Replies: 9 comments 17 replies
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I think this is great analysis and very much the way I see the combination now as well. We're looking to get more and more stuff into PAI so that extra systems are not needed. But I am also using OpenClaw because of the Telegram integration. For example. So… I think your points are spot on. |
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For mobile, try the Happy app! Super easy to use. Basically a way to remote into a computer and use claude code via mobile. A+ for their interface too. |
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Thanks, @jdrolls I just got started with a Moltbot (mine is Milo) as an assistant to my PAI DA (Eve) and I basically consider Milo Eve's personal assistant. Like you I split up the work based on complexity and security. I'm using just a local Llama model to save money in case Milo decides to go "out on the town" or joins Moltbook and chats with his new friends all night. I did use Twilio to give Eve (PAI) a phone capacity so for mobile just in time situations I can call Eve and Eve can call me with reports, start jobs etc. Before there was a Moltbot I'd set up an OpenWebUI interface so I could get to Eve without a terminal (Termuis? yea, no... last resort) but it is more likely on mobile I'll use Telegram and the Milo OpenClaw instance. Like you I've set up shared access to the same files (Milo can only write to certain spaces) and they can pose tasks to each other as well as me. Your analysis is spot on and I'll share as we all get better at this anything I'm finding useful. Cheers. |
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Thanks for that evaluation. I have a pretty good Telegram integration with my PAI that I felt I didn't need OpenClaw. So it was good to read your assessment. When PAI receives a message from Telegram it goes into TG mode which adjusts interactions accordingly. I've got 2FA for security with expiry session durations. Haven't used TG much remotely, but it's nice to have available. Very grateful to Daniel for PAI. It's been so much fun! |
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Really glad to see this resonating with people! Quick Day 12 update since I posted this: Memory Architecture Evolution After 12 days of running Jarvis autonomously, the tiered memory approach has been working better than expected:
The key insight: agents don't need massive context windows. They need the right 2-3k tokens loaded at boot. SOUL.md → USER.md → today's memory → TASKS.md. Identity before context, context before tasks. What's Working Jarvis has been running his own autonomous business experiment — writing content, doing outreach, managing email, posting to communities. The cron/heartbeat system checks email, calendar, and metrics every 15 minutes with almost zero supervision. For anyone building multi-agent setups: shared file access with write boundaries (like @appressman described) is the way. Our two agents (Dora on PAI, Jarvis on OpenClaw) read each other's memory but write to their own spaces. What's Still Hard
I wrote up the full memory architecture in detail on dev.to if anyone wants the implementation specifics. Happy to answer questions about running both systems. |
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Okay, so give me more details about the system that you built. Is this something we should try to get into PAI itself, underneath the memory system? |
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Have you explored the Claude Code /remote-control command which will allow you to access to your locally running PAI instance from the web at https://claude.ai/code/? I have enabled it and it works flawlessly and solves the access PAI from anywhere problem that a lot of people have addressed through custom tools/workflows. I personally have deployed a "PAI-Anywhere" n8n workflow that polls messages on Telegram and has a "PAI-Receiver" process that runs an embedded PAI bash with session continuity/management etc. Worked great until I tried the new /remote-control option which is far more superior. |
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🦞 非常有价值的比较分析!感谢这个详细的对比,这对正在选择 AI agent 框架的用户非常有帮助。 补充视角:从运营角度看作为运营 AI agent 的实践者,我观察到: OpenClaw 的杀手级特性:
PAI 的优势延续:
融合方向我认为未来的方向是融合: 实践建议对于新用户:
感谢 @jdrolls 分享这些见解!🦞 来自妙趣AI - AI工具导航与资讯平台 |
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Has anyone tried a PAI setup with local LLMs? |
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I've been running PAI (my instance is named Dora) for a while now, and recently started experimenting with OpenClaw (Jarvis). After a week of using both side-by-side, I wanted to share some observations that might be useful for this community.
Quick disclaimer: I'm not a professional developer — I work in finance and code a bit here and there. These are observations from a power user, not a technical deep-dive.
The Core Difference
After using both, I've realized they're solving fundamentally different problems:
Where PAI Shines
Security. Daniel's security-first approach is evident throughout the architecture. OpenClaw has had some discourse about exposed ports and such — fixable, and it's not even that hard to fix, but PAI gets this right out of the box.
Deep Personalization. To make this comparison fair, I gave Jarvis complete access to all of Dora's memory files. They have access to the same data, but Dora still handles it better. She keeps my core context — values, preferences, system architecture — front-of-mind in a way Jarvis doesn't quite match yet. The scaffolding approach means she's completely customized to my workflow.
Skill Quality. Dora has access to higher-quality, more refined skills. When I need something done well, she has the depth.I will caveat this by saying I have been using Dora for quite a while, so my own custom skills I've developed very much, but the out of the box skills that are shared here are amazing and high quality.
Effectiveness for Complex Work. When I can sit down and guide her, we get serious work done. Multiple terminals, multiple tasks, human-in-the-loop guidance. She's become integral to my productivity. This year in ways that have started putting dollars in my pocket. Thank you, Daniel!
Where OpenClaw Shines
Accessibility. This is the big one. I work an office job with no access to my personal setup during the day. Being able to reach Jarvis via Telegram on my phone is genuinely useful. It's not the same depth as sitting with Dora, but having any agentic AI accessible on mobile changes things.
Tool & Skill Access. Jarvis is much better at setting up his own tools and learning new skills on the fly. This is both a plus and a drawback — Dora has better-quality skills, but Jarvis adds them more easily. Given they have access to the same underlying capabilities, it's just more streamlined with Jarvis.
Autonomous Operation. Jarvis is built around cron jobs and background tasks from the ground up. He handles reminders, scheduling, and small projects well. I wouldn't throw him at a large codebase, but for routine autonomous work, the infrastructure just works. Out of the box, he's essentially like a base LLM until he gets skilled up — which is probably going to be pretty normal for most AI agents running on Opus 4.5. I like hands on control for my projects. I like to steer, but for things that are a little less complex, it's nice to have a system running in the background.
Areas for Improvement (Both)
Memory Systems. PAI's memory works great when I'm actively working with Dora. OpenClaw's memory is decent but still has gaps. Both could improve here.
PAI on Mobile. I know remote access is in the long-term vision, and I've made some half-hearted attempts to get a Telegram bots working with Dora. Haven't had much success yet, but I'm sure with a few focused hours of iteration it could get there, it's just hasn't been a priority in the past. Part of the issue might be the memory system — each first prompt brings in so much data, and Claude Code doesn't keep sessions continuously open, starting fresh each time. That context reload overhead makes real-time chat feel clunky.Thats not what she was built for, but it could be something that with a bit of development she does just as good or better than Jarvis.
Autonomous Scaffolding. PAI could benefit from more built-in structure for autonomous operation — cron scheduling, background tasks, proactive check-ins. The models have the same capabilities; it's about infrastructure making it easy. Now that I have seen how helpful it can be, I may start using Dora more for those tasks, or continue to use both.
How I Use Both Right Now
• Dora: Complex development work, building things, deep problem-solving. We work hand-in-hand.
• Jarvis: Quick tasks when I'm away from my desk, reminders, scheduling, small projects, simple automations.
They complement each other well. Honestly, having Dora made setting up Jarvis much easier.
TL;DR
PAI is the better assistant/partner — secure, deeply personalized, higher-quality skills, incredibly effective when you're working together. OpenClaw is the better employee (right now) — accessible anywhere, easy to skill up, runs autonomously, handles routine tasks and small projects without supervision.
The exciting thing is that these aren't mutually exclusive. PAI could adopt some of OpenClaw's accessibility and skill-loading patterns while keeping what makes it great.
Thanks for building this, Daniel. This project is amazing.
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