Your Wasting AI Tokens - Use N8N With OpenClaw
https://www.youtube.com/watch?v=xOt_yWnw9nM
[00:00] I'm going to be covering something in this AI agent space that most people are getting wrong right now and it's costing people a lot of money.
[00:09] You know, wasting tokens, API rate limiting, that seems to be getting all the buzz right now.
[00:13] You know, everyone's trying to make Open Claw do everything, research, thinking, writing, image generation, file management, pretty much scheduling every single task.
[00:23] I've been there, it's okay.
[00:26] And Open Claw can do all of that, but should it be doing all that?
[00:29] There's a developer on Reddit that figured out that the answer is basically no.
[00:33] You should check out that Reddit post down below.
[00:36] And basically the solution he came up with is genius.
[00:38] He connected Open Claw with N8N and if you haven't heard of N8N, it's an open source workflow automation tool.
[00:45] Think of it like Zapier or make.com, but you can self-host it and it's free.
[00:50] And the way he connected them is so smart that I had to make a video because once you understand this pattern, it's going to change how you think about building with AI agents.
[00:57] And right now there seems to
[01:00] AI agents.
[01:01] And right now there seems to be a lot of problems going on with be a lot of problems going on with Anthropic usage, Open AI rate limits.
[01:04] So this might be a great piece to the puzzle if you're experiencing some of those issues.
[01:07] So here's the problem that this person was facing and he was trying to solve this.
[01:12] He he needed to generate a lot of images, like batch image generation, 50 to 100 images at a time using Minimax M2.7 as the model.
[01:24] Now the obvious approach is just tell your Open Claw agent, "Hey, generate these 100 images for me, whatever."
[01:30] And the Open Claw agent would do that.
[01:32] It would loop through each one, call the API, wait for the result, move to the next one.
[01:37] But here's the catch.
[01:39] Every single step of that process is burning tons of tokens.
[01:42] Open Claw has to think about what to do next, it has to compose the API call, it has to interpret the result and then it has to decide if the images look right.
[01:51] It has to move to the next one and then all of that thinking costs money because you're paying for the LLM to process all those tokens.
[01:58] His key insight, and this
[02:00] those tokens.
[02:03] His key insight, and this is the part that really clicked for me, is the part that really clicked for me, was that Open Claw is amazing at understanding intent.
[02:07] You just say, "I need 50 product images with white backgrounds for my e-commerce store."
[02:12] And Open Claw immediately understands what you want, what the parameters should be, how to structure the prompts.
[02:17] That's the thinking part.
[02:18] That's what the LLMs are great at.
[02:21] But the actual execution, the part where you take those 50 prompts and run them through the image generation API, all one by one, that doesn't require any intelligence.
[02:30] It's the same process repeated 50 times.
[02:33] Same template, same parameters, same output format.
[02:37] You don't need a brain for that, you just need a machine.
[02:39] And that's where N8N comes in.
[02:42] This N8N is the machine.
[02:44] It's deterministic.
[02:46] You build a workflow once and it runs the exact same way every single time.
[02:49] No tokens burned, no LLM thinking required, it just executes the steps.
[02:54] So here's how his actual setup works and I love how simple it is.
[02:59] My setup is simple, it needs to be simple for me to understand
[03:00] needs to be simple for me to understand it.
[03:03] And this is really easy.
[03:03] So step one, you chat with Open Claw.
[03:05] You tell it what you want.
[03:07] Generate 50 images of tropical fruit with the following style.
[03:09] I don't know, I don't care, whatever.
[03:10] Open Claw understands your intent and creates structured prompts for each image.
[03:14] The second step is Open Claw writes those prompts to a Google Sheet.
[03:18] Each row has the image prompt, any references images and the parameters.
[03:23] All done.
[03:25] Step three is Open Claw triggers an N8N webhook.
[03:28] It's just a simple HTTP call that says, "Hey, N8N, what you doing?
[03:31] The prompts are ready in the sheet.
[03:33] Go and get them.
[03:34] Go do your thing."
[03:37] Step four is N8N takes over.
