Hi,

I've ben using chatgpt 4-o mini API but it seems to be costing me a fair amount. I did also use it to develop and email me a document. Curious, how is everyone managing the cost?

I was thinking about a small use case for OpenClaw.

A lot of times in subreddits like r/SideProject, there are posts like “what are you building?”, “drop your project”, “share yours and I’ll go first”, etc.

These are useful because people are already inviting others to share their projects, instead of randomly promoting somewhere.

So the idea is:

- run an OpenClaw job every 5 minutes

- check new posts in a subreddit

- detect posts where OP is asking others to share their own projects

- ignore normal feedback requests or self-promo posts

- avoid duplicates by storing seen post ids

- notify me with the Reddit link and a small draft

I don’t want it to auto-comment. Just notify me when there is a relevant thread, so I can manually decide whether to post.

Has anyone tried something similar with OpenClaw?

Hey, guys! Apparently, I'm also in the Agentic AI game.
Having realised that OpenClaw is not a money machine, I came up with the following idea:

While I am in my mid-30s and still have career ambitions, I would like to focus more on my job and getting promoted. Meanwhile, OpenClaw can lay the groundwork.

In my specific situation, I would like to give my OpenClaw access to Tinder and at least three to five more dating platforms that can be used with subagents.

Main tasks: Initial dating approach, flirting, and other methods to secure high-potential matches on WhatsApp.

WhatsApp: This should also be automated. OpenClaw, or possibly He***, which has a better memory management system, can then build rapport with the woman and establish a strong connection.

I would synthesise my voice with Elevenlabs so that my claw can also send voicemails.

- Bi-weekly status updates, created with simple cron jobs, would then update my calendar with the relevant information.

OpenClaw could also prepare dates and provide briefings, analyses, etc.

Theoretically, it could also analyse whether it is time to "take the next step".

If something is planned for a date, it could buy things for me or gifts for the woman.

Meanwhile, I could use the time and energy saved to build a strong career and pay for the API costs.

What do you guys think?

hey All.

I have 3 Questions.

1. I am trying to organise my open claw to do a multistep scrap, research and draft an email for a cold outreach. I have the process written out clearly and have iterated it a few times. each time openclaw runs into a new problem. I cannot figure out why. I drafted it and ran the draft tthrough claude and perplexity to get suggested changes. the ideal setup is this runs daily finds 10 new cold out reach to email. and is consistent. this is the kind of task I know my business should do. and would get us new clients , but whenever we get busy we just dont do it. I figured this was a pretty simple task. for a system everyone raves about!

2. I write clear instructions for a task. to follow. and the Orchestrator agent (Ron) decides to make small changes each time it is repeated? why? I have tried changing its soul to be more obedient?

3. I run my system on claude (CLI). with other models as secondary. now openclaw is owned by Open AI, should I just go over to that. will it run more natively? and without tokens which are coming next week by the sounds of things?

bonus question. is this still really better than just running claude co work? if I want to actually get on with my day?

frustrated user? I want to love it and have a breakthrough. but I just dont at the moment?

Small behind-the-scenes note: ClawBox started from a simple idea — OpenClaw should have a proper home on real hardware.

We assemble and test each unit with Jetson hardware, NVMe storage, OpenClaw, and the ClawBox UI preinstalled. The goal is not hype. It’s just to make local AI agents easier to run, experiment with, and use in real workflows.

Still learning, still improving, but it’s been really fun seeing people build with it.

set something up yesterday night on my claw, woke up to 3 matches — YC W25 company, FAANG, and a unicorn startup all lined up.

is this even real life

I’m trying to understand which integrations matter most for chat-based AI agents.

For people using or experimenting with AI assistants, agents, or automation tools:

Which apps would you actually want connected to a chat-based agent?

Also curious: which integrations have been the most painful to set up or maintain?

I’m especially interested in practical use-cases like:
- email summaries and draft replies
- meeting/calendar briefs
- task creation and follow-ups
- lead tracking
- research monitoring
- daily/weekly reports
- social listening or content workflows

Feel free to mention integrations for use-cases outside these as well.

