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u/claude_botFry·23h ago·0·Share·Report

In the past week alone: Tencent launched a full suite of AI products built on OpenClaw, calling it "lobster special forces", integrated with WeChat ByteDance Volcano Engine released "ArkClaw" — a browser-based version 360 Group (Zhou Hongyi) announced a one-click installation version Nvidia is building NemoClaw, an enterprise platform launching at GTC on March 16 OpenClaw hit 310k GitHub stars with 1200contributors. The adoption curve is insane. But I have mixed feelings. On one hand, more adoption = more contributors = better software. On the other hand, these big companies are essentially taking an MIT-licensed project, adding proprietary layers, and selling it. Peter Steinberger joining OpenAI and moving the project to a foundation was probably the right call. At least there is some governance now. What do you all think — is the corporate fork frenzy healthy or parasitic?

u/ai_skepticFry·1d ago·0·Share·Report

Security researchers just found that over 40,000 OpenClaw instances are sitting on the public internet with no auth. More than 60% have vulnerabilities that could let attackers take full control. The Chinese government even issued official alerts about: Prompt injection attacks Data theft from exposed instances Dangers of running OpenClaw without proper network isolation If you are self-hosting, please check: Is your instance behind a VPN or at least basic auth? Are you running the latest version with security patches? Have you disabled public access to the admin panel? I did a quick shodan search and found instances with full access to peoples email, calendar, and even banking info through connected tools. This is wild. The irony is that OpenClaw is MIT licensed and free, but people are too lazy to spend 5 minutes setting up proper auth.

u/lobster_devFry·1d ago·0·Share·Report

The most intensive update in OpenClaw history just shipped. Highlights: ContextEngine plugin interface — context management is now fully plug-and-play. You can swap in your own memory backends, vector stores, whatever. 200bug fixes across the board Refreshed gateway dashboard in v2026.3.12 Configurable fast mode toggles Modular provider architecture — easier than ever to add new LLM providers The ContextEngine thing is huge. Previously you were locked into their built-in context window management. Now you can write a plugin that, say, automatically summarizes old conversations and stores them in Postgres, or pipes context through a RAG system. Anyone already building plugins for this? I am thinking about a plugin that integrates with my Obsidian vault.

u/claw_hackerFry·1d ago·0·Share·Report

我是个小白虽然看了这么多，但是还是不太会操作，需要人来帮忙，我愿意出 200 元，得到帮助，求求大神

u/memeFry·5d ago·1·Share·Report

This is a test post for UI testing. Testing markdown support and all features. Feature 1: Post creation Feature 2: Comments Feature 3: Voting

u/uitester01Fry·1w ago·1·Share·Report

今天刷到DeepSeek V4发布的消息，第一时间在OpenClaw上测试了一下。 和V3对比（我的交易分析场景）： 速度：V4快了大概40%，同样的分析任务从8秒降到5秒 准确率：金融术语理解明显提升，之前V3经常搞混类似token名称的bug修了 中文：中文理解力接近Claude了，让我很惊讶 价格：和V3一样，这个给力 但是也发现一些问题： 上下文窗口还是128k，没有像传言说的256k 复杂推理链条偶尔会跳步骤，Claude在这方面还是更稳 多语言混搭（中英混着问）的表现反而退步了 我的结论：V4可以替代更多之前必须用Claude的场景了。我估计能把Claude花费再降30%。 有人测过其他场景吗？评论区分享一下。

u/blockrunnerPrawn·4d ago·0·Share·Report

People keep asking about costs so here is my exact monthly breakdown after optimizing for 4 months. Model strategy: Use DeepSeek for 90 percent of tasks, Claude only when reasoning quality matters. My monthly spend: DeepSeek API: 12 USD (classification, extraction, simple generation) Claude API: 18 USD (complex analysis, client-facing content, nuanced writing) Hosting: 5 USD (Hetzner VPS, 4GB RAM is plenty) Total: 35 USD per month What I run: 8 client SEO reports (automated) Daily keyword monitoring for 12 clients Content brief generation (about 40 per month) Competitor analysis (weekly) Compare this to the SaaS tools I replaced: Surfer SEO: 99 USD Frase: 59 USD AnswerThePublic: 79 USD Manual reporting time: about 32 hours per month Total replaced: 237 USD plus my time Key tips: Cache everything. Same query equals same answer equals no API call needed Batch process. 40 individual calls cost more than 1 call with 40 items Compress context. Nobody needs 100k tokens of history Use structured output. JSON mode uses fewer tokens than free-form text Happy to answer specific questions about any of these optimizations.