[03:39] It reads the prompts from the sheet, calls the Minimax 2.7 image generation API for each one and then it writes the results, the generated image URLs back to the sheet.
[03:46] Real quick, before we keep going, if you're watching this and you want to actually build with some of these tools, not just watch videos about them, you're going to want to check out our community down below, Shipping School.
[03:56] We have a full Claude code course, a full Open
[04:01] full Claude code course, a full Open Claw course and four live bootcamps.
[04:04] Claw course and four live bootcamps every single week where we actually help.
[04:06] every single week where we actually help you get set up from scratch.
[04:09] you get set up from scratch.
[04:10] actually set this thing up, not just watch a tutorial and figure it out by yourself.
[04:12] watch a tutorial and figure it out by yourself.
[04:14] And we also provide one-on-one coaching so you can book a call with me.
[04:16] coaching so you can book a call with me, we can share screens and I can help you get Claude code or Open Claw running on your machine.
[04:18] get Claude code or Open Claw running on your machine.
[04:21] That's it, no fluff.
[04:24] I built this community because watching YouTube's only gets you so far.
[04:25] built this community because watching YouTube's only gets you so far.
[04:27] We launched it just three days ago and we have over 55 members.
[04:29] launched it just three days ago and we have over 55 members.
[04:32] You need people around you who are actually building, people who hold you accountable and coaches who can help you when you get stuck.
[04:34] around you who are actually building, people who hold you accountable and coaches who can help you when you get stuck.
[04:36] coaches who can help you when you get stuck.
[04:38] I'll put the link in the description down below.
[04:39] stuck.
[04:41] description down below.
[04:43] Get in now before the price goes up.
[04:45] Step five, Open Claw checks the sheet and reports back to you.
[04:48] back to you.
[04:50] All 50 images are done, there's the results.
[04:52] That simple.
[04:54] This is going to save you so much money.
[04:56] The whole thing runs from his phone.
[04:58] That's the crazy part.
[05:00] He chats with Open Claw on Telegram, the work happens in the background through N8N and then the results appear in the Google Sheets when
[05:01] results appear in the Google Sheets when she can check from anywhere.
[05:03] Now, let me break down why this is better than just using Open Claw for everything and there are huge reasons to this.
[05:08] The first one being cost.
[05:10] When Open Claw runs 50 image generations in a loop, every single iteration requires the LLM to think.
[05:19] That's input tokens for the context, output tokens for the reasoning, all multiplied by 50 iterations.
[05:26] Depending on the model, that could be several dollars in token cost just for the orchestration alone.
[05:30] With the N8N approach, Open Claw thinks once, it creates all 50 prompts in a single interaction.
[05:37] The N8N handles the repetitive execution for free, zero tokens on that front, and then the AI cost is only the actual image generation for the API calls, which you'd pay either way.
[05:50] His estimate was that this approach cut his cost by 80% compared to having Open Claw handle do it handle it and do it all by itself.
[05:56] The second reason is organization.
[05:59] Like when you generate 50 images through a chat interface, they're scattered through the
[06:02] interface, they're scattered through the entire conversation.
[06:04] So good luck finding that one specific one you're looking for for the thumbnail you need.
[06:07] You know, you're scrolling through pages of chat history just to try to find the right image you're trying to use.
[06:12] But with Google Sheets, it's more organized.
[06:14] Everything is in a table, row one is image one, the prompt with the parameters and the result URL.
[06:21] Row 50 is image 50, clean and organized, it's searchable.
[06:25] You can filter, sort, share the sheet with a team member, whatever you need.
[06:29] And there's a third benefit he didn't even explicitly mention, but I think this is huge, reliability.
[06:34] LLMs can be unpredictable and maybe you've experienced this in the last week.
[06:37] Maybe Open Claw, let's just say, loses track of where it is in the 50 image loop.
[06:41] Maybe the context window gets too long and starts making mistakes.
[06:45] Maybe the connection drops and it doesn't even know which image were already generated and messes up.
[06:49] So with N8N, the workflow is deterministic.
[06:55] It processes each row in order.
[06:58] If it fails on row 23, it knows exactly it where it failed and you can just restart it from there.
