So What? How to Manage AI Usage Limits

Well, hey everyone, happy Thursday. Welcome to So What, the Marketing Analytics and Insights live show. I'm joined by Chris and John. Howdy, fellas. Um, thankfully, our pre-show ramble is not recorded anywhere because it is nonsensical, not to like be all mysterious, but it it occurred to me while the credits were rolling to start the show.

I was like, we don't we don't need to be uh talk about any of that publicly. Um so what we are gonna talk about publicly today is so what how to manage AI usage limits. So a lot of people a few weeks ago jumped ship from ChatGPT, Gemini to move over to Claude, especially Claude Desktop, which includes chat and co-work and code. Doesn't have to be desktop, you can use code and chat on the web app as well. But what happens is that people are running into usage limits.

Now I think it was just was it this week started. Um Claude was tightening some of the peak usage windows from eight to two p.m. for whatever time zone you're in. So that's gonna look a little bit different for everybody. Um, and basically they're like, these is when people are, you know, using our systems the most.

So you are stressing our systems out. So we are gonna like make it undesirable for you to be working on Claude during those times. But you know when you can work is when you should be sleeping. And for a lot of people, that does not work because they're sleeping. So what we wanted to talk about today is how to manage your AI uses usage limits, but also what are some alternatives if you're running into these usage limits and you just really want to get a good night's sleep and not actually be working on your AI vibe coding.

So Chris, where should we start well? I think we should start actually with what you do uh in Claude Cowork, because let's say so. There's there's a few different scenarios here, and we should probably start talking about what the usage limits are first, because that's important. There's two fundamental different ways to use AI these days. There is the all you can eat within with a big asterisk for a fixed fee a month, so there's fixed fee usage, pay 20 bucks a month, 200 a month, whatever.

That's one version, and that's what pretty much everyone is used to. If you're using Gemini in the web, you're using Chat GPT, you've been on the $20 a month plan or whatever. The second is called API usage, where you're you're using the APIs directly in tools like uh um Visual Studio Code, for example, and you pay per token that you use. A token is three quarters of a word, essentially. So the more code you write, the more you pay.

If to give you a sense of the disparity between these two and why usage limits are such a big deal. If you were to use a tool like Claude Code on the API plan, and you paid the maximum amount of money for Claude Code, the $200 a month Claude Max 20 plan, which is what we pay for, and you ran the exact same amount of usage, full tilt for a month on the API, you would spend close to $3,000 in API usage for the same $200. So just obviously it's it's kind of a money loser for anthropic, uh, but it gets people to use the product, and very few people max it out, you know, 24 hours a day. Their usage limits were specifically 5 a.m. to 11 a.m.

Pacific time. That's where the data centers and the headquarters is. So wherever you are on the planet, translate that into your local time zone. For us, it's 8 a.m. to 2 p.m.

Eastern time. If you're in Europe, it's 1 p.m. to uh 8 p.m. uh european time, etc. etc.

So during those times, you get throttled. You use up your anthropic has uh, and this is common to a lot of providers, they have two different sets of limits. There's what's called a session limit, which is five hour windows. I don't know why five, but five hour windows, where during that period of time, you have a limited to the amount of usage you can get out of the system on the fixed plan. And by the way, this is true of Gemini and Chat GPT and stuff like that too.

I have run into Gemini limits in the trust insights workspace, like in 20 minutes sometimes. Well, and to uh apologies for interrupting you, just for context, when a lot of these models first came out, you would see people using like Anthropics Claude's chat on the web, and it'd be like, Your session you have like exceeded your session for the day, try again in a few hours. Like that was very common for a lot of people to see up front. So that's you know, just for context, that's what we're referring to is like your session limits, not your overall weekly and monthly usage limits. Right.

And that brings me to the second point, which is the weekly limit. You also get a budget of usage for the week. Now, here's the thing about anthropic, they don't tell you what that unit is. They just tell you you've used 82% of your weekly uh plan. Yeah, but of what?

Like we don't know if it's by token, by whatever. Other providers uh will tell you like it's the number of requests you make. So requests can be small or big, but we're gonna bill you by, we're gonna basically give you a certain number of requests you can't go over that. So that's sort of the context of what usage limits are with AI. It's it's it's a cap to prevent you from just melting someone's uh data center uh on you.

And every provider implements it differently. Some providers don't tell you, some do. Uh and and they're different. If you if it's pay as you go on the API, then there functionally are no limits. The limit is what your credit card can tolerate.

