AI fluency assessment tool "AI Cred" launched by Nate B Jones and developer Jonathan
Nate B Jones presents his framework for multi-dimensional AI fluency and introduces AI Cred, a new assessment tool built by Jonathan, a filmmaker and developer from northeastern Pennsylvania.
Summary
Nate B Jones opens with an extended argument that most AI certifications and courses make a fundamental error: they treat tool proficiency as equivalent to AI competency. In a multi-model world where new models launch weekly, he argues that fluency must be built above the level of any single tool. He identifies five core AI skill dimensions — strategy, prompting, workflow integration, critical evaluation, and ethics — and contends that most practitioners are strong in only one or two while ignoring the rest. The second half of the video is a live demo and conversation with Jonathan, the developer who built AI Cred, a free assessment tool that evaluates users across all five dimensions, generates a personalized training plan, and includes a public leaderboard. Jonathan also shares his experience building the tool using Claude Code and Codex, offering a candid comparison of the two.
Key Takeaways
FULL TRANSCRIPT
The Problem with AI Certifications
Nate B Jones: How do I learn AI? That is the topic of this video. I want to talk specifically about how we move from the idea that AI is a single competency to the idea that AI is a related group of competencies that we can all stand to get better in. I want to talk about a tool I'm using to measure that. But let's talk about how we think about AI as a multi-dimensional skill set first, because if you don't believe me on that, none of the rest of it is going to make sense.
I have to be honest: I think most of the courses out there are not doing any of us any favors, because they view tool competency as equivalent to AI competency. As an example, if you get an OpenAI certification, it certifies you for use of that tool. They may tell you it certifies you for AI, but any given organization — Claude, Gemini, OpenAI — they all make great models and they're doing good work on the training side for their specific tool. But we shouldn't mistake the tool certification for an understanding of artificial intelligence, especially in a world that is multi-model.
If you've gathered anything from what I've been talking about over the last month or two — with the launch of Gemini 2.5 Pro, with the launch of Claude Opus 4.5 — we are living in a multi-model world. ChatGPT 5.1, every week a new model comes along. Grok 4.1 last week. It's a multi-model world, and we need to be ready for AI fluency that scales as models continue to proliferate, grow, and evolve.
The Five Core AI Skill Dimensions
If you're looking at the elements of a multi-dimensional skill set, you have to look above the level of the tool. I don't know very many courses that think that way. The ones that do tend to look at a particular job family and say, "Are you certified in AI for engineering? Are you going to be focused on AI for product management?" — whatever it is. They don't tend to think about AI as a new core skill set above the level of the tool that we all need to be good at.
Regardless of job family, there are foundational AI skills we all need to know. I'm going to suggest there are five critical skills that we need to get better at, that we need to grow in, that we need to have in our growth kit for AI. They're all practical.
Number one is a sense of AI strategy. Strategy is not just for executives anymore. Strategy is for all of us, because AI puts artificial intelligence as a team member on all of our teams. We have to have the strategy to know how to deploy that AI intelligence correctly. We have to have the strategic insight — if we're looking at products — to know what is the right product that moves my workflow forward. If we're in any of the building spaces, whether that's video, engineering, whatever it is, you have to have a strategic understanding of the market and how AI fits into that market. It is not something you can outsource to just one executive part of the business anymore.
Prompting — that's another multi-dimensional skill set. You need to know not just how to prompt for a particular task, but how to evolve and change and think about that prompting as it shifts. How do you think about prompting Gemini differently from ChatGPT? How do you think about prompting for a deck differently than a doc? I released a prompt tool because of this gap just this week called Hey Presto, and it's designed to help you figure out how to form intent through prompting. But prompting is a skill set that is above the level of the tool. You can use any tool — I don't care if it's Hey Presto or any of the other hundred tools out there — and use them badly, or you can use them well. That is your skill set that drives that. And that is something we haven't got a good handle on how to teach yet, because it's so new.