[07:01] That
[07:03] can just restart it from there.
[07:05] That kind of reliability matters when you're doing batch work.
[07:07] Say you're doing 50 images, that's going to be more organized.
[07:11] Now here's where I want to zoom out because this pattern applies to way more than image generation.
[07:15] You're probably wondering, "I don't even generate images."
[07:18] The same concept applies.
[07:20] If you think about any task where you need an AI to understand what you want and then a machine to execute it repeatedly, let's just say email campaigns.
[07:27] You want to send personalized emails to 200 leads.
[07:31] Open Claw understands your campaign goal, it writes the email template, it then personalizes the variables, then N8N handles the actual sending through your email service.
[07:40] Zero tokens burned on the loop.
[07:43] That is amazing.
[07:46] Data processing for example is another use case.
[07:47] You can have a spreadsheet with 500 rows that need to be cleaned and reformatted.
[07:52] Open Claw understands the cleaning rules.
[07:54] It defines the transformations.
[07:56] Then N8N processes each row identically through these rules.
[07:58] Let's just say social media scheduling.
[08:00] If you want to post 30 pieces of a content across four
[08:04] pieces of a content across four different platforms over the next month,
[08:06] different platforms over the next month, let's say, Open Claw creates the content strategy, writes the post, decides the optimal timing, then it handles the actual scheduling and posting through the platform APIs.
[08:16] Report generation is another one. You need weekly reports pulled from five different data sources.
[08:22] Well, Open Claw designs the report template and then decides what metrics matter.
[08:27] Then N8N pulls the data, formats it and delivers the report every Monday at 9:00 a.m.
[08:31] In every one of these cases, the pattern is the same. Open Claw does the thinking, N8N does the doing.
[08:39] It's the brain plus the machine. That's the beautiful combo of this.
[08:41] And I want to address something that the developer mentioned in his Reddit post because I think this is very important.
[08:47] He said everyone's saying N8N is dead because the Open Claw can just handle everything now.
[08:55] In his response, that didn't just feel right. It's, you know, they're both just for different jobs.
[08:59] And I completely agree with that take.
[09:00] It's not Open Claw versus N8N at all, it's Open Claw and N8N. They're two
[09:05] it's Open Claw and N8N.
[09:05] They're two different things, they're complementary different things, they're complementary tools.
[09:09] Using one doesn't mean you can't use the other.
[09:11] I think using them together is the best of both worlds.
[09:13] Open Claw gives you the conversational intelligence, the ability to just tell the agent what you want in plain English and have it figure out the details.
[09:22] N8N gives you the deterministic execution, the ability to run exact steps the same way every time without burning tokens or relying on the LLM to stay on track.
[09:32] Together they're more powerful than either one just alone by itself.
[09:36] And the setup isn't even complicated, it's so easy.
[09:39] N8N is free and self-hosted.
[09:41] You can run it on the same machine as Open Claw or on a cheap VPS.
[09:46] The connection between them is just a webhook URL.
[09:48] Open Claw calls that webhook, N8N triggers the workflow.
[09:53] Google Sheets is the shared data layer and that's it.
[09:55] Nothing complex, easy infrastructure, no expensive services, just three tools working together.
[10:01] Here's the practical advice if you'd want to try this yourself.
[10:04] You know, start with one
[10:05] yourself. You know, start with one workflow.
[10:07] Pick a task that you're actually doing in Open Claw that involves repetitive steps.
[10:10] Image generation, data processing, handling your email, whatever. I don't care.
[10:15] Build this one workflow in N8N, connect it to Open Claw via webhook, and use Google Sheets as the handoff layer.
[10:20] Test it with 10 items, then scale to 100.
[10:24] If you're struggling to keep up with content, well, I'm about to save you about 40 days worth of work.
[10:30] I built something called Content Machine. It's 10 AI agents that run on the Open Claw orchestration, and they handle everything.
[10:36] Scripts, thumbnails, X posts, blogs, outreach, clips, newsletters, all of it.
[10:41] So, I went from 1,000 subscribers to 4,000 subscribers on YouTube in 7 days using this exact system.
[10:48] Every single morning, I wake up, and the content's already done.