Well, and what's interesting, so you know, we I use Claude desktop, specifically co-work a lot, but it doesn't tell me, hey, you're almost at your limit, or hey, you've exceeded your limit. It's just like you went over your limit. So here's the extra money we're gonna charge you now. And it's like you there's nothing you can do about it. And so I've gotten more diligent about checking the limits a couple of times a day.

So, like right now, for example, my current session is at 44% and it resets in about three hours. And then the weekly limit, which resets in about 19 hours, is at 73%. And that's for me and you and John and Kelsey. Exactly. In fact, uh, let's just do a very quick tour to show where some of these limits live in case people aren't familiar.

So if you're in Claude, either in the desktop, the mobile app, or wherever, go to your uh settings, go to your usage menu, and that's exactly what Katie was talking about. Here's your session limit, which is the five hour window, and here's your weekly limit. And Claw Anthropic to make things even more confusing, uh, also tells you uh all models and just the sonnet model, which is a little bit more efficient. There's the extra usage. If that toggle is turned on and you have a credit card attached to your account, then it will spend money on the API.

I actually turned that off for our account so that it doesn't do that, will just tell us warning. Uh if you're in Google's AI Studio, you'll see uh AI their API usage, and you can see uh what you're doing there. A provider like Grok G R O Q, not Elon Musk's shop, tells you your activity and your costs. This is API based. So there's no there's no spending, there's no uh usage limit there, but it will tell you like, hey, you've spent two dollars so far in the last 30 days.

Um and finally, uh it in providers like Minimax, which uh you can see the same five hour limit there, I'm at four percent of my five hour limit there, and uh and the weekly limit, I'm at 25%, and that resets in in about three days. So that's where all the usage limits live in the desktop in the consumer versions like Gemini and workspace and stuff, you get no warnings, and there's no place to check the usage. You just get a come back later. Mm-hmm. Yeah, so you can be in the middle of something like that really, you know, heavy project or in a flow, and then all of a sudden, what the heck?

And then you totally forget it. And so, like, it's very unhelpful. Um, and I think, Chris, one of the things that you said is if you're not hitting your usage limits, like then what are you doing? I'm paraphrasing, you didn't say that exactly, but you know, that's what I said you said. And there, and that's interesting.

It's sort of a game that we play every week uh with our with our accounts is to say, okay, well, we've paid for all this usage. And if it's if it's reset is in 22 hours and we're at like 16% usage, you're like, well, better use it somehow. Hey, let's better murder mystery. Well, it's I think the way for it to resonate with people, think of it like PTO. It's use it or lose it.

And nobody wants to lose their PTO. So they're gonna start squeezing in all those days at the end of the month, which is really annoying to your manager, but there it's your time. Exactly. So there's three things that you should be doing to manage your AI usage limits. Uh the first one, Katie's gonna talk about, which is intelligent planning, like planning ahead to deciding when to do things.

The second is command line interface tools, which we'll talk about, and the third is drop-in replacements for some of the different tools, alternatives to look at. So, Katie, let's start with you on intelligent planning first. Maybe you don't want to change provisions, maybe you don't want to juggle all technology, and you still have this planning limit. What do you do to get around those limits? Knowing that there's periods of time when yeah, you're gonna burn your session limit if you if you do stuff during that time.

Um, so I'm gonna shock you all. Ta-da! It's a 5P framework. Um, I am a project manager at heart, and everything I do starts with what am I doing? What is the purpose of this thing?

Who's involved? What is the process? Process is huge. I wrote a post about this the other day because the amount of work that I've gotten done in the past month is 10x what I've been able to do previously. But that's because everything has a clear process.

And so I'm able to produce more while not burning up the usage because I'm not sitting there trying to figure out this, that, and the other. You know, what are the platforms? So for every project, it's likely bringing in Google Analytics data or HubSpot data or other, you know, research or you know, stuff from the Trust Insights website or whatever. And then the performance. What is the output meant to be?

I always start with a plan. And you're like, that is just my default state. So I'll, you know, boot up a new Claude co-work instance on the desktop app and I'll say, I have all of these things. I'm thinking about this thing. Before you take any action, let's make a plan because I want to make sure that it's what I'm after, it's what I'm looking for.

But I mean, this is true of like anything you're doing in software development or in marketing or in operations. You should have a measurable plan first that has a very clear, repeatable process in it, so that if you want to do it more than once, you can do it more than once. And you can create high quality things at a high volume. And that's, you know, so when Chris says intelligent planning, that's what I'm doing. And so over the uh over this past weekend, um, I actually developed a plan to fix up as much of the technical SEO on the Trust Insights website as we could.

Because, you know, we're a small team, it's the three of us plus Kelsey, and we don't have time or the resources to dedicate to that stuff, even though we know it's important. So I took the site issues from our SEO tool. I just exported the data and I put together a plan with Claude Co-Work, and we came up with a four-part, let me see what it was. It was four parts, uh, four phases. It was uh phase one, critical errors, phase two, structural issues, phase three, content meta, and phase four was maintenance.

And I was like, this is great. And that probably took me about 20-ish minutes to put that plan together with Claude Co-work. And I was like, I don't want to do this now. I wanted to be able to run it overnight. So I said, let's come up with scheduled projects.

And so it took each project plan and made its own sort of task, you know, it's a task within Claude Co-Work. It made its own project and basically said, All right, whenever you're ready to run these, hit run, or you can schedule it to run at a certain time. I personally chose to run them myself, knowing that I would need to be able to give permissions and that kind of thing. But I could set up at seven o'clock on a Saturday night, give it the permissions, and then it just runs on its own. When I wake up the next morning, it's done.

And I haven't really drained any of the usage limits. But because that plan was already built, I didn't have to babysit it. I didn't have to build the plan as I was going. I built the plan and basically handed it off to a capable SEO person and said, go execute it, let me know what happens. Exactly.

And not to be a complete jackass, but this is something that I mentioned in my book, Almost Timeless. Uh, it's called plan big act small. You use a big model at some point to write a big plan, and then you can hand it off to a different model to implement and you can save yourself a lot of time and get a lot of things done. I do this a lot with coding where I'll use a model like Opus 4.6, which is a very smart model, but very expensive in terms of usage limits, off-peak hours, write the PRD, write the spec, write the implementation plan, and then I will hand it off to a much smaller model like Minimax M2.7 to actually do the implementation. So if you wanted to stay in one ecosystem, that's how you do it.

Follow Katie's structure of plan, strong plan, make a strong plan and then hand it off for off-hours execution when your your limits you're gonna hit your limits slower. Right. But the plan has to be there because otherwise you're just handing off this, you know, vague set of instructions to an autonomous AI system that goodness knows what it's gonna do to your system. Um we have a question. Uh to be clear, how could I also hand off between Claude and my Gemini workspace account so I can use those tokens and get my knowledge work done?

So uh that's a good question. We'll get to that in just a second. Um, the second thing that you'll want to do is install command line applications. So, command line applications, when you're using something like Claude Cobra, Claude Code, etc., they have what these called MCPs, model context protocol connectors, which are basically APIs for AI, but they are very token intensive. They use a lot of tokens, which means that they you hit your usage limits faster.

If you install command line applications which run locally on your computer and that that are not AI, that can access the systems you want, you the a tool like Claude Code or Claude Cobert can say, I will you pick up and just use the command line tool. It it runs the tool. The tool does all the work communicating data back and forth, and then hands the finished work product back to Claude Coworker, Claude Code, and thus you save a tremendous number of tokens, uh, something like 10x because the command line tool did the job and not the AI. So a couple of examples. Google Workspace has the Google Workspace CLI.

This is a tool that you can install, one command line tool that can access all of Google Workspace, Gmail, your calendar, your Google Sheets, your Google Docs. The other day, Katie and I were working on a business proposal, and it looked like crap. And so I said, you know what? I'm not going to sit here and make co-work click on things. That's a waste of tokens.

Instead, I said, Claude Code, use this command line tool, compare. Here's a good version of the document that with proper forming, here's the hot mess I'm handing you. Make the hot mess look like the good version. And it said, okay, I'll download this, I'll use this tool to download the schemas for both, compare them and say, Oh, yeah, this one is the hot mess because these reasons I can fix that and just and use that the command line tool to upload a new version. So this is literally 10x less usage because this tool, these these command line tools don't touch AI.

Um, but I have a question though, uh, or maybe more of an observation. I feel like with this and with you know anything else that you're giving AI access to, like this to me, I look at this, I'm like, ooh, you really should know what you're doing if you're giving this command line access to all of your Google workspace. Like, you don't want to just do that all, you know, willy-nilly. No, and when you do the first the setup the first time through, it gives you options like, do you want this to be read-only? If you're just getting started, say yes.

John's like, take all of my data, just go do it, whatever. Where'd my inbox go? I don't have any things I have to answer. Hooray. Um another example.

I was working on an MCP server for WordPress for the longest time. And then I realized, why am I doing this? It's completely stupid. Uh, WordPress has its own command line tool. You install this locally and tell your AI agent, hey, WPCLI is installed and it's logged into my blog, just go edit my blog this way instead.

And it will say, got it, I'll pick up the tool, I'll go and edit things. And you don't have to have co-work, you know, clicking on buttons on a page anymore. It can now programmatically access the entire site. Um, super handy. Saves token usage, right?

So any opportunity you can reduce token usage is better. To the question about how do you hand off between different systems? If you're using uh a tool like anti-gravity and co-work, you should always be writing to a folder on your computer that you have given permission for these tools to work in. And so if you plan well, like Katie was saying, and you have a good solid layout, you know, a document layup, you can say, Hey, Claude, write this new plan to my docs folder, my plans folder, and then flip over to anti-gravity and say, Hey, read my plans folder and execute this plan. And your disk drive effectively is the intermediary ground that these tools can pick up and hand off work to each other.

It's kind of like you know, it's the digital equivalent of passing notes in class from when we're kids, right? You just have a place where the notes live in some kind of sensible order that there's a common structure. Uh, I'll give you an example. So anytime I'm starting a new project, in fact, let me create a new folder on my desktop here, and we'll just call it um live stream new. No, but I start with a completely blank folder, and then we just create folders in here.

So we're gonna make these. This is my structure. Now, this is not everybody. This is this is you should do this for what works best for you. I have a data folder, which has where I put structured data.

I have a documents folder, which is where I put things like requirements documents, I have an input folder, which is where I put unstructured data. I have a logs folder where the the tools can write their logs. I have an output folder, which is where stuff comes out, I have a source folder, which is where code belongs, I have a temp folder, which is where like a playground, I have a tests folder. So when I'm writing software, uh it has a place to put its tests. I can just bring her up.

I have checklists for best practices. So this is an example uh for presentations. These are the rules that that as an AI agent will use to create a good presentation. Say this is what you should not do. Um writing song lyrics.

I have an orientation document that tells AI here's where things belong. Don't put things where they don't belong. Uh, and of course, and then for each of the languages, I have stuff like a guide document. So this is my one for Python that says, here's your 12 first core principles like never reinvent the wheel. If there's an existing Python package, don't write a new thing, just use the one that already exists.

It's stupid to be again stuff like this cuts down on token usage because it's already pre-baked, it's already proven, and you're giving it known good rules. So it doesn't have to think as hard. If you say, I understand what you want me to do. So the second second and third principles of of imagining AI usage limits is use command line utilities, used use non-AI tools as much as you can, and have good governance internally, even at the personal level. This is something I used to hate to do, but since I figured out how to automate it with Katie's guidance, I now it's now just baked into the process.

Um, if I may, I can show my version because I have some I mine is not structured like yours, and I actually make uh Claude build the folder for me. I don't build the folder anymore. I'm like, you do it because what I have on my desktop is this one master, it's up here, everything else is messy, but it's called Claude Co-Work Organized Files, and I just give Claude access to this one master folder. Every project I've ever worked on is in here. Uh it's I'm like, because I I don't have client work in here.

So everything I do is related to the company, so it makes sense for me to have everything grouped together. Whereas if I had different clients, I would set it up different uh in this, but because everything relates back to the company, uh, I have all of my reference and instructions, similar to what Chris was talking about. Um, you know, the things the uh I have similar things to what Chris has in the Claude folder where you have your outputs, your start here, your quick starts, your AI agents, so on so forth. Like there's a lot of stuff in here. But every time I start a new um project, the first thing I say to Claude is you're gonna create a new folder structure following what you have access to and name it, you know, this, whatever it is we're working on.

So like I make it do it now because I've already done it so many times and there's so much reference material already. I'm like, make that part of your plan. You do it. I actually Claude cleaned up my desktop for me too. It organized those files, uh, which was the greatest hack ever.

I don't know if it's a hack or it's really just a great idea, but I was like, can you do that? And it's like, I absolutely can. So stay tuned. It's gonna organize Google Drive next. And it's funny you mentioned that because I have a very similar piece of code in a shell script to organize my folders.

Again, because uh what I want to do is uh oops, I forgot to show my thing. Uh what I want to do is not use AI for this uh because it consumes tokens. So I guess what we're talking about reducing usage limits, the uh we want to use AI as little as possible, which sounds so uh so counterintuitive, but it's how you do it. So that's so number one, plan ahead. Number two, use command line tools.

Number three, have great governance locally for yourself as well as your team to have pre-baked stuff so that you're not having AI reinvent the wheel all the time and constantly chew up tokens. And number four is have the ability to switch providers and models. In AI, there's there's two concepts that are really important to understand. One is the harness and one is the model. The model is the engine, the harness is the rest of the car.

Clawed code, Claude Co-work, etc. is the harness. And then Opus or Sonnet or Haiku or whatever are the models, the engines. It turns out you could swap the engine pretty easily. And Anthropic has its own dialect in the same way that we, you know, if you've ever worked with OpenAI uh APIs, there's an open AI dialect that was sort of the standard in AI for a very long time.

Well, Anthropic has their own dialect that Claude Code and Claude Cowork speak. Other providers are saying, we now offer that dialect. You can use that dialect in addition and uh seamlessly swap your tools. So in Claude Code, um, one of the things that you can do in Claude Code is you can edit the settings file to switch to a different provider. You keep your Claude Code the way you like it, uh, with all your skills and all your plugins, and you just change the provider in the settings.json file.

And uh one of the providers that I use is Singapore based uh Mini Max. So Minimax M2.7 has that that model is about as smart as Opus 4.5, so the previous generation, which was the hottest things in sliced bread until January when Opus 4.6 came out. A model that's as smart as Open 4.5, but is dirt cheap, is is amazing to use. And Minimax offers what they call you know a coding plan. They call it the token plan.

You can see here in Minimax, there's my five-hour usage window, which I've used they they tell you like you have uh you've used 23% of this five-hour window, uh about put a thousand requests to through, and then your weekly limit is which resets in about three days, uh 12,000 out of 45,000 use. So in Minimax's documentation, they explain uh let's see minimax token plan. And so while he's pulling that up, one of the first questions we got was would love to hear how I can find a robust replacement for Claude Cowork when I run out of usage. So I personally have not tried Minimax. That's next on my list of things to install and uh play with.

But Chris, you're what I would probably call a power user at this point. Yes, that's right. And so Minimax gives you instructions. Here's how you modify Claude code to use the Minimax model. And it says, you know, do these things.

Again, this is something that for myself, uh, because I don't want to use AI to do this, and I don't want to just be constantly flipping back and forth to do this. Uh, I had uh Minimax and Claude build me a little utility, and the little utility just uh takes their the settings and it swaps them back and forth uh to say like okay, uh you switch because minimax has uh high usage hours too. Their high usage hours are typically between 8 a.m. and 6 p.m. Singapore time.

They're a 12-hour offset from us. So right now it's 1 a.m. there. This is the off-peak time. So their their high usage time is our we're at sleep time.

And so during the day, what I do is during the workday, I'm on minimax. And at night, I flip back to Claude because it's after hours after that window. So I can flip back and forth. Now, you can't do this with Claude Cowork. The Claude Desktop app does not have that.

However, there is an absolutely outstanding tool called Open Work. Open Work is from Open Work Labs. It is free, it is open source. And it is highly capable. I would say it is a near peer to Claude Cowork.

Remember what we said earlier. If you have a desktop folder that you say this is the folder I want you to work in, you can flip between anti-gravity and codex and claude code and cowork and now open work. In the settings file in the settings for here, there's connect your provider. And there are 133 different providers that you can choose from. Different companies, different coding plans and stuff like that.

So if you want to use you know Claude Pro and Max, you can use it there. You can see you know, mini uh coding plan or uh token plan, coding plan, and so on and so forth. You put in your providers. This also works, by the way, with local AI. So if you've got a beefy enough computer or your own little server, um, you can run like LM Studio or Cobalt CPP or Olama with a model like Quinn 3.5, and then you connect it to this, and then there's no payment because it was.

Now, it's not as smart as the big foundation models, but for simple stuff, it's smart enough. And then in this tool, you do exactly what you you do previously. Start a new local workspace, you choose your folder, you find out the folder that you want to work in, like your live stream folder, create your workspace, and then you have four uh three uh four agents to work with. There's sort of the default, just general doing stuff. There's the planning agent, which is a coding planning agent, there's a building agent, which is a coding implementation agent, and then there's the open work agent, which is their browser use agent.

So if you wanted to have it take control of your browser and do stuff, that's the agent to use. And down the lower menu here, of course, if you've if you've connected different providers, you can swap providers as you want inside open work. So I'm going to pause you for a second, Chris, because you just covered a lot of information. Um so first and foremost, uh, we have covered on previous live streams how to set up a local model. Uh, we've also talked about how setting up uh Claude desktop in general.

So you can go to trustinsights.ai slash YouTube, go to the so what playlist, you can find all of those episodes there. So we've talked about a lot so far. I just want to do a quick recap because this has been a lot of information. And this episode, if you're watching, you can replay on our YouTube channel as well and get all the information, the transcripts, everything. So first and foremost, everything I'm hearing says that's cool, but if you don't have a solid plan, if you don't have governance, if you don't have a clear process as to how this thing is done, then you're just switching contacts all over the place, and it's gonna be a bigger mess than just trying to use one model.

So that's number one. For Claude. It sounds like if you're hitting your limits with Claude code, then min max is my saying that right? Min Minmax or Minimax Minimax is a really good alternative that you can sort of switch back and forth because their peak hours, if you're in the United States, is likely not to align with their peak hours. So you can use that.

And then also perhaps schedule projects, you know, to work after hours and run autonomously in Claude during our peak hours. But again, it comes back to having really good planning and making sure you know exactly what to expect and what you're giving permission to. And then for Claude co-work, if you're running into peak issues, then this open source tool called open work allows you to have a near identical experience that you would in Claude Cowork. So if you're getting really good, really adept at Claude Cowork, then open work is a really nice alternative if you're hitting your usage limits, if you have really good planning and governance. John Wall, did you get all that?

There is gonna be a quiz. I'm ready. The uh a question I had though is I do, you know, one of the latest rounds of spam that I get is I get vendors all the time now asking me, Hey, do you need help managing your tokens? And we can do this. That just seems like it makes the problem a lot more complicated, and you're gonna have to give people access to everything.

I I've just completely been ignoring those. Is that is there any validity to any of that stuff? No, get out of here. Um someone said thank you for always helping us. What is that YouTube channel again?

Happy to provide it. Go to trustinsights.ai/slash YouTube, go to the so what playlist, and you will find all of our back episodes of the live stream, including this one once it's completed. Um, and then the other question, Chris, that we got was Does Open Work have the same VM concept as co-work? Um I'm trying to remember if open work does. Uh, I believe it uses a can its own container, but it's not a full VM.

Uh if I call correctly, it's essentially I want to say it's essentially either a window, uh a Mac container or a Docker container, is what it uses internally to partition itself so that it doesn't just blow up your system. That's yes, go ahead, Katie. Well, go well, I'm hoping also maybe you can back up a little bit and explain to those of us who don't know what do we mean when we say VM concept? Like we mean virtual machine, what do we mean? So Claude Co-Work.

So here's the big difference between Claude Code and Claude Cowork. Claude code operates in your system itself, which means that it can do things like delete things you don't want it to. Um, Claude Cowork creates a little Linux virtual machine that it operates in that is self-contained and actually creates it, destroys it, you know, uh on demand. And what that does is it prevents less technical users from accidentally doing things like deleting their hard drives uh through bad prompting. Um it's it is it is its own little environment.

Um open work, there's there's like four different or four or five different major open work open cloud core clones out there. Open work has is it can uses a container, which basically is sort of its own miniature thing, but it's not a full VM, it's not a full server, so it still can access stuff in your environment. There are trade-offs to doing this. Um and the trade-off is this, it makes it harder to run things like command line utilities from inside of a Claude Cowork or inside of an open work inside of its container because it doesn't have access to the local tools installed on your computer. So you have to provide that as part of like skills and things like that to simulate it where possible.

Whereas Claude Cowork, Claude Code can directly access the file system, which is much more dangerous, but also much more powerful because it can directly talk to local apps installed on your machine and pick them up and use them if you give it permission to. Again, with the caveat, not great for experimentation. Excellent if you know what you're doing, excellent if you have a plan. Highly recommend starting with the Trust Insights 5P framework. The goal of the 5P framework is to help you like outline a plan either really quickly or more in depth.

But if you're just starting with these tools, use the 5P framework to say, what are the different things I need to think through? You can even give the 5P framework to your the AI that you're using and say, help me think through a plan with this structure before we change anything, before I give you access to stuff, before you go off and running. I'm someone I love how well the autonomous feature in co-work works because I was I've been doing things like giving it access to our website to let it, you know, do all of those technical SEO fixes. I'm not gonna stay up until 3 a.m. doing it, but cowork doesn't care what time it is.

So like making sure you have that plan in place so that when you give it the autonomous access and it just does things and clicks buttons, it's not going to do something that you're like, oops, I didn't have a backup of my website. Guess I gotta start from scratch. Like you never want to be in that position. Exactly. Um, as does anti-gravity uh and codex supports the skill format.

So if you've built skills in Claude Cowork, you can copy paste them sometimes literally into open work. So like for example, we have the Trust Insights brand uh style guideline then the slide maker and our landing page refresh plugins that we've made for ourselves. Those you can copy and paste into the open work environment, and then it will be able to use them as well. Um if you are a technical you yes, go ahead, Katie. Sorry, I don't mean to keep interrupting, but it reminds me of questions that have come up.

So I got this question from a friend the other day when I was sharing sort of some of the work that I was doing, and she was asking about the file type for skills. So a lot of our files default to markdown files, so dot MD. And then she was like, Well, my Claude co-work is just making them as dot skills. And I couldn't give her a good response other than I think I, you know, I could be wrong, but I feel like it's easier to switch or to share a markdown file between systems than it is necessarily to share a skills file between systems, but I don't know that that's true. So there the architecture there should be in each folder have a file called skill.md.