The third critical skill set is how you think about integrating AI into your workflow. I talk so much about AI being useless if it lives off to the side. What does it mean if AI is deeply connected and tied in and integrated into your workflows? How do you design workflows that are AI-native? That is also a learnable skill set that we need to practice and teach on, but very few people teach on it.
Critical evaluation — that's another one. How do you evaluate the output of an AI critically, with good taste and good judgment, so that you can say with confidence and authority, "This is good and this is terrible"? I was working on a little test today between Gemini 2.5 Pro, ChatGPT 5.1 Pro, and Claude, asking them to write me a creative story. One of the interesting bars for LLMs, even if you're using them in a business context, is how they form narrative. I gave them the same prompt and I had to use my taste to figure out what the best answer was. I had to read through the three different stories to figure out which one was the highest quality. I'm still digesting it — don't ask me, I'm still thinking it through. This is a skill we need to develop that we can use across a wide range of contexts: numeric data, decks, docs, and so on.
The final big piece — the one I don't think we talk enough about — is ethics. People often roll their eyes and say ethics is for ethics officers. But the ethical choices we're all facing are actually so multi-dimensional and so woven into our work that we probably all need to have an understanding of where the lines should be.
I'll give you a few examples. One is that some AI tools can now make passport pictures. The simplest ethical issue is don't fake a passport — that's an easy one. But a complicated one is: how do you think about installing guardrails in systems so that your system is not vulnerable to a model change in output generation capability that would enable something like that to get through? That's system design and ethics. You can also think about how you change security policies so that you have in-person or physical asset verification where needed, to make sure you aren't being spoofed by something like a fake passport photo. Or you can think about it a different way: how do you build trust in your product experiences? How do you ensure that people trust what you are making, and that you are one of the good guys, when your model can be used in so many different ways? Where's the right line for guardrails?
I am firmly convinced that the question of how LLMs ought to act — which we traditionally call ethics — is really a question of product design to build trust. We are all in the business of either designing products that use AI, or using products in such a way that we want to build trust with others. The way we use products to build reports for sales, or the way we use them to build white papers, can either be trust-building or not. That falls under the banner of ethics.
Why Multi-Dimensional Measurement Matters
I've given you a painted picture across strategy, prompting, integration into workflows, critical evaluation, and ethics — and I've done that for a reason. We constantly misjudge ourselves when we don't understand the core skill sets we need to learn, because we tend to over-index on one of them while ignoring the others. Frankly, of those five, most of what I hear about is prompting, and I think that's an impoverished view of the rich LLM skill set we need to develop.
Most AI-fluent users tend to be strong in only one or two pillars and weaker in the rest. If you don't measure across all five, you don't get a real picture of how someone thinks, how they work, how they reason through ambiguity.
Real AI work blends all of these skills — the judgment, the synthesis, the workflow design, the rapid learning, and the ability to interrogate models — into an overall application on a particular task that delivers value. If you can only prompt but you can't evaluate output, that's dangerous. If you're great at strategy but you can't operationalize a workflow, it's not going to work out.
Introducing AI Cred
This is where I want to point you to a tool that I did not build. It's a tool that one of my Substack readers built with my permission, using a prompt set from a very popular post I made about evaluating AI fluency. He's done a fantastic job. It's called AI Cred. I'll show it to you in a few minutes and we'll talk with him.
I'm sharing this because it's a way for me to start giving you tools to understand AI fluency, to test yourself on it. It's a little bit fun — there's a leaderboard — but most importantly, it gives you resources to grow that I haven't seen collected and customized in any other way.
AI Cred goes across that full multi-dimensional skill set: strategy, prompting, integration, critical evaluation, ethics, workflow design, synthesis. It's a very comprehensive assessment of your AI skill set, and one you can retake and grow in. It is a hard test to do well in — that is on purpose. The highest score on the leaderboard right now is 8.9 out of 10. No one has hit nine yet. Maybe you'll be the first.
When you answer honestly and see your actual score across these different dimensions, it empowers you. It gives you options to succeed, because it comes back with custom resources that I spent a lot of time picking out and tailoring, so that the recommendation you get is tied to the specific gaps in your skill set.
I've been asked for a long time: "Nate, can you give me just a course on AI so I can scale up?" Because the answer is custom — because it involves this multi-dimensional skill set — I can't in good conscience point you at one tool and say, "Learn that tool." I can't just point you at one particular course and say, "That's going to make it work." I want to point you at a thousand courses, at a bunch of resources to read, but only in bite-sized chunks tied to your particular gaps. That's where AI Cred comes in, because it custom-assesses you for your unique skill set and it's consistent. You can reassess yourself in a month, in two months, in three months, and ask: where am I at? Have I made progress? Did the resources I actually dug into change the way I work and think?
So often when we talk about AI fluency, it is a piece of paper we staple to the wall. It is not getting into our head and into our hands and onto the keys. AI Cred measures whether that outcome is actually happening.
Conversation with Jonathan — Building AI Cred
Nate B Jones: I'm here with Jonathan — really the guy who built AI Cred. I want the second half of this video to be about how this came to be, how you make the build decisions to build a tool like this, and of course what the tool does. I'd love to get into the tool, show it on screen, demo it a little bit, and talk about it so that everyone knows what it is. So Jonathan, maybe introduce yourself and let's jump into it.
Jonathan: I'm a filmmaker out of northeastern Pennsylvania — the Wilkes-Barre/Scranton area. I've been running a production company for the last 20 years. I got started with AI like everyone else, got a little bit addicted, and as I was building workflows out for my video editing I did some really cool stuff. I was fascinated with what AI was giving me the ability to do and I couldn't stop talking about it. I tried to find other people to talk about it, ended up following you, and that's the super-abridged version of the story.
Nate B Jones: We'll take it. So how about AI Cred? What sparked that for you?
Jonathan: Nate, I have to tell you — you keep making these videos and guides and prompts and notes, but every third post you make could be an app. One of the things we're most aligned on is really trying to share our skills. When you made that post about those prompts for determining your AI fluency, I thought: that's what people need. You need to identify where you're at, and getting that foundation is what's going to help you move forward.
Nate B Jones: That makes a lot of sense. My goal has always been to put out good stuff and let it percolate through the internet. One of the things I'm really excited about is that sometimes stuff really lands. With AI Cred, the vision goes well past Substack. You don't have to be a Substack person for this to resonate — the idea that fluency matters, that learning AI matters. It should be evergreen and available, and all of us should be able to dig in at our own pace.
Jonathan: Agreed. It's not even about the tools you use — whatever model. The core principles you're always pushing, the fluency, really does matter regardless of tool. Learning how to communicate with AI honestly helps you learn how to communicate with people as well, which is super cool.
Demo: The AI Cred Assessment Tool
Nate B Jones: I'd love to hear and see a little bit about AI Cred. Maybe you can throw it up on the screen, walk us through what it looks like, and then toward the end talk a little bit about using AI to build AI — how you actually built it and put it together.
Jonathan: So right now what we're looking at is the dashboard. I went ahead and — not to brag or anything — I'm currently number one on the leaderboard.
Nate B Jones: We'll see how long that lasts.
Jonathan: You can see your score up here. This is going to be pretty different tomorrow, but right now you can go in, take your assessment, and see your fluency score. We have your sectional breakdown. The evaluation works in six different sections: an introduction and report that covers what you're experienced in, your technical fundamentals, different use cases you use AI for, prompt engineering skills, your strategic thinking, and then how you apply things practically. I just switched over to Claude Opus 4.5 yesterday and it just—
Nate B Jones: Really breaks it down, doesn't it?
Jonathan: It's insane. It gives you a competitive context.
Nate B Jones: That competitive context — is that about you in relation to your peers?
Jonathan: Yeah, pretty much. For example, mine reads: "Jonathan operates in the top 5% of AI practitioners. His combination of systems thinking, documented workflows, and active frontier experimentation places him well above most professionals." I'm feeling a little self-conscious reading that. But then the brutal truth section is where I feel a little less comfortable. It says something like: "You've mastered personal AI fluency and built impressive systems, but you're still operating as a solo practitioner. Your knowledge transfer has reached maybe 12 people through one-on-one work, and that's not scale. Your assessment app is a step in the right direction, but it's still an MVP with no revenue validation. Your technical depth is a genuine asset, but also a blind spot."
Nate B Jones: But then you can retake it, right? That's what I've been saying — with AI Cred, you can go back and retake your score and see how you're growing. That's an example of where you could be growing.
Jonathan: And here's the thing — I don't know if you've seen this part. Okay, here we go: Start Your Training Plan. I have not clicked this button yet.
Nate B Jones: Oh, we're live on your profile.
Jonathan: Yeah, it's going to take a minute. What it's doing right now is actually building a training plan. Your original prompt told it to build it all at once. I'm a little bit of a psycho, so I wanted each module — two, three, four, five — to not be generated without the context of the previous module.
Nate B Jones: Okay. So let's look at the module content in module one. What is it suggesting for you?
Jonathan: So we're going to hop into module content. This is all live. Thank god it works.
Nate B Jones: This is why we're launching it — because it actually works. I know it's the builder's nervousness, but this is good.
Jonathan: Yeah, for real. So the focus area gives you a hands-on exercise. Let me make that larger for everyone. It wants me to design and execute a two-hour workshop for a group of five non-technical users, teaching one core AI workflow, and then take a progress check. This is AI-graded, so it actually gives you a quiz.
Nate B Jones: And in your case, because your growth challenge is scaling your impact to others, the exercise is about exactly that.
Jonathan: Exactly. And then when you finish that module and take the quiz — and this is all free. The evaluation costs something, but all these modules are entirely free. You pay to get a free education.
You take your progress check, and you get a whole learning plan that evolves with you. Because here's the really cool part: you'll take the progress check and depending on how you respond, it's going to customize module two to what you particularly need. That was honestly one of the things that took me forever to build.
Nate B Jones: Because when you get done with your learning path, it doesn't end there.
Jonathan: You take a reassessment which builds on the context of your first conversation, all your training modules, and then it reassesses you and regenerates a brand new learning path.
Nate B Jones: It's super rad. And tell me about how you're designing it — there are obviously hands-on exercises. What other things are there? Resources, videos — how does it pull all that together?
Jonathan: Right now I have a basic database. I would like to call it a RAG, but it's not a RAG yet — it's just MySQL. But it pulls from almost entirely your content and AI training modules. There are many more versions to come. I have a roadmap that's ten miles long. But yeah, that's where it pulls from — a lot of the training you've done. What are you posting, six videos and four posts a day lately?
Nate B Jones: I also age in dog years, Jonathan, I will tell you. The beard grows ever wider.
The Leaderboard and Social Features
Jonathan: Let me show off a couple more things I really like. We ran a prototype of this about two months ago in your private Substack.
Nate B Jones: Yeah. For anybody who doesn't know, the Substack has this whole group of people — hundreds of people who are really into AI. That's the place to be.
Jonathan: We ran a prototype and had just over a hundred people sign up, and they were all dying to see each other's scores — begging to. That's why we added the social piece, the leaderboard piece. So we have this profile page — please ignore the lime green, that's going to be fixed tomorrow, I promise.
Nate B Jones: You can barely see the text.
Jonathan: Yeah, that'll be fixed tomorrow. But it's authentically built, right? It's not like there's a bunch of VC money here. You can add your social links, add your own bio, and it ranks you right here. It actually tells you what position you are on the leaderboard. I have this wingman summary — a lot of people, myself included, don't like bragging about themselves. So if you make your profile public, you get an automatic augment where the AI is your wingman and talks about you for you.
Nate B Jones: Brag about yourself.
Jonathan: Exactly. You can share your links. And of course you can take a look at the leaderboard — which again, I'm just not going to brag. I'm number one.
Nate B Jones: Somebody's got to be, Jonathan. That's my ask to the world: go be Jonathan.
Jonathan: My wife, by the way — 5.5. I have to say, 5.5 is a phenomenal score.
Nate B Jones: This isn't an easy test, is it? I made this one brutal.
Jonathan: You see these numbers like 8.7, 8.9, 8.6 — these are some test users who have been hardcore into AI since the day ChatGPT was released. And my wife — I was shocked. The average person gets like a 1.4 to a 2. Somebody who's been using ChatGPT casually and actually trying a little bit is more around a 3. 5.5 is ridiculous.
Nate B Jones: When I wrote the fluency algorithm, I was like: I don't care about grade inflation. I know it's a thing. We're not doing it here. If you earn your way to whatever score, it's a real score. It's hard. You should be proud.
Jonathan: Absolutely true. So, last couple of things. This is the homepage. We have the leaderboard right there — the top ten people are going to be here. That's the challenge.
Nate B Jones: Yep.
Jonathan: And then you can search for your friends. So the only people who show up on the leaderboard are people who have actually gone through the evaluation. Here's my son's page — he has not gone through the evaluation, but he sent me so many error reports and bug fixes.
Nate B Jones: I'm the god of finding bugs. I love this.
Jonathan: Yeah. And of course he linked to his TikTok here.
How AI Cred Was Built — Claude vs. Codex
Nate B Jones: Coming back to the build story — how did you build this with AI? Tell us a little bit about that.
Jonathan: I used every tool known to man. I started using Claude Code, then jumping from system to system to figure out what worked. For example, I hate using Codex for building, but I love using it to review what Claude did, because Claude can be a little bit silly sometimes.
Nate B Jones: Tell me more about that. A lot of people are really keen for the hands-on Claude versus Codex comparison. Dig into that for me.
Jonathan: I have a strong opinion. Codex straight up ignores you when you ask it to use tools. Period. You have to prompt it in a very specific way every single time: "Hey, use this tool to do this job. By the way, you do have access to this tool. This is how you use this tool." All of that has to be in your prompt, and that drives me insane. So I just use Codex for code review, because it's phenomenal at that. It'll go through the code, help me plan, help me check the plans, find all the faults in the plans. But then I have Claude execute, because Codex is lazy about execution in my opinion. You could prompt your way out of that, but I just really like the experience with Claude.
I had a few days with Gemini 2.5 Pro last week that blew me away, and then Opus 4.5 came out and I haven't even thought about using Gemini again. Because it has its quirks. Gemini 2.5 Pro scares the hell out of me. When you're watching its thought chain, it always starts off speaking in the first person for some reason — repeating your prompt in the first person, like "Hey, I'm really focused on this and I'm really focused on this" — and then it'll say the wrong thing and dig into saying the wrong thing, and you're desperately trying to pull it out of the mud in your head. And then maybe it self-corrects, but you don't know.
Nate B Jones: Right as you go to click cancel, it's like—
Jonathan: It'll be like, "No no no, I'm wrong, I should be doing this." And you're like, "Oh, okay, thank god," because it was just about to touch something you didn't want it to touch.
Nate B Jones: I think that happens with AI more than we realize. Gemini made a very bold choice to expose that, because I think behind the scenes there is a lot of what I would call temporary misinterpretation. With Claude, for example, if it's streaming the train of thought, it will sometimes say something that sounds absolutely nasty — like "I'm thinking about the user's underdescribed prompt" — and I'm like, what do you mean? This thing is a 50-line prompt. But it's because it hasn't opened the prompt up yet and it's just kind of thinking, and then eventually it gets into it and opens it out.
