Claude Skills: The NEW Way to Build AI Agents (Live Tutorial)

In this episode, Amir takes us through how to use Claude Skills to build digital employees. We cover practical demos including an A/B testing idea agent, marketing insight analyzer, and a live build of a tweet-to-newsletter converter. You'll learn what Claude Skills actually are, why they represent the biggest leap since sub-agents, and how to build them yourself—even if you've never written a custom AI workflow before. Timestamps 00:00 – Intro 01:05 – What are Claude Projects 02:40 – Sub-agents in Claude Code explained 03:34 – Introducing Claude Skills 05:58 – Context rot and the performance degradation problem 08:01 – Why matter Claude Skills Matter 11:08 – Building a UTM link generator with Artifact Builder 17:41 – Claude Skill Demo: A/B test generator for website optimization 20:32 – Claude Skill Demo: Marketing analytics insights from campaign data 23:40 – Building a Claude Skill: Creating a tweet-to-newsletter converter skill 30:32 – Final Thoughts on Claude Skills 30:58 – Why AI adoption is falling and how better prompting solves it Key Points Claude Skills are automated workflows that apply globally or per-project, pulling context only when relevant to specific tasks Skills solve the "context rot" problem where too much context degrades LLM performance and increases hallucination You can create custom Skills using markdown files with instructions, reference documents, and executable scripts The tweet-to-newsletter converter built live demonstrates Skills' ability to match tone and style with minimal training Poor AI fluency and prompting—not the tools themselves—explain why enterprise AI adoption is declining The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ Boringmarketing - Vibe Marketing for Companies: boringmarketing.com The Vibe Marketer - Join the Community and Learn: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND AMIR ON SOCIAL Humblytics: https://humblytics.com/?via=community X/Twitter: https://x.com/amirmxt Youtube: https://www.youtube.com/@amirmxt

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Greg Isenberg?

  In this episode, Amir takes us through how to use Claude skills to build digital employees. We go through A B testing idea agent, marketing insight agent, and then we build one live together. You're going to learn about what Claude skills is, why it's the biggest thing to happen since subagents, and how to actually build them yourself.

• 0:30Greg Isenberg?

  Amir, what are we learning today?

• 0:32Speaker 01

  Today, we're going to talk about Claude skills. I'm going to tell you what they actually are, how they're different from projects and subagents in Claude, and why this matters and how you can actually apply for work.

• 0:42Greg Isenberg?

  Okay, and by the end of this episode, are we going to be able to apply Claude skills?

• 0:47Speaker 01

  100%. I'm going to show you, first I want to talk about what it actually is and why it matters, but I'll show you how to use existing skills in Claude that they just came out with, and how to create your own and how to apply for your work. So whether you're in marketing, in data analysis, or any sort of document creation, you can actually use skills to do that.

• 1:03Greg Isenberg?

  Cool, let's do it.

• 1:04Speaker 01

  Cool. So first thing is, I want to talk about Claude. So not a lot of people are familiar with Claude projects, and I want to talk about what that actually is, and why it matters, and how it's kind of related to skills. So within Claude AI specifically, you can actually create projects, and they're essentially workspaces with a set of custom instructions. So this is a system prompt, and it has relevant context, memories, and tools. So say, for example, you're part of a broader marketing team, and you want to create a project that will have a set of instructions to analyze marketing data, for example, or generate a newsletter. And you want it to connect to specific tools, have relevant context and files.

• 1:47Speaker 01

  So this could be a glossary of terms used within your organization, your brand guidelines, depending on the task it is that you wanted to do, and then also have memories generated from the chats that you have within that project. So it's really great for collaboration with other team members. Now, you can also use it yourself as well, but really, the ability for you to create repeatable tasks and do a certain set of instructions with external tools and data. So if I'm in a marketing team, this is something that I want to look at, and essentially you think Claude, share with my team members, and create projects around it. All right, so the only thing with projects, I would say that it's important to... One, work with your team members to actually refine the system instructions and then always have relevant context files. As your business changes, the data changes, you need to update it and you have to go back and constantly update these context files.