They're all markdown files. Okay. Um, if it's creating a dot skill file, that's weird. That's that's not what that's not anthropic's own standard, uh, which would be kind of strange. So so basically the the standard for Anthropic, but also across different systems, if you're trying to switch context and system, is make sure that you have markdown files, dot md files, because my understanding from you Chris is that markdown file is the easiest file type for a large language model to read.

Easier than a text file, easier than a PDF. If you can, you know, if you have a bunch of PDFs and you can export them as markdown, then you're gonna be able to get the large language models to read them faster and not burn tokens by it trying to convert those files. Yeah, that's correct. Um minimax, this is the other reason to look at Minimax. When you look at the pricing, the plus plan that they have there when you build annually at $200 a year is roughly equivalent to the Claude Max20 plan.

So think about that. For $200 a year instead of $200 a month, you can get the same amount of usage out of Minimax that you can out of uh Anthropocodels because Anthropics models are very expensive. So if you were going to if you want to do a hybrid and you only want to pay like for Claude Plus or Pro, not Max, you could do your planning in Claude Pro and take those plan files, flip to your Minimax subscription and implement them with Minimax at a much lower cost um and reserve Claude just for that the stuff that requires the actual thinking and planning. That's a great way to to manage those usage limits because a lot of pro users found that with with uh pro the Pro Plan and Cowork, you hit your limit in 16 minutes. I mean, again, it comes back to what the heck are you doing in the first place?

Um, so I like I'm all for a hybrid model, I'm all for saving money, you know this. My first question is well, what are we doing that we're hitting the limits? Are we using the tools correctly? Or are we just kind of like playing around, or have we just not thought through, you know, what the overall, you know, what the company is using it for to you know necessitate bringing more tools into the stack. If we bring more tools into the stack, can we then you know put together some sort of an outline to say if you're doing this, use this tool?

If you're you doing this, use this tool. Because it really comes back to planning and governance for all of these things. How did I know? So this is generally where things are right now. Doing text to be perfectly honest, all the major models are are are great at it.

If you're doing coding, the smartest model is Opus 4.6. The second choice is Sana 4.6, and Minimax is the open weights model. That's really good. Um if you're doing video, Google VO 3.1, still the best. Sora 2.

I gotta change that because Sora's going away. Um then see that, and that I feel like that's a different discussion. That is a different discussion. Uh, and then the open weights model, uh, LTX 2.3 Pro just came out. Images, nano banana two, top of the top of the list.

Uh, chat GPT image 1.5 high. Flux 2 dev uh turbo is the best version of that for text to speech, 11 labs is is generally considered the best, although there's a lot of competition in that space now. Google second and voxtral uh which just from the mistroll just came out is open weights i actually am doing a test of voxtral right now to render an entire book as an audio book to see how it sounds um because if it turns out well that costs no money at all because it's gonna run on a Mac um for music Suno the the version 5.5 model just came out top of the charts murika version uh actually I shouldn't need to change that's V9 is out now there is no open weights model that can generate music incredibly it just isn't it for speech recognition NVIDIA's parakeet TDT2 is the best speech recognition model for voice recognition it is also an open weights model second is cohere transcribe there is no reason to pay for a uh speech recognition model none the open weights models are just so good now and finally a genta coworking claw co-work you know best of the breed open work is the second choice there so this is where things are as of today um i volunteer to take this and turn it into an instant insights for our website because I have a really good process and the whole thing will likely take me 10 minutes from you giving this to me to me getting it up and live on the website because we're gonna wait till 2 p.m because that's when Claude limits relax my point being once you have a really solid repeatable process you actually like yes still pay attention to usage limits but the amount of time you're spending doing things is so quick. And this is true. I mean, this is true of any sort of you know thing.

It's sort of like the first couple of times you should have figure it out. But if you build that repeatable process, this is true in software, this is true in life, this is true in like you know what we're talking about with AI, repeatable process is going to help you win. And I have a really solid, consistent, repeatable process for putting up things like new instant insights, new case studies, new landing pages, anything on the website. So yeah, hand it over. I'll get that up real fast.

And it's all gonna look consistent. Exactly. So the four things you need to do to manage AI limits. Number one, learn how to plan, plan well and write great plans locally on your computer so that you can hand off plans from one tool to the next. Two, have good governance, have as much pre-written as possible so that you're making the AI work uh work less.