Jonathan: I'll do my standard thing — I'll just use Whisper Flow and talk to it for like five minutes, then do the standard "Hey, please explain to me what you think I'm talking about and wait for me to confirm or clarify." It'll make this huge list, and I'll clarify or confirm. But if it's right, I'll tell it, "Yeah, please proceed." And the first chain of thought is like: "What is the user talking about? This is super vague." And I'm like, what?
Nate B Jones: And yet from there we get to "You're absolutely right" with Claude every time.
Jonathan: Yeah. As soon as you see "You're absolutely right," you should clear your context immediately. That's the sign to run away.
Nate B Jones: That's a bad omen. Okay. So you're using Claude Code, you're using Codex. Any other vibe coding tools?
Jonathan: The prototype of this app I built in Lovable. And then of course the minute Nate and I talked, he's like, "I want it in Next.js," because it was in Vue.
Nate B Jones: So there's no longer any Lovable heritage in it.
Jonathan: Yeah, we did pull it back out. He made me refactor the whole thing.
Nate B Jones: We had to refactor it — I'm sorry about that. But this does call out something really cool that I don't think people realize. One of the things that's cool in the age of AI is that it's easier to build things with fewer meetings. This is the first time Jonathan and I are having a meeting, and we are launching tomorrow.
Jonathan: Usually it's me posting document after document after document and Nate saying, "Yeah, this is fine. I hate this. That's good." And then I'll hear from him two days later.
Nate B Jones: Yeah. I'm like one of those slow inference LLMs — I eventually trickle back around, hopefully with a high-quality response.
The Vision for AI Cred Going Forward
Nate B Jones: I always ladder back to why we do this. One of the things that really excites me about AI Cred is that we haven't had any kind of product space where we can have a conversation about what overall fluency feels like. I'm sure AI Cred will continue to evolve as folks give us feedback. One of the things I want to call out is that Jonathan and I are going to be opening up a Slack channel. So if you sign up for AI Cred, you're going to be invited to join us in the work Slack and give us feedback directly. You can ping us and say, "Hey, I got this weird response and I want this fixed," or "I have this cool idea for the leaderboard," or maybe it's a bug, and we can get right on fixing it.
One of the things we want to model is that AI tooling evolves. We build AI Cred, but we're building it for a space that's evolving, and so AI Cred will evolve to keep pace with how learning continues to need to grow in the age of AI.
Jonathan: Definitely join the Slack. I implemented a whole bug report system — it's rate-limited at two per hour because I don't want people spamming me, but definitely join. In two months you're going to hear all kinds of updates implementing really cool features. There's a lot of stuff I don't want to talk about now because you never know if it'll actually happen, and I want to get your feedback first.
Nate B Jones: There are so many cool things coming. This is just going to constantly improve, and we definitely need people's input. Jonathan's 12-year-old son is the reason the profile pages are actually going to look good.
Jonathan: Your feedback is super important. And for folks — this came out of the Substack community, so we want to give back to the Substack community. If you're a member of the Substack, you're going to get a significant Black Friday discount. That's because this is one of the products that got born out of that community.
Don't join the Substack just to get a discount on this. Join the Substack because genuinely the people I've met in this space — the people who have helped me — we have engineers, top-level software developers, people who run actually large companies. So many genuinely amazing people. And then there's me. But yeah, join anyway.
Nate B Jones: The community is a reason. I am genuinely shocked — it's something I really appreciate. This community has just grown up organically and now I just watch the chat and it's not me answering everything. It's people responding to each other, which is always what you want with a community. It's this many-to-many connection and it feels really strong. I love that.
Jonathan: Definitely sign up for AI Cred, get your fluency score. I have an 8.9 right now. I'm pretty sure you can't get more than a nine on a first evaluation, so it might be a little tough to beat me.
Nate B Jones: Someone needs to go beat Jonathan. I want to see the leaderboard tomorrow. All right. Thank you, Jonathan. This has been great.
Jonathan: Same. Cheers.