Why the Future of Learning Starts with Building

By

-

July 10, 2026

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

Switch to Learn for behind-the-scenes insights and your personalized roadmap.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

Rework your prototype in real time with the help of AI.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Time Management: What is it, who has it, and can you improve it? (Repost)

By

onlinefreecourse

-

July 10, 2026

0

Time Management: What is it, who has it, and can you improve it? (Repost)

Time management can refer to a wide range of behaviors and can look very different from person to person. There are lots of different systems and approaches to time management. Making a to-do list, keeping a planner, setting event reminders in your phone, setting goals, prioritizing tasks, and marking events on a calendar can all be part of time management. It’s therefore a little tricky to define time management. However, in general when we talk about time management we are referring to a skill that involves assessing your use of time, planning ahead, and monitoring your activities and use of time (1) .

Effective time management is linked to a number of personality traits. People with better time management skills tend to have higher self-control, which means that they are able to control and refrain from acting on impulses (2). People who are better at managing their time also tend to be high in self-efficacy, which is your belief in your ability to handle challenges and complete tasks successfully (3, 4). Time management is also linked with conscientiousness, which is a personality trait that describes someone who sets a high priority on completing obligations and doing tasks well (5). However, it should be noted that all of these studies on time management used surveys and self-reports. This means that we cannot determine causality. For instance, we do not know if higher self-efficacy leads to better time management or if better time management leads to higher self-efficacy – or if there is some other factor that influences both of these things. But, these studies do indicate that there are reliable differences between people who are good at managing their time and those who are not.

Interestingly, some of these same factors (high self-control and self-efficacy) are often linked with higher levels of satisfaction and happiness (3, 6, 7, 8). Again, while we know these relationships exist, it’s difficult to determine causality. Are people happier because they have higher self-efficacy (or, by extension, time management)? Or does happiness lead to better self-efficacy and time management? It’s hard to say. But it is reasonable to assume that managing your time can help reduce your stress and help you to be more productive. So that leads to the next question: Can you improve your time management or is this just a trait that some lucky people have and some people don’t?

The literature on time management interventions is somewhat mixed (1). Some studies have found improvements in time management after an intervention. For example, Burrus, Jackson, Holtzman, and Roberts (2017) found an improvement in time management after an intervention for high school students who were low in time management skills (9). In this quasi-experiment half of the students were assigned to be in the intervention condition and half were in the control condition. The intervention involved an assessment of time management skills, feedback on their individual skills (e.g. if a student scored low on goal setting they were told “Remind yourself regularly of your goals. Goals are an investment in your future.”), and homework assignments over the course of 5 weeks. Homework assignments involved goal setting exercises, accounting for how they spend their time, and learning how to use a planner. Students who were in the control condition (and did not receive the intervention) took the assessment of time management skills, but did not receive feedback or homework. One month after the intervention ended all students were rated on their time management skills by their academic advisors. Importantly, the academic advisors did not know which students received the time management training and which students did not. Burrus and colleagues (2017) found that time management improved after the intervention, but only for students who scored low on time management to begin with.

However, other studies have found no improvement in time management after an intervention. For example, Macan (1996) studied the effects of a time management training program on employees’ time management behaviors at a social service agency (10). All of the participants completed a time management survey at the beginning of the study. Half of the participants then attended a 2-day seminar that covered topics such as: goal setting, setting priorities, overcoming procrastination, desk organization, and dealing with interruptions. The other half did not attend the seminar. Four to five months after the seminar participants filled out the time management survey again. Participants in the seminar did not report engaging in time management behaviors after the training. However, they did report that they felt more in control of their time after the training.

There are a lot of differences between these two studies. They examined different populations: high school students versus employees at a social service agency. The interventions are different: feedback on behaviors and homework over a 5 week period versus a two day seminar. And the assessment delay: one month after the interventions versus four to five months. These differences highlight the complexity of research on time management and why it is difficult to make recommendations on how to improve time management.

Can you improve your time management? Probably, but it seems that not all interventions are successful and it may depend on what you consider an improvement. Even though the Macan (1996) study did not find an improvement in time management behaviors, those who completed the training did report feeling more in control of their time which is valuable in and of itself. What does seem likely based on these studies is that any improvement is not going to happen overnight. Like any skill, it will most likely involve deliberate and consistent practice to improve – and it is a skill worth improving. Better time management is linked to improved academic outcomes and general stress relief (1, 11).

Sadly, it seems there is no silver-bullet to improving your time management. While the literature is still mixed on how to improve your time management skills, there is no shortage of advice and tips on how to deal with procrastination and time management. We have collected some of these in previous digests on procrastination and time management.