• 2:34Speaker 01

  And I'll talk about why context is important in this specific session and kind of how it ranks our working skills. Now, the next part of it is subagents. With subagents, this is more relevant in Claude Code specifically, and I actually use subagents in Claude Code to spin up multiple agents. And multiple agents are really great at breaking down complex multi workflow tasks into individual tasks with specialized agents. So what does that mean? Say, for example, you're building a very complex feature and you want to delegate the front end to one agent and the back end to another. So within the chat, you can actually spin up these agents to say, hey Claude, create an agent that'll work on the front end using this set of rules. And then create another agent to spin up to do the backend for it.

• 3:17Speaker 01

  And what's interesting is the context is isolated to that conversation window. And so whatever context is provided or gathered in that conversation is actually used as an input. But those agents have a set of system instructions as well. Now, where things get interesting is skills. And I want to talk about kind of why this actually matters. Skills are automated workflows and tasks that you can apply globally at a project or individual level. So whether you're in an existing project, you have a set of system instructions, you can use skills, which is an add-on or augmented skill set

• 3:59Speaker 01

  within that project or individual chat, and it can do a set of tasks. Create documents, create PDFs, analyze documents. It can actually help build MCPs for you. You can use skills to create other skills or create visual art as well. Now, when do you actually use this? It's for very specialized tasks based on the constraints and guidelines and steps built by you, the expert. I think it was Karpathy a couple of days ago. He had an excellent analogy where it's like AI is essentially your coworker or someone that like reports to you. You want to train it, you want to build the guidelines. This is not verbatim, but like basically what he was trying to say was yeah, it's someone that you work with and you can kind of build the constraints around it and guidelines on how you want it to respond to you.

• 4:45Speaker 01

  And this is kind of similar in some nature. You can create, for example, let's say you are a paid media expert and you run campaigns for your clients and you want a very detailed analysis on your visit to booked appointments and what the conversion rates look like and how that attributes to the different channels you have and what's performing better than the other in terms of campaigns. You can create a skill that can follow a set of custom instructions, but also scripts that you can build out yourself to analyze that data. And I want to circle back later on and why that actually is important. But what's also interesting is that it actually only loads context when it's relevant to the task. So when a project, oftentimes you have the LLM that's determining which context to

• 5:30Speaker 01

  retrieve and add into the conversation window and reference it. But in this instance, it's only based on the judgment of the task, whether or not it should pull relevant context and it's just relevant to actually what you want to get done. So I would say the key takeaway here is that it's repeatable instructions, it's laser focused on a set of tasks, it pulls in context as is needed and it has the ability to run scripts or run code to perform specific functions. Why this matters? Because there's a paper, great paper out there called, talking about context rot and how essentially talks about how to do effective prompt engineering and how the right amount of system prompts from, you know, very detailed to vague and the right amount of context

• 6:15Speaker 01

  has a huge impact on performance. And as you add more context, you essentially could be, you know, I don't want to be caught on this, but potentially be like degrading performance from the LLMs and likely to lead to more hallucination.

• 6:27Greg Isenberg?

  Sam Altman, the co-founder of OpenAI, just said that it is the era of the idea guy, and he is not wrong. I think that right now is an incredible time to be building a startup. And if you listen to this podcast, chances are you think so too. Now, I think that you can look at trends to basically figure out what are the startup ideas you should be building. So that's exactly why I built idea browser.com. Every single day, you're going to get a free startup idea in your inbox, and it's all backed by high-quality data trends. How we do it, people always ask, we use AI agents to go and search, what are people looking for? And what are they screaming for in terms of products that you should be building?

• 7:11Greg Isenberg?

  And then we hand it on a silver platter for you to go check out. We do have a few paid plans that take it to the next level, give you more ideas, give you more AI agents and more, almost like a chat GPT for ideas with it. But you can start for free, idea browser.com. And if you're listening to this, I highly recommend it. I mean, makes sense, right?

• 7:36Speaker 01

  Exactly.

• 7:36Greg Isenberg?

  The more context you have, the less likely you are to hallucinate.

• 7:42Speaker 01

  Well, the more, well, yes and no. The more context you have, you're less likely to hallucinate, but the right amount of context. So it's like, kind of like a coworker, like, do you want to give them all the information or just the right amount so that it doesn't bombard them to get the right task?