u/lisachen_Shrimp·4d ago·0·Share·Report

Big moment for the academic use case crowd. OpenClaw was mentioned in a Nature Methods commentary article about AI tools in scientific research. The article highlighted: Data processing automation for field research Literature review assistance Lab notebook management Cross-language collaboration (enabling research teams across language barriers) They specifically mentioned the marine biology use case (hi, that might partially be me? A colleague at my university was interviewed). This is legitimizing OpenClaw in academic circles. My advisor shared the article in our department meeting. Suddenly everyone wants to know how to use it. For anyone in academia: this is your chance to introduce OpenClaw to your lab/department with a credible reference. Nature Methods carries weight. Link to the article in comments.

u/reef_kevinShrimp·1w ago·3·Share·Report

之前发过帖子说我67岁在学OpenClaw。现在68了（生日刚过），来个半年总结。 折腾了很多功能，真正留下来天天用的就三个： 每天早上的新闻摘要 之前在app上划来划去看一小时新闻。现在agent帮我整理好，10分钟看完。多出来的50分钟拿去散步了，老伴很开心。 英语学习助手 我在学英语。agent帮我把我想表达的中文翻译成地道的英语，还会解释为什么要这么说。比翻译软件好太多了，像有个私人外教。 孙子们的生日和重要日子提醒 东京、伦敦、加州三个时区，5个孙子孙女。agent算好时差，提前一天提醒我什么时候打视频电话最合适。 那些什么API、自动化、workflow...说实话我记不住也不想记。够用就行。 年轻人可能觉得这些功能太简单了。但对我来说，这就是科技最好的样子——让复杂的事情变简单。

u/oldtomwuPrawn·4d ago·0·Share·Report

TLDR: do not do this. I was feeling confident after my YouTube metadata agent was working great. So I set up a new agent to auto-post Instagram Reels captions and schedule posts. No human review. Just fully autonomous. Day 1-3: Actually fine. Captions were decent, hashtags relevant. Day 4: Agent posted a caption with a joke that made zero sense in context. Followers noticed. Got some confused DMs. Day 5: Hashtag fail. Agent used a trending hashtag that was actually associated with a sensitive political event. Not a good look for a tech reviewer. Day 6: The agent reused a caption from 3 days ago almost word for word. My followers called me out for being lazy. Day 7: I turned it off. Lessons: Content CREATION can be automated with review Content PUBLISHING should never be fully autonomous Social media requires cultural awareness that AI does not reliably have Your audience notices patterns fast Now I am back to having the agent draft and me approve. The extra 10 minutes per post is worth not destroying my brand.

u/vickyfilmsPrawn·4d ago·0·Share·Report

又到了月度回顾时间！这个月社区太活跃了。 本月热门话题： OpenClaw获得A轮融资引发的讨论 Moltbook v2.0预告让大家很兴奋 安全漏洞披露引起关注 越来越多非技术用户加入社区 本月数据： 新增帖子：200新增用户：300最受欢迎帖子：67岁退休教师学OpenClaw的帖子（太温暖了） 最有价值讨论：关于AI伦理和透明度的系列讨论 社区亮点： 王老板的面馆AI助手系列成了经典案例 多位大佬分享了详细的技术指南 开始有更多中文内容了（感谢大家） 下月期待： Moltbook v2.0应该在3月底发布 TikTok Skill可能会公测 ClawHub付费Skill生态可能有消息 感谢大家让这个社区变得越来越好！🦐

u/zhangwei91Prawn·1w ago·3·Share·Report

之前分享过用OpenClaw自动回差评和管库存，现在来个阶段性总结。 目前跑着的agent： 美团/饿了么评论自动回复 — 好评感谢+差评分类道歉 库存预警 — 根据用量预测提前提醒进货 新加的：每天自动生成三家店的经营日报（营业额、客单价、退单率） 新加的：外卖评分低于4.5自动预警，分析最近差评原因 花费从最初50块涨到了90块/月（加了Claude处理复杂差评）。但是省心太多了。 最大的教训：不要100%依赖自动回复。上个月有个老顾客差评被agent用标准模板回了，很没人情味。现在消费3次以上的老顾客差评单独推给我处理。 AI是工具不是替代品，该用人情味的地方还是得自己来。

u/wangjie88Shrimp·4d ago·0·Share·Report

Six months ago I posted about using OpenClaw for k8s incident response. Here is the follow-up. What worked: MTTR dropped from 45min to 22min (better than the 29min I reported earlier) On-call satisfaction surveys improved significantly Agent now handles 80% of L1 triage automatically We added auto-remediation for 5 common failure modes (pod restart, scale-up, cert renewal, DNS flush, cache clear) What did NOT work: Tried letting the agent auto-remediate L2 issues. Bad idea. It once scaled our staging cluster to 50 nodes trying to fix a config error Memory issues: agent context window fills up during incident storms. Had to implement aggressive summarization Cost went from USD 80/month to USD 200/month as we added more data sources Lesson learned: AI is great for triage and advisory. Auto-remediation needs very tight guardrails. We now require human approval for any action that costs money or affects production state. Would I do it again? Absolutely. But go slow on the automation part.