Make sure you have command line tools installed on your system. So again, you're taking away token usage and handing it to things that don't need to be consuming tokens. Umber three is that internal governance and file and file structure. And number four is have great tools that you can swap in and out. So uh having the uh the building swap the model in clawed code, being able to swap the environment from clawed co-work to open work and so on and so forth, whatever you've got to work with, be able to swap tools in and out, which is part of your planning.

Because if you have a tool like Minimax, you build the great plan with clawed opus at night when lose limits are are more relaxed, and you implement with Minimax during the day. It's sort of like you know, what is it, coffee in the morning and martinis at night? It's the exact same idea. I mean, should probably drink some water in between the two. Maybe yeah, but that's how you work around these ages limits.

There's to your point, Katie. If you plan well, even on a budget, you can get a lot done. And I would say if you are on a budget, like if you were to say to me, all right, you know what? Uh, Trust Insights is no longer gonna pay for any AI tools, Chris. You're on your own.

If you were to say that, the Mini Max Plus plan for $200 a year, I would pay for that out of pocket. Like that's that is valuable enough to me, and it's capable enough at that usage level that I could I could make do with that. And I think that that's a really important distinction. It's not $200 a month, it's $200 a year. $16 a month.

Which is, you know, again, a lot of people are getting their budgets squeezed. So you need to be really thinking about that. So, like, why am I using the tools in the first place? Do I need all of these tools? Maybe even start with an audit of like, oh my goodness, what are all the tools I'm paying for?

Chris knows, like, once a month when I go through our Amex, I'm like, oh, we canceled that. That I why why am I still seeing that, sir? But it's it's very easy to sort of get swept up in the well, I just got I bought this one, and then I bought this one. I forgot about this one. Like, it's very easy to fall into that trap.

It happens to all of us. Audit your tools, make sure you're only paying for the ones that you're using. Make sure you have a clear purpose as to why you're using them in the first place, and then process, process, process. And speaking of process, uh, this question is when you ask Claude Cork to create the off-peak plan, do you explicitly take all the permissions? No, because you never want to say, hey, you don't you don't want to use YOLO mode.

YOLO mode goes very badly. Instead, I built a skill that says, here's the PRD, here is the spec, here is the permissions file for this environment. Alter the permissions file to permit as many safe operations as possible, and it will go in and it will rewrite the permissions file to say, you want to read, you want to search the web, you want to do this, you're allowed. You don't need to ask the user for it. So it stops the asking for permission every you know every every six seconds.

That skill, which you can build in the claw is or the tool of your choice, can then change the permissions, but you've got to have the PRD in the spec first because it doesn't know what to permit until you have those two documents. And to Katie's point, it doesn't just have to be code. I write PRDs and specs now for everything because it's easier to do that and then hand it to the rest of the ecosystem to execute on. We know I'm the most risk-averse person on our team. So I still set up the project and manually grant the permissions, but once that's all set, you know, the autonomous project is off and running.

But I still like to do that double check, me as the human. So it really comes down to, you know, how complex your project is, what it needs access to, and your comfort level with risk. Um, so John, what's the first thing you're gonna do? The first thing I'm gonna do. I gotta load Claude cowork and get it to work.

I have the DMG in my desktop. So that's I am at like square one. All right, John, we're gonna we're gonna work on this with you. We're gonna get it set up. Uh, because I'll share with you offline what I've been working on that does uh affect you.

Yep. All right. The question about uh the PRD permissions thing, yes. Yes, uh I put it in our free Slack group, Analytics for Marketers. If you go to trust and/s.ai slash analytics for marketers, you'll get you'll go in there and there's a link to the GitHub repo if you want that to that particular skill because it's it's pretty straightforward.

So all right. We covered a lot. Again, highly recommend um if you want to know what we covered, if this was a lot, it was a lot for me and I was in it. Go to TrustInsights.ai slash YouTube. Not right this second, but right you know in a little bit we'll have the YouTube video up on our so what playlist and you can get the transcript and all the things that we covered, including Minimax open work, which I'm actually going to probably install uh over the next couple of days because I'm curious to try that.

I'm a Claude co-work uh heavy user so I need to sort of see what the alternatives are and then yeah make sure you have a plan and some good governance and uh apparently a cup of coffee and a martini. Exactly coffee in the morning martinis at night. All right thanks for tuning in folks and we'll talk to you on the next one. Thanks for watching today. Be sure to subscribe to our show wherever you're watching it.

For more resources and to learn more, check out the Trust Insights podcast at TrustInsights.ai slash TI podcast at our weekly email newsletter at TrustInsights dotai slash newsletter. Got questions about what you saw in today's episode join our free analytics for marketers Slack group at TrustInsights.ai slash analytics for marketers see you next time