• 7:56Greg Isenberg?

  Exactly.

• 7:57Speaker 01

  So that's, that's what I would really call break it down into. So I'm going to go through some examples, but I want to talk about the importance of scale and why it's actually solving a real problem that I have faced myself. So with custom skills, how it works is that you essentially create this markdown file that explains exactly what the skill is and what it does. And you can actually create reference files that it can reference back into for additional context. So say, for example, you create a skill that applies XYZ's company brand guidelines to presentation and documents. And this overview, essentially, you know, this skill overview has a set of tasks and instructions that follows, but you can also

• 8:40Speaker 01

  have an additional document as a reference that is an example, existing brand guideline document that it can reference. And it's not, it's only pulling it when it needs to.

• 8:51Speaker 01

  You can take another layer and you can essentially create custom scripts as part of that skill. Now, there's a great documentation by Anthropic on this and they talk about kind of how to write good skills and descriptions. But what's interesting is that when you are using a Claude project and you have MCPs or tools connected, connectors connected, the LLM is determining which tools to call based on your instructions and how to perform that task. So say for example, you have a raw output of your meta campaign ad data or your Google Ads data. And you have a project in Claude that says like it's a market analyzer.

• 9:34Speaker 01

  I want you to, your instructions are to analyze this data and give me insights. The LLM is determining how to, like the model is determining how to actually look at the data and perform insights. And it's non deterministic in a way, right? Like it's, you know, it can look at it differently every single time. And you're not giving the right guidelines on how to actually take the data and analyze it. And I've seen this firsthand, actually working with a lot of clients where like, you know, a director of rev ops is looking at churn data, new subscription data, and they'll put the file into the Claude project and it's not giving the right output of insights they're looking for. How this gets interesting is you can actually create scripts that are very specific.

• 10:15Speaker 01

  So say for example, if you wanted to have a very set of strict guidelines on how it should actually run and analyze the data, then you can create that within the skill itself to say, I want you to look at column X, Y, and Z, multiply by this, divided by that, to the power of this, to give me this insight. That way it's actual functional code that's running this and it's not deterministic, non deterministic by the model itself. So, so yeah, that's kind of the beauty of skills itself where you're able to really bound or create the boundaries on what it should actually work towards for, yeah, for, for like building out these skills.

• 11:00Speaker 01

  So yeah, you can essentially have metadata with it, resources and code. You can load it as needed and it kind of breaks down exactly how you should write these skills. Now let's jump into some examples. Let's do it. This is the fun part. How do you actually apply this? So the first one we're going to go through is an artifact builder. So you can actually go to Claude and it's preloaded with some existing skills. So we're going to go to capabilities and essentially you'll see there's some existing skills that are preloaded. So I have created these two ones right here. We'll go through them, but I want to show you the ones that are already in there. So you can have an artifact builder, an MCP builder and a skill creator. So it's very meta. You can create skills with skills.

• 11:42Speaker 01

  So we'll go through an artifact builder one and I'll show you an example of what that looks like. So say for example, you want to create a tool that is relevant to marketers. Marketers, you know, when they run campaigns, they always have to have UTM links to do proper attribution back to their data to see, okay, which campaign was driving the most and when they're seeing the analytics. So here, you know, I have added the artifacts builder skill. Please create a UTM link generator for my marketing team. So what's happening here is that Claude is now going to reference that skill specifically that we have defined.

• 12:26Speaker 01

  I'll show you what that skill looks like and essentially it's reading the documentation to understand how to build components. Artifacts are essentially these like live apps within Claude itself that you can create. Very functional web apps and you can also share with your team as well. So what it's doing is it's actually referencing that skill here and now creating an artifact slash web app of a UTM link generator that marketing teams can use. And you can actually just share this with the rest of your team as well, or your entire team can use this as well. I mean, it's literally a web app. It's literally a web app, but what's interesting is We're now creating a set of specific instructions and skills, adding a skill to this L M now that no one has to follow this versus before you're saying, hey, code this web app.

• 13:09Speaker 01

  And it's kind of, you're not really defining the guardrails or the parameters of what it should do.

• 13:15Greg Isenberg?

  And what happens is people get frustrated that they're not getting the right result.

• 13:19Speaker 01

  Exactly.

• 13:19Greg Isenberg?

  And then they're like, oh, you know, AI doesn't work for me.

• 13:22Speaker 01

  Exactly, exactly, exactly. So this is where it gets interesting, right? Like you, as an individual, you have the opportunity to work with Claude and skills to build exactly the skill you're looking for to do. That's a repeatable task. So if you, as a marketer, are doing weekly tasks of reporting, create a skill that can actually help you with that. And just explain to it in terms of what you're looking for, what you need. Be very detailed if you were to assume that you're hiring someone else to do it for you.

• 13:54Greg Isenberg?

  Yeah, I mean, it really is. I mean, it really is thinking about AI as a teammate,

• 14:04Greg Isenberg?

  especially a junior teammate, that you have to really give it guardrails and really give it context. Because that's how you would, you know, if you hired someone junior, you would be like, Kate, these are the tools that you're going to use because they don't know the tools they're going to use because they're new. This is the context that you need to know about our business and how we operate. And then you kind of drip feed them. You don't want to overload them, right? Because then they're gonna, they're not going to remember everything or they might, you know, it might, yeah, it just might be overwhelming. So you drip feed them the context over time.

• 14:38Speaker 01

  Exactly. But it's also interesting is if you start now, as these models get better and as the toolkit expands, you now have this like history of like training and reference and metadata and memories that you've created over time now. Then, so like, someone like me who uses Claude a lot, I now have a lot of pre-context of like memories and experience with building these projects. Now I know exactly how to use skills and apply it here. So I think that's where it gets really interesting. I generally think skills is probably the, a huge problem solver for a lot of problems I've seen firsthand working with people. Like I've worked with a lot of teams right now that have actually like a lot of go to market teams that have used Claude as part of the workflow. And the

• 15:18Speaker 01

  number one feedback I get is the output was not on what I expected, or it's incorrect. There's two reasons for that. One is The prompting is not good.

• 15:30Greg Isenberg?

  The prompter.

• 15:31Speaker 01

  The prompter. The problem is them. But the latter of it is, it's also the same, you can prompt, you know, I worked on with them on setting the right guardrails, the prompts, the access to tools, the right retrieval of context, and it still doesn't get it just right. And I think this is where skills come in and solves that problem, where it's just that task. So you now have an artifact that's fully functional and working. You can actually share with your team members if you wanted to, and you can essentially like provide a URL like humblex.com or ideabrowser.com, and it will append the rights like Google and CBC, you know, was it Black Friday, Cyber Monday? Yeah, something like that. And it'll actually

• 16:12Speaker 01

  create those. I will append it for you. I don't know why there's a clear button. It should be a submit button.

• 16:18Greg Isenberg?

  You can also sell this to other people as a product, right?

• 16:23Speaker 01

  Yeah, so I think Claude, in collaboration with someone else, created this like repository of skills. I don't want to butcher the names, I'm not going to say it. But basically, there is a directory of some sort with skills and plugins, because they recently came out with plugins as well, which is like a collection of context and tools and skills and prompts, all in one that you can install for your Claude workflow. So there is a huge opportunity for people to sell skills, absolutely.

• 16:50Greg Isenberg?

  Okay, sorry. What's the difference between plugins and skills?

• 16:53Speaker 01

  So, yeah, yeah, plugins just came out last week, which is like a plugin. You plug it in, and it has ancillary features, MCP access, context, system instructions, and I think skills now, I'm not, don't quote me on this. Claude's been shipping. Claude's been shipping. I'm having trouble keeping up. You know, when I was building this out, when I was writing this out, I was like, I'm trying to understand what skills is. And as I was actually building with it, I was like, it's clear to me. Because initially, my gut reaction was, this is overcomplicating it. How's this different from projects?

• 17:23Greg Isenberg?

  Right.

• 17:23Speaker 01

  And now I understand why.

• 17:24Greg Isenberg?

  Okay.

• 17:25Speaker 01

  Yeah. So, yeah, so we essentially, you know, HTTPS, ideabrowser.com, we can go Google, CBC.

• 17:36Speaker 01

  Black Friday, Cyber Monday, and then generate the URL and we have a URL. Boom. So that's one use case. Let's make it more interesting. I am interested in finding A B testing ideas for my website.

• 17:47Greg Isenberg?

  Yeah.

• 17:48Speaker 01

  So I have a skill that essentially looks at A B test generator. And what it does is that you provide a URL and it will come up with headlines or experiments for you to run for your website to increase conversions. And it actually, the skill, I created the skill using the skill creator. I said, I'm going to give you a URL and you're going to run a framework on actually how to run good A B tests for me. So we're going to test this and see what it looks like. And then I'll show you an example of how to create your own skill as well. So, hey Claude, I have just added, I have added the A B test generator skill. Can you run, can you provide me with A B experiment ideas for humblytics.com?

• 18:29Speaker 01

  And what this will do is here, because I have access to an F C B called Firecrawl, it would actually use Firecrawl to scrape the URL, the page and the contents, and then come back with a very clear framework on experiments to run. So while that's running, maybe I'll just show you an example of what that actually looks like. And essentially it looks something like this. So it gives you an experiment pipeline, impact, confidence, ease, I C E score. And you know, it was actually a really good one. I actually did it right before this call, before the session today, was it asked me to,

• 19:08Speaker 01

  it told me to actually test shifting the case study that I have above, one section above. So it's like hero section and then case study. Go to Amelia's social proof. And I was like, damn, that's a good idea. Why am I showing the features when I should do the social proof? So I'm running an A B test right now to see which one is likely to drive more conversions. And signups. So that's interesting. Like it really breaks down exactly the control, the variants, the headlines you should be testing. So experiment number one, experiment number two. And if I really wanted to, you know, just take this, put it into my app and then run, run through an experiment.

• 19:45Greg Isenberg?

  You know, it'd be really cool if you can automate this. So that you know, every month, send me a report.

• 19:51Speaker 01

  Yeah.

• 19:51Greg Isenberg?

  What's changed?

• 19:52Speaker 01

  Exactly. Exactly. So if you really want to, yeah, you can. You can probably write a skill that I wonder if you can, I wonder, I wonder if you can already do that today where you write a skill that writes a script that automatically sends you a report every single week or every month. Yeah.

• 20:08Greg Isenberg?

  Why not?

• 20:09Speaker 01

  Yeah. Yeah. So yeah, you know, I am then plugging my app and say, we do that automatically in our app. So every week we have like four sets of subagents that go through your website and give you insights from like a copy, conversion, marketing, like a designer as well. So every week and then we give you like an optimization score. So similar, kind of similar approach here, but I think doing that within cloud is actually really interesting as well. Now, what I really, really, really want to show you is the problem I've been trying to solve for the past couple of months with these companies I've been working with, which is take data and give me the insights that I actually want to look at. It's such a repeatable task and it's so important that I think, I can't confirm

• 20:50Speaker 01

  yet, Skills has probably solved that problem for me now, in a way. So I uploaded a file called Traffic Analytics. It's just basically like a CSV of just a bunch of campaigns and you know, revenue data and whatever. And I was like, I need some insights on this. And that's what really matters to a lot of people in terms of just the costs go down, the CVC go up, down, what does a trial conversion look like, X, Y, Z. So I, I provided a file and it references Skill and has a set of scripts within that Skill to then do a comprehensive analysis of the data, the traffic data. So overall performance, your total spend was 400K, your revenue was 854K, net profit, conversions, which channel did better than

• 21:35Speaker 01

  the other. So you have a clear idea. And I'll be honest, like I, you know,

• 21:42Speaker 01

  You know, I am gonna be honest, but I would say that I would say that if I had done this through a project and I just uploaded a file with some instructions without running scripts, it would have probably hallucinated some of the data.

• 21:57Greg Isenberg?

  That's what I was gonna say, cuz I, when I look at this, this feels, this, if this wasn't in Claude and I had a product manager send me this, I'd be like, yeah, you know, this feels like that level of fidelity. It just, you know, it just, it's.

• 22:18Speaker 01

  It looks right.

• 22:19Greg Isenberg?

  It looks right. I can confirm cuz I don't know the, I didn't look at the Excel.