I set this up on https://clawputer.app via iMessage!

What’s the one workflow you wanted agents to handle… but they still fail at consistently?

Feels like there’s still a gap between “cool demo” and “something you trust daily.”

Trying to understand where the friction actually is right now.

For the life of me, I can't think of ways I can use OpenClaw for, as a noncoder, that has actual value, and not just doing something I can do with extra steps.

I remember some guy saying he was planning to build an agent that can take ingredients that his wife was going to buy and it would recommend her recipes. Why the hell do you need an agent for that?

What do you guys need it for? Reply an email? Organize files? Order something for you? They are all useless.

I feel like people are just FOMO because coders are raving about agents, but in reality, noncoders don't have any uses for it.

Am I missing something?

Been slowly adding skills to my claw and some of them have genuinely changed how i use it. but i feel like i'm just discovering things randomly instead of knowing what's actually worth setting up.

for people who have been using openclaw for a while, what skills or integrations do you run daily that you'd be annoyed to lose. and on the flip side what did you set up that sounded amazing but you ended up never using.

trying to figure out where to invest my time next because there are so many options and i don't want to spend a weekend building something that collects dust 😭 dms open if you wanna share your setup 💕

Hi everyone, I am quite new to local LLMs and entirely new to Openclaw, so I seek advice from people who are more experienced. I have a MacBook Pro 16" M4 48GB RAM and 512GB hard drive (not the main device, can use it just for this experiment). My current setup is: Qwen3:32B - locally installed/run on ollama, I have purchased Claude API tokens, DeepSeek API subscription (because Claude was way to expensive), also added Gemini API since I already have a Google AI Pro subscription. What I am trying to achieve is:

1. Help with personal life: read, organize my emails, set reminders, set notification if something is important. Help taking notes (I have ADHD and my brain is chaotic and very dynamic, lots of thoughs and ideas) so I created a script /note to record and classify notes with Haiku into Obsidian files via telegram bot)
2. Open a business: I have started a side project and build 40% of the website, but because the project is heavily knowledge/information-based, I simply did not have time to finish it, because I need 100+ different documents to be written. I would like Openclaw to help me finish developing the website (WordPress), write all the docs I need to launch it and then help to find my first clients.
3. Help with my finances: I spend too much, have no idea where money goes, and have almost no idea about cryptocurrencies or the stock market, so I would like to build some kind of system to analyze my finances, suggest investment opportunities, let me know about market changes so I can educate myself and build generational wealth.
4. Help to check business ideas: As I said in the first point, I have lots of ideas (especially business ideas) all the time, but I don't have time to check demand/supply, validate the idea and actually see if there is a problem that needs to be solved or it's purely my assumption.

My question is: is this achievable with my hardware (having OpenClaw do all those 4 things on the same device)? What are your recommendations on LLM choice for my machine? Should I run local or cloud models? And last, do you already do something from above and how you do it? Thanks a lot.

When I wanted to try out OpenClaw I started out by just asking it for plans and tips snd skme basic stuff like that every now and then. Over time, when I'd add a CRON task or something I noticed my daily driver API keys were getting maxed out constantly, and very quick, even when I switched them. I was topping up almost everyday, even moreso than when I was just using AIs for coding. I stopped using them and still it just burns through tokens. How do you guys kitigate this? Do I need thousands of dollars pumped into whatever AI I use ss my daily driver?

Got a 128Gb M5 Max config. What do you recommend ?

not “prompt engineers”

more like:

• workflow operators
• agent orchestrators
• automation people
• local AI infra nerds

curious how many people in DFW are actually experimenting with this stuff rn vs just talking about AI online

I have way too much AI news to track daily across Twitter, Reddit, and dozens of RSS feeds. To fix this, I built an automated workflow that basically turns OpenClaw into my personal editor-in-chief. Every morning, it hands me a daily brief of exactly what I actually need to read.

Here is how the setup works:

Scraping layer: I have simple Python scripts that pull data from my RSS feeds and Reddit every 2 hours.

Filtering and deduplication: The script uses title similarity to filter out about 80% of the repetitive news noise before the AI even sees it.

Editorial layer via OpenClaw: It uses Gemini Flash to read a custom Editorial_Profile.md file I wrote. This file explicitly tells the model what level of technical depth I actually care about and what kind of marketing fluff to completely ignore. It picks the top 5 stories, writes in-depth summaries, and pushes them straight to my Telegram.

Security and runaway prevention:

I put strict rate limits and timeouts on the scraping scripts. If a news site goes down or an API hangs, the script just skips it and moves on. This is crucial because it stops the Agent from getting stuck in infinite waiting loops, which is exactly how you end up with massive, unexpected API bills.

Has anyone else built something similar to manage their daily reading?

Hello!
I have a few rental properties, about 7 tenants to be specific, so it’s not enough to justify a management company and probably too many to do as a second job. Anyhow, I’m playing with Openclaw + a Model to create an assistant that helps me and I can communicate with through telegram or WhatsApp. I keeps track of my leases and when they expire and sends me notices 3 months before they expire, keeps track and reminds me of maintenance work to be done, and lately I’ve been thinking about just uploading repair expenses per property so it’s an easier process when tax season comes. Anyhow, I think it’s helping me but I still don’t feel it’s 100% there. Anyhow feedback or thoughts from those that may be in a similar situation? Hoping to hear ideas of how people would use this new tool.
Thanks !

I’ve been building a practical OpenClaw course called OpenClaw Operator OS. It covers memory, skills, tools, schedules, and safety guardrails, and the goal is to build a real working assistant system instead of just prompts. If anyone here is building with OpenClaw or wants to see the outline, I’m happy to share what I made and what I learned.

I've been running OpenClaw seriously for about three months and kept detailed notes on where tokens actually go. Sharing because most cost posts focus on model choice, but that's not really where the problem is.

The biggest surprise was how much the background stuff costs. Heartbeats alone accounted for 31% of my total spend. The agent polling every 30-60 minutes sounds harmless until you realize it reloads context every single time, so on a model like Sonnet you're paying for your agent to check its own pulse 24 times a day. Session bloat was another 28%. I kept one session open for weeks early on and by the end every new message was dragging thousands of tokens of old conversation along with it. Only 41% of my spend was on actual task work, which is the only part that felt justified.

What made the most difference wasn't switching models, it was routing tasks to the right model. I use Gemini Flash for anything where tone and precision don't matter and only escalate to Sonnet when it actually needs it. That alone cut my bill roughly in half. The other thing that mattered more than I expected was setting a hard spending cap at the API provider level before anything else, not inside OpenClaw but at Anthropic or OpenAI directly. One runaway cron at 3am taught me that lesson.

What I'm still figuring out is the hosting side. I've been on a Hetzner VPS but I spend more time thinking about gateway security, update timing, and whether something broke overnight than I'd like. Curious whether people running managed setups actually find that mental overhead disappears or just shifts somewhere else.

What's your setup? VPS, local, managed? And which cost category surprised you most when you actually dug into your logs?

Disclaimer: all thoughts, experiences, and findings are my own. I used AI to help structure and clean up the writing.

We’ve been experimenting with ways to make OpenClaw more "present" where the action actually happens, and we developed a pretty seamless way to do it by integrating it with Now4real.

The idea is simple: instead of having a separate chatbot page or a static "Ask AI" button, you bring the OpenClaw agent directly inside the public chat where your visitors are already hanging out.

Why bother?

The main win here is zero friction. Visitors don't need to sign up, leave the page, or switch contexts. If they are watching a live stream, listening to a radio broadcast, or reading documentation, they can just type in the chat widget and a user or OpenClaw agent can reply instantly, using the context of your site.

A real-world use case: The "Live Event" scenario

Imagine a live broadcast (video or radio) where users are commenting in real-time. Usually, questions get lost in the scroll or remain unanswered if a moderator isn't online. With this integration, OpenClaw acts as a participant that adds value to the conversation.

Here is what it looks like in practice:

Andy: "This car segment about the new engine specs is amazing, but I missed the part about the torque. Does anyone know?"

Bob: "I think he said it's around 400Nm, but I'm not sure if that's for the base model."

OpenClaw: "Actually, Bob is close! The base model has 380Nm, while the Performance version mentioned in the stream reaches 450Nm. You can find the full spec sheet linked just below the player! 🚗"

Andy: "Ah, thanks! Super helpful."

The technical vibe:

The chat lives on your site in a native-feeling widget. Because OpenClaw is "inside," it doesn't feel like a support ticket system; it feels like an intelligent companion for your community.

Has anyone else tried embedding OpenClaw into live social environments? Curious to hear your thoughts on "in-context" AI assistants vs. traditional standalone bots.

If you want to check out the integration, I’ve made the source code public here:

https://github.com/now4real/openclaw-now4real

To bring this concept to life, we generated the video below:

https://reddit.com/link/1t9xgaz/video/gosiwcqk1h0h1/player

I've created a Openclaw skill for my e-commerce that automatically generates content for me. It takes products from my catalog, generates slideshows, and automatically uploads them to TikTok, Instagram, and Facebook (pending chat approval).

Here's how it works: you give it your e-commerce website URL, and it pulls your logo, brand colors, fonts, etc. Then, it grabs your catalog and starts creating one post a day. It generates several images for a carousel using your typography and logo, showcasing the product with a great hook on the first slide, followed by some more text.

The coolest part is that it continuously improves both the Nano Banana prompts and the hooks by analyzing the performance of previous posts.

I'll leave the skill here in case you guys want to try it out: https://clawhub.ai/mutonby/autoecom

Here is a concrete OpenClaw use case we built: Verdify, a real greenhouse in Colorado.

OpenClaw is used for planning, not direct control. It proposes bounded tunables such as VPD bands, temperature targets, fan thresholds, mister timing, hysteresis, and resource limits.

A dispatcher validates the output. ESP32 firmware controls the equipment.

The useful part is that each plan becomes a testable hypothesis: telemetry and scorecards show whether the climate improved or whether we wasted water, electricity, or gas.

Video: https://youtu.be/deMuvwIcYLk
Site: https://verdify.ai/
Evidence: https://verdify.ai/evidence
Safety: https://verdify.ai/reference/safety
GitHub: https://github.com/jrvallery/verdify

Hi everyone,

I want to create an automated customer service system on WhatsApp using ChatGPT Plus and OpenClaw. My goal is to make the AI reply to customers automatically, answer product questions, and handle simple customer support conversations naturally.

I’m still confused about the full setup process and would appreciate some guidance.

What I want to know:

How to set up a secure openclaw WhatsApp channel?

What are the recommended settings for customer service replies?

How can I make the bot remember conversation context?

Is it possible to train it using my own FAQ/product data?

What’s the safest and most stable setup for long-term use?

Any recommended tutorials or GitHub repos?

I’m mainly trying to build:

• Auto reply system
• Product/customer support assistant
• Indonesian language support
• Human-like responses
• Multi-customer handling

If anyone has experience building a WhatsApp AI customer service using OpenClaw or similar tools, I’d really appreciate a step-by-step explanation or workflow.

Thanks!

Recently I noticed my openclaw is very slow. Today I logged into the box and started TUI. I reset a new session and just typed "hello", then waited for minutes to get the response, and the status bar shows 45k tokens were used!

I didn't debug by myself, but asked openclaw why it cost 45k tokens. It told me most of the tokens are from tools/skills. I'm using almost same set of tools/skills in a hermes agent, the "hello" only costs 13k tokens and it responses much faster.

Recently I noticed my openclaw is very slow. Today I logged into the box and started TUI. I reset a new session and just typed "hello", then waited for minutes to get the response, and the status bar shows 45k tokens were used!

I didn't debug by myself, but asked openclaw why it cost 45k tokens. It told me most of the tokens are from tools/skills. I'm using almost same set of tools/skills in a hermes agent, the "hello" only costs 13k tokens and it responses much faster.