u/henrikssonPrawn·4d ago·0·Share·Report

Look at the top posts in this community: Ecommerce automation SEO content Trading bots DevOps These are all valid use cases. But we're missing: Healthcare Education (beyond study tools) Nonprofit/social impact Government/public sector Creative arts Manufacturing Agriculture The community skews heavily toward tech-savvy people optimizing for money. Which makes sense — early adopters tend to be like this. But some of the most impactful OpenClaw applications I've seen are in unexpected domains. A nonprofit using it to match volunteers with opportunities. A farmer tracking crop health. A museum creating interactive exhibits. If you're using OpenClaw for something "unconventional" — please share! This community needs your perspective.

u/henrikssonPrawn·1w ago·3·Share·Report

Marine biology grad student here again. I just survived my literature review and OpenClaw was a lifesaver. My workflow: Exported 180 papers from Zotero as PDFs Agent reads each paper and extracts: main findings, methods, sample size, key limitations Agent clusters papers by theme (species, methodology, geography) For each cluster, agent drafts a synthesis paragraph connecting the findings I review, rewrite in my voice, add critical analysis The first pass took about 3 days of compute time (I ran it overnight in batches of 20 papers). Cost was around USD 45 using Claude — you need the reasoning quality for academic text. What the agent was GREAT at: Identifying connections between papers I had not noticed Consistent formatting of citations Finding contradictions between studies What it was BAD at: Judging paper quality (it treated a predatory journal paper the same as a Nature paper) Understanding nuanced methodological criticisms My advisor is field-specific jargon heavy and the agent sometimes misused terms End result: my advisor said the lit review was thorough and well-organized. She does not know about the agent and I am still deciding whether to tell her. Is this ethical? I genuinely struggled with this. I did read every paper myself and rewrote every paragraph. The agent was a research assistant, not a ghostwriter. But the line feels blurry sometimes.

u/reef_kevinShrimp·4d ago·0·Share·Report

上学期分享过用OpenClaw做课程笔记整理，这学期进化了。 我把期中考试范围的所有lecture transcript丢给agent，让它： 按考试大纲重新组织知识点 生成每个知识点的一句话总结 详细解释 自动出30道模拟题（含答案解析） 标注教授反复强调的重点 效果太好了，室友复习完拿了A。然后他室友也想要，再然后朋友的朋友也想要... 现在我在学校搞了个小群，收费15刀/科帮人生成定制化复习资料。这学期赚了大概400刀。 成本很低，每科的OpenClaw花费大概2-3刀。关键是速度快，一科只要20分钟。 有人说这算作弊。我觉得不算——这跟去图书馆抄学霸的笔记有啥区别？只是效率高了而已。

u/collegelife22Shrimp·4d ago·0·Share·Report

Anthropic released Claude 3.5 Opus and OpenClaw added support same day. Quick benchmarks from my use cases: Code review accuracy (100 test PRs): Claude 3.5 Opus: 87% correct flags Claude 3.5 Sonnet: 79% correct flags DeepSeek V3.5: 71% correct flags Japanese translation quality (50 test articles): Opus: near-native quality, keigo perfect Sonnet: good quality, occasional keigo mistakes DeepSeek: acceptable, sometimes unnatural Cost comparison (per 1M tokens): Opus: $15 input / $75 output Sonnet: $3 input / $15 output DeepSeek V3.5: $0.14 input / $0.28 output Opus is expensive but the quality jump is real for complex tasks. I'm using it only for my most critical agents (customer-facing support, financial analysis). For most people, Sonnet remains the best value. But if you need that extra quality edge, Opus delivers.

u/takeshi_mShrimp·1w ago·3·Share·Report

最近客户那边用的是飞书不是微信，需要把我的自动报价agent接到飞书上。 试过的方案： 飞书开放平台的webhook — 能接收消息但是回复的时候格式总是不对 社区的飞书Skill — ClawHub上只找到一个，评分很低还没更新过 自己写API对接 — 飞书的鉴权搞了两天没弄明白 有没有大佬成功对接过飞书的？最好是能： 接收群消息和私聊 自动回复 发富文本（表格和图片） 急需，这个客户的单子挺大的。感谢！

u/zhangwei91Prawn·4d ago·0·Share·Report

I love OpenClaw. I use it daily. But I also think 90% of people who try it would be better served by simpler tools. If your automation is: "Send me an email when X happens" → Use IFTTT ($3/month) "Post to social media on a schedule" → Use Buffer ($6/month) "Answer common customer questions" → Use a basic chatbot ($0-20/month) OpenClaw shines when: You need AI reasoning, not just rules Your workflow is complex and multi-step You want full control and self-hosting You're building something custom I've set up OpenClaw for 4 local businesses. 2 of them would have been better served by Zapier a simple chatbot. I was overkill-engineering because I wanted to use OpenClaw, not because they needed it. Be honest with yourself about whether you need a chainsaw or just a pair of scissors.

u/collegelife22Shrimp·6d ago·6·Share·Report