• 22:23Speaker 01

  Yeah.

• 22:24Greg Isenberg?

  I'm just, just looking at it, it looks right.

• 22:26Speaker 01

  Yeah, it does. Yeah, exactly. So, and I'll show you what it looks like essentially within the breakdown of the skill itself. So, skills, what you do is you have the actual skill.md file itself. So, this again is a breakdown of what the skill is, the scripts it should run, and then, yeah, like generate data for 90 days, generate data for 7 days, generate data for 10 campaigns, and then what the structure should look like. So, you can actually use this to define it. And, you know, if I wanna take a step further, that I can use cursor to then update the skill itself. And I'll show you an example of how to create your own skill. And then you can also reference files. So, you can see here it says, "See references, metrics, MD for detailed metric definition and typical ranges."

• 23:07Speaker 01

  So, if we wanna go back into references, we can see what metrics MD has, which is all the, you know, definitions or glossaries. So, as a marketer, you get to define what these are, and you should be doing that. So that, you know, when you run these scripts and skills, it gives you exactly what you need, instead of getting the LLM to actually do it for you. And then the scripts are made by Claude itself, where it's running a Python script on, you know, calculating all this for you. So, it's accurate in some way or another.

• 23:36Greg Isenberg?

  Yep.

• 23:38Speaker 01

  Cool. Let's see where we are. Yeah, so let's now create, we've gone through A/B testing ideas, we created an artifact, we got some marketing insights. I think we should now just create our own skill. Do you have anything in mind?

• 23:51Greg Isenberg?

  Tell me if this is possible. So, I tweet every day, and I also have a newsletter. And every single week, I

• 24:04Greg Isenberg?

  Basically, I use my tweets, like if it rips on Twitter, I'll kind of expand on it on my newsletter.

• 24:12Greg Isenberg?

  I have a specific type of style how I write on my newsletter. So what would be really cool, like this is something I would hire for potentially, like almost like a ghostwriter. So is it possible to have a skill that basically like looks at my tweets and turns it into long form content that I can review and be the editor of?

• 24:35Speaker 01

  Okay, let's try.

• 24:37Greg Isenberg?

  Let's find out.

• 24:38Speaker 01

  We're doing it.

• 24:39Greg Isenberg?

  You're like, maybe.

• 24:42Speaker 01

  Yeah, no, absolutely. I think, I think we can figure it, we can, we can try. So, hey Claude, I just added the skill creator skill. So we're using the skill creator to do that. Can you make me a skill that takes an existing tweet provided by the user and turns it into long form content for LinkedIn?

• 24:55Greg Isenberg?

  For?

• 24:57Speaker 01

  For newsletter.

• 24:57Greg Isenberg?

  Newsletter.

• 24:58Speaker 01

  For newsletter.

• 24:59Greg Isenberg?

  Yeah.

• 24:59Speaker 01

  So I would, I think what I would do in this scenario is making sure that we have a reference file.

• 25:07Greg Isenberg?

  Right.

• 25:07Speaker 01

  Of your existing newsletter.

• 25:09Greg Isenberg?

  I would need to, and would you need like an export of all my tweets?

• 25:14Speaker 01

  Exactly.

• 25:14Greg Isenberg?

  Yeah.

• 25:15Speaker 01

  Yeah, yeah. So maybe we can try to do one example one right now and then, and then see. But ideally, what I would do is actually, I actually have this. I have an automated bot that looks, has all my tweets and then finds the most viral ones and tries to like expand on it. So ideally, we would export all of your tweets.

• 25:31Greg Isenberg?

  Yeah.

• 25:31Speaker 01

  And then.

• 25:32Greg Isenberg?

  And then, you know, we would, in order to keep it updated, we would need to make sure that we're, you know, constantly.

• 25:40Speaker 01

  Updating the reference file.

• 25:41Greg Isenberg?

  Yeah.

• 25:41Speaker 01

  Yeah, exactly, exactly. So while that's running behind the scenes, I'm going to scrape, I'm going to get some examples of every posts on Twitter.

• 25:50Greg Isenberg?

  Yeah. That's me.

• 25:53Speaker 01

  Okay, so what's a good tweet?

• 25:56Greg Isenberg?

  Yeah, you find a tweet that like speaks to you and then we'll.

• 25:59Speaker 01

  Okay, I like this one actually, it speaks to me.

• 26:01Greg Isenberg?

  Okay, pricing?

• 26:02Speaker 01

  Yeah.

• 26:03Greg Isenberg?

  Yeah. I mean, this is a perfect one because it was too long for Twitter.

• 26:08Speaker 01

  Yeah.

• 26:08Greg Isenberg?

  But I posted it anyways.

• 26:13Greg Isenberg?

  But if I did, even if I did this on a newsletter, I would totally expand on this.

• 26:17Speaker 01

  I got you.

• 26:18Greg Isenberg?

  And then.

• 26:21Speaker 01

  For the newsletter, where's the best, I mean, I

• 26:24Greg Isenberg?

  I don't even know if you can

• 26:26Speaker 01

  Yeah, how do I

• 26:26Greg Isenberg?

  Find it. Go to, I think Greg Isenberg dot C K dot Greg Isenberg dot C K dot com.

• 26:33Speaker 01

  Alright, cool. So let's take this actually and

• 26:38Speaker 01

  we're gonna copy this and then create notes.

• 26:46Speaker 01

  Export this example newsletter.

• 26:50Greg Isenberg?

  Export it as a markdown, right?

• 26:52Speaker 01

  Yeah, as a markdown. Exactly. Exactly. So we're going to go back to Claude now. So now that we have an example tweet, post and example newsletter, we're going to

• 27:03Speaker 01

  up, we're going to upload that as a reference file in there as well. So what we'll do is let me just drop this in here. Add these files as references. You know, what's interesting is I actually gave you a zip of the scale for you to upload. And we're saying now like add this as a reference into that scale.

• 27:21Greg Isenberg?

  Okay, stuff is happening.

• 27:24Speaker 01

  Things are happening. We're seeing instructions. Yeah. So we're adding instructions to similar to I showed before where there's instructions to reference the file in the folder. We're going to see a zip now with a folder called references. And if you open it up, you'll see these two examples in there. Boom. So now we can essentially download this and re-upload it back into Claude.

• 27:44Speaker 01

  There you go. Sweet. Okay. Tweet to newsletter. And we're now going to go to settings, capabilities, upload a scale, and we're going to upload tweet to newsletter. And now we're going to write the skill. Try and chat. I just had skill. Can you turn this tweet into a newsletter format? And you're going to be the judge of this. Tell me if you think it's good.

• 28:10Greg Isenberg?

  Yeah.

• 28:12Speaker 01

  So we'll go back. You know, we already had it, but I'll just copy paste this to see how it works. Okay.

• 28:21Speaker 01

  And we'll go Claude. Let's see what happens.

• 28:27Greg Isenberg?

  I'm honest, I'd be surprised if this crushes it on the first try. Cause think about how, I don't know, I'd be surprised. I hope it does.

• 28:39Speaker 01

  So I'm, I'm, I'm very curious. Like this is, we're doing this live and I'm curious to see how it actually comes out and I want to get your honest take on it, right? Because for me, at least from a data standpoint, to get the insights, I think it's interesting. Cause like there were challenges with projects before to get the right insights. So

• 28:56Greg Isenberg?

  Honestly, this is fire.

• 29:00Speaker 01

  I mean, so tone of voice. So we just did this in one shot, but if we really wanted to, we would take all of your existing tweets, all of your newsletters and then use that to generate a, like a style guide or tone of voice. And then kind of refine this, but as a starting point, it's not bad.

• 29:15Greg Isenberg?

  As a starting point, it's not bad. And I'll, I'll even take it a step further. Like this is

• 29:22Speaker 01

  It's actually not bad.

• 29:23Greg Isenberg?

  Really good.

• 29:23Speaker 01

  It's actually not bad at all.

• 29:25Greg Isenberg?

  Until next time, keep building and keep raising, not keep raising.

• 29:29Speaker 01

  Yeah, we don't.

• 29:30Greg Isenberg?

  You know, but keep building. I like

• 29:34Greg Isenberg?

  forward this to a founder who's been sitting on the same price point for too long. Like I like that. I think that's really smart, right?

• 29:40Speaker 01

  We talked about product market fit. We should talk more about

• 29:43Greg Isenberg?

  Pricing market fit. Like that's a, that's a banger.

• 29:45Speaker 01

  That's actually a banger.

• 29:46Greg Isenberg?

  Yeah. Like if I tweeted that as its own one liner, like that probably would do really well.

• 29:52Speaker 01

  Oh, until next week. Yeah, I think so.

• 29:54Greg Isenberg?

  Yeah.

• 29:55Speaker 01

  Yeah. A hundred percent. Now it would've been interesting if you're like, if you, you know, we could technically say, okay, now go scrape like tweets and embed it in there.

• 30:02Greg Isenberg?

  Yeah.

• 30:03Speaker 01

  That'd be really cool. And the cool thing is you can actually create skills now.

• 30:06Greg Isenberg?

  Dude, this is crazy.

• 30:08Speaker 01

  I actually, yeah, like this, here's where it gets interesting though, right? Cause you can now create skills that generate visual graphics. Cause that's, that's a thing now.

• 30:17Greg Isenberg?

  Yeah.

• 30:18Speaker 01

  So you can, you don't have to do MCP calls like Canva or anything like that. You can programmatically create these visuals. So we can update the skill to say, hey, now add images as well in there.

• 30:27Greg Isenberg?

  Yeah.

• 30:28Speaker 01

  This is pretty good.

• 30:30Greg Isenberg?

  All right.

• 30:30Speaker 01

  Yeah. So, you know, we covered why projects matter, how it's different. I think.

• 30:37Speaker 01

  From skills and I think we got a good idea that skills are probably more deterministic in terms of what you wanted to do, in terms of how you wanted to find the skills and you can now do programmatic code in there with MCVs and tools and how impactful context is.

• 30:53Greg Isenberg?

  Yep.

• 30:53Speaker 01

  And you know, essentially how it differs from everything else. So we've covered some use cases as well. The last thing I want to talk about is kind of just like, you know, I saw this report, I don't know if you, if you saw it from Ramp where they were tracking subscriptions for like different AI tools and they saw that there's a dip happening. And they're saying, there's getting stickier in enterprise, but AI is off ramping and it's not as sticky as we want it to be because cost is coming down. I actually want to say now with what we're seeing with skills and all the education and awareness around prompting, we should be able to solve that gap because the reality is a lot of companies are investing in AI and there's reports now saying that it's not actually being as productive as we thought. The issue is, I think, prompting and context.

• 31:33Greg Isenberg?

  The issue is people.

• 31:34Speaker 01

  The issue is people.

• 31:35Greg Isenberg?

  Not AI.

• 31:36Speaker 01

  Yeah, yeah. That's the reality, right? There isn't enough AI fluency and education around how to actually do prompting. People like write, you know, build me a SaaS, one million AR, don't make mistakes, you know? And then the reality is like, no, no, you gotta give the right amount of context and do some prompt structure. And I think when it comes to Anthropic, they do a really good job of not only building with intention, but creating the resources, the education to help people actually become more AI fluent and giving them tools to do that. And they're very deliberate with what they create and it's actually real problem solvers. Like, I've never seen a company so dialed into customer feedback and just creating something around it. It's almost like they heard me in conversations about what issues I'm having

• 32:20Speaker 01

  and, you know, why skills matter. So the net of this takeaway is AI adoption may be falling and the adoption rates may be down for this month or this past quarter. I think part of it is just because companies don't have the right resources and the people to build education on AI enablement and AI fluency. And then once we see that come into play, adoption's going to come back up and there's a tool now to support that.

• 32:43Greg Isenberg?

  Beautiful. Well, thanks for explaining it to me, honestly, and everyone else. For more of Amir, I'll include links in the show notes where you can go ahead and follow him. X is the best place.

• 32:57Speaker 01

  Yeah. Amir M X T, A M I R, M X T.

• 33:01Greg Isenberg?

  Cool. I appreciate you coming on.

• 33:03Speaker 01

  Cool. Thanks for having me.

• 33:04Greg Isenberg?

  Thanks, man.

• 33:04Speaker 01

  Thanks.