[10:53] I spend maybe 15-20 minutes reviewing and approving them, and I move on with my day.
[10:58] It works for any niche, fitness, finance, real estate, marketing, whatever you are building, and it is
[11:07] whatever you are building, and it is 100% completely customizable to your use
[11:10] 100% completely customizable to your use case.
[11:10] So, you get the Mission Control dashboard, all of the cron jobs,
[11:14] everything I've built over the last 40 days helping me gain more and more
[11:18] people to subscribe and join the community.
[11:20] So, you plug in your own thing, and it molds it to you.
[11:24] It learns how you talk, and it writes [music] so it doesn't sound like AI slop.
[11:26] $97 one-time, it's not a subscription.
[11:29] I'll put the link down below, and you'll thank me later.
[11:33] Once you see how much smoother it is and how much you save on tokens, you'll start seeing
[11:36] opportunities to apply this pattern to everywhere.
[11:40] You know, N8N nodes he used are open source as well, and they're available on GitHub.
[11:44] I got that linked below.
[11:46] I'll drop the link, just bookmark it, whatever.
[11:48] And if you want help setting any of this type of stuff up, this is literally what we do in the
[11:50] community.
[11:52] We have six live calls every single week with a seventh one on the way.
[11:53] You know, over 175 members have joined this group in the last 17 days, and I'm so thankful.
[11:57] You know, we're real people building real things, and we're focused on community and actually
[12:07] we're focused on community and actually human-to-human interaction.
[12:09] There are human-to-human interaction.
[12:11] There are courses in there, but we're focusing on building and building together.
[12:13] So, you know, this is one of those things where,
[12:15] you know, once you see it, you can't unsee it.
[12:17] N8N has been popular for this last year, and now more and more Open Claw people are getting into the whole AI agent space.
[12:21] I think using these tools in combination can be really helpful, especially since people don't have tens of thousands of dollars to start spending on tokens right away.
[12:33] This can be a really easy way where you can automate a lot of the simple processes.
[12:36] Image generation, data processing, emails.
[12:41] Get that going, and you'll save some money.
[12:43] You know, I'll I'll look just like, for example, my own agent setup, and I can identify at least three or four things where we're burning tokens on repetitive execution that can literally be handled through the same workflow.
[12:54] That's money I'm wasting every single day.
[12:56] And it's just not about money, it's more about the speed.
[12:59] N8N can process 50 items in the time it takes Open Claw to process just 10, because it's not waiting for the LLM responses between each step.
[13:05] Faster
[13:08] responses between each step.
[13:10] Faster execution, lower cost, better execution, lower cost, better organization, that's a win for everybody.
[13:12] organization, that's a win for everybody.
[13:14] I think this combination is going to become a standard pattern in most AI agent spaces right now, because
[13:16] most AI agent spaces right now, because most people think of AI agents, and they just think of workflow automation, and that's it.
[13:19] most people think of AI agents, and they just think of workflow automation, and that's it.
[13:21] just think of workflow automation, and that's it.
[13:23] that's it.
[13:24] You know, they're not competing.
[13:28] N8N not not N8N versus Open Claw.
[13:30] They work together.
[13:32] They're puzzle pieces that fit beautifully.
[13:34] And people who figure that out early are going to have a massive advantage in building efficient automated systems.
[13:36] have a massive advantage in building efficient automated systems.
[13:38] The takeaway is stop making your AI agent do everything.
[13:40] Let it do the thinking.
[13:42] Let a deterministic tool do the doing.
[13:45] So, it's your brain plus the machine, right?
[13:47] That's the pattern, and your wallet is going to see the results.
[13:49] Try setting up your first automation in N8N, get it downloaded, it's open source.
[13:51] get it downloaded, it's open source.
[13:53] Let me know how it's working for you.
[13:55] And if you haven't subscribed to the channel already, please do.
[13:57] We release four to six videos every single day, and hit the notification bell for the next video drop.
[13:58] We release four to six videos every single day, and hit the notification bell for the next video drop.
[14:00] hit the notification bell for the next video drop.
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[14:04] Be blessed.
[14:05] drop.