Claessens, B. J. C., van Eerde, W., Rutte, C. G., & Roe, R. A. (2005). A review of the time management literature. Personnel Review, 36(2), 255-276. DOI 10.1108/00483480710726136
Osgood, J. M., McNally, O., & Talerico, G. (2017). The personality of a “good test taker”: Self-control and mindfulness predict good time-management when taking exams. International Journal of Psychology and Educational Studies, 4(3), 12-21.
Donnelly, D., Kovar, S. E., & Fisher, D. G. (2019). The mediating effects of time management on accounting students’ perception of time pressure, satisfaction with the major, and academic performance. Journal of Accounting & Finance, 19(9), 46-63.
Boysan, M. & Kiral, E. (2017). Associations between procrastination, personality, perfectionism, self-esteem, and locus of control. British Journal of Guidance and Counselling, 45(3), 284-296. http://dx.doi.org/10.1080/03069885.2016.1213374
Douglas, H. E., Bore, M. & Munro, D. (2016). Coping with university education: The relationships of time management behavior and work engagement with the five factor model aspects. Learning and Individual Differences, 45(1), 268-274.
Hofmann, W., Luhmann, M., Fisher, R. R., Vohs, K. D., & Baumeister, R. F. (2014). Yes, But are they happy? Effects of trait self-control on affective well-being and life satisfaction. Journal of Personality, 82(4), 265-277. https://doi.org/10.1111/jopy.12050
Cheung, T. T., Gillebaart, M., Kroese, F., & De Ridder, D. (2014). Why are people with high self-control happier? The effect of trait self-control on happiness as mediated by regulatory focus. Frontiers in Psychology, 5, 722. doi: 10.3389/fpsyg.2014.00722
Caprara, G. V. & Steca, P. (2005). Affective and social self-regulatory efficacy beliefs as determinants of positive thinking and happiness. European Psychologist, 10(4), 275-286. DOI 10.1027/1016-9040.10.4.275
Burrus, J. Jackson, T. Holtzman, S., & Roberts, R. D. (2017). Teaching high school students to manage time: The development of an intervention. Improving Schools, 20(2), 101-112.
Maccan, T. H. (1996). Time management training: Effects on time behaviors, attitudes, and job performance. The Journal of Psychology, 130(3), 229-236.
Macan, T. F., Shahani, C., Dipboye, R. L., & Phillips, A. P. (1990). College students’ time management: Correlations with academic performance and stress. Journal of Educational Psychology, 82(4), 760-768. DOI 10.17220/ijpes.2017.03.002

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Word of the Day: querulous

By

onlinefreecourse

-

July 10, 2026

0

This word has appeared in two articles on NYTimes.com in the past year. Can you use it in a sentence?

Why the Future of Learning Starts with Building

By

onlinefreecourse

-

July 10, 2026

0

Coding has always served two purposes: the intrinsic drive to build something, and the practical path to a lucrative career. Even the most passionate code aficionados don’t dream of variables or syntax — they want to make a website, a tool, a game. For years, the career upside was impossible to ignore. You could land a stable SWE job, bootstrap your own app, or join a buzzy startup as a first hire.

Generative AI flipped the script. AI now handles the repetitive tasks that used to define entry-level developer roles. At the same time, the barrier to entry for coding and building is lower than ever — you can spin up a working prototype with just an idea and a natural language prompt.

This shift hasn’t eliminated the desire to code, but it’s changed what and who coding is for. If you’re not learning to land a junior dev role, you’re learning to build the thing you’ve been imagining, to add a technical skill to your existing career, or to understand the tools you’re already using at work. And here’s the catch: those goals all require understanding your code, not just having code that works.

At Codecademy, all of these changes excite us about the future of learning to code. We’re introducing the AI Builder, a new project-based learning tool that flips the script by teaching you how to work with AI-generated code from the start. Our approach brings together the immediacy of modern AI tools and the rigor of real instructional design.

Why we created the AI Builder

AI’s speed and efficiency often come with a tradeoff; you can get working code immediately, but you don’t really know what it’s giving you or why it’s built a certain way. Developers use the term “vibe coding” to describe this phenomenon — it’s fast, fun, but shallow; great for demos, less great for long-term skill-building.

If your goal is to understand what you’re building, generic AI output alone won’t get you there. And the more you push these tools into real-world complexity, “the harder it is for them to give you exactly what you want,” says Zoe Bachman, Head of Learning at Codecademy.

With the AI Builder you get an education along with the AI output. In the workspace, you can toggle between two tabs: Build, where you work directly with a project and can modify and change code in real time; and Learn, where you get a personalized learning roadmap that’s based on your project.

“We pair the experience of having a working app with a learning path that allows you to reverse engineer how it’s built, so you can deeply understand it and modify it confidently,” Zoe says. We’re calling our hybrid approach to learning-driven development “vibe learning” — it’s powered by AI guidance but rooted in learning science.

Build first; learn continuously

With AI Builder, you start with what you want to do: build the thing in your head. Whether that’s a habit tracker, a portfolio site, or the seed of a bigger idea, you don’t need to have prior coding knowledge to learn and build with the AI Builder. In other words, there are no pre-requisites for creation.

You create a prototype by typing what you’d like to create in natural language. The AI chatbot will ask a few clarifying questions about your needs and overall goal before generating the project. Once the project is created, you can use the chat function to continue describing what you want. (You’re also welcome to go right into the code and start making changes if you already know your way around!)

“It was fun to build something so quickly and be able to see the code and a learning plan for it,” says Grace Krishna, a Code Crew member who beta tested the AI Builder.

When you need clarity on what’s going on behind the scenes in your code, or you hit a wall with AI, that’s a great time to flip over to the Learn tab.

We’re calling our hybrid approach to learning-driven development ‘vibe learning’ — it’s powered by AI guidance but rooted in learning science.

Your project becomes the curriculum

Rather than teaching concepts in the abstract and hoping learners translate them later, AI Builder removes that translation tax entirely. “We’re showing you specifically your code from your project and helping you understand it,” Zoe says.

To build that personalized curriculum, the AI Builder breaks your project’s code into clear milestones and tasks. For each task, it generates an interactive learning loop, which is an activity designