything
Let me be real — I don’t use OpenClaw to run my life. I don’t let it read my emails, manage my calendar, or handle scheduling. There’s still roughly a 2-5% chance it’ll mess things up, like getting dates wrong or hallucinating details. That’s just the nature of AI agents right now, and it’s a point that TechCrunch recently echoed in their piece questioning whether OpenClaw lives up to the buzz. Some AI experts have pointed to its complex setup requirements and high computational demands as reasons for skepticism.
Instead, I let OpenClaw handle tasks that are time-intensive, repetitive, and where mistakes aren’t catastrophic. That’s the sweet spot.
Where OpenClaw Actually Excels: Daily Briefings and Cron Tasks
The thing OpenClaw does better than almost anything else is recurring daily tasks. I have it generate a daily briefing presentation for me every morning — it just runs automatically via cron jobs, no prompting needed. I wake up to a full rundown of what’s happening in the crypto and AI space, complete with actual quotes, linked tweets, and sourced data.
This didn’t happen overnight though. Over time, I refined the instructions to make sure it wasn’t gaslighting me. Early on, it would flat-out lie about video view counts or make up restaurant locations. My fix? I told it to always include source links, and I even set up a sub-agent to fact-check everything before the briefing gets delivered. These tweaks drastically reduced the slop and made the output genuinely useful.
OpenClaw’s architecture is actually well-suited for this kind of work. Since it gained popularity in late January 2026 thanks to its open-source nature and the viral Moltbook project, the community has built out robust cron scheduling and monitoring capabilities. Tasks that need to happen daily, that benefit from memory across sessions, and that can be iteratively improved — that’s where OpenClaw is in its element.
Content Ideas and Creative Bouncing
I also have a second bot that scans trending videos and gives me daily intel on content opportunities. When I talk back to it and say “here’s what I’m interested in, suggest some video ideas,” it’s genuinely useful as a brainstorming partner.
The key insight here is that none of this is mission-critical. If the bot suggests a bad video idea, nothing breaks. I can accept or reject its suggestions freely. It’s low-risk, high-reward automation — and that’s the mindset you need when working with AI agents in 2026.
I’ve even had it scan through my old videos to add referral codes I’d missed, then save the process as a reusable skill for future use. Setting up skills in OpenClaw is honestly one of the most important things you can do to get real value out of it.
Where OpenClaw Falls Short: Don’t Trust It With Your Life
Here’s where I have to be honest about the limitations. We had an incident on our team where OpenClaw randomly messaged Ron’s girlfriend. Just out of nowhere. That’s the kind of thing that happens when you give an AI agent too much access without proper guardrails.
I don’t trust OpenClaw enough to let it into my Mac or manage my personal communications. And I think that’s exactly where the “overhyped” perception comes from — people install it on their local machine, give it broad access, and then get disappointed when it can’t flawlessly run their entire digital life. As CNBC reported, some experts have criticized OpenClaw’s complex installation and the gap between expectations and reality.
The way I see it, OpenClaw is like a $500-800 virtual assistant from a developing country. They can handle rough tasks, they have some coding skills (which is a huge bonus), but they make mistakes 2-5% of the time. You wouldn’t trust them with mission-critical work — that’s what your executive assistant is for.
OpenClaw vs Claude Code: Different Tools for Different Jobs
Miles’ original post suggested using Claude Code instead, and honestly, I use both. Claude Code is fantastic for programming tasks — it excels at parallel task execution, deploying sub-agents, and agent orchestration. As DataCamp’s comparison puts it, if your main use case is programming, Claude Code is the way to go. If you need a general-purpose assistant, OpenClaw is the better route. One comparison I saw described it perfectly: it’s like comparing a Swiss Army knife to a surgical scalpel.
I actually plug my OpenClaw into Claude as its language model, but Claude Code is even better at leveraging Claude’s capabilities for building systems. If you want to build something fun — like the mini-games I’ve been making — Claude Code will get you there faster. But it takes 2-3 weeks to really learn, and it’s a bigger scope project.
My Setup Recommendation
If you’re going to use OpenClaw, here’s my advice: run it on its own virtual private server, not your local Mac. The open ports let you directly access files, share presentations with friends, and browse dashboards from anywhere. Letting it build dashboards and visual presentations with coding capabilities will dramatically improve your experience.
And most importantly — understand what level of “employee” your AI agent is. Don’t try to build your entire life around it. Delegate the right tasks: repetitive daily work, content research, data monitoring, and creative brainstorming. Keep the mission-critical stuff in your own hands, at least for now.
I genuinely believe that in about six months, we’ll get to the point where these agents can function as true executive assistants. But we’re not there yet, and pretending otherwise is what leads to the “overhyped” label. Use OpenClaw for what it’s good at, and you won’t be disappointed.
Michael Gu
Michael Gu, Creator of Boxmining, stared in the Blockchain space as a Bitcoin miner in 2012. Something he immediately noticed was that accurate information is hard to come by in this space. He started Boxmining in 2017 mainly as a passion project, to educate people on digital assets and share his experiences. Being based in Asia, Michael also found a huge discrepancy between digital asset trends and knowledge gap in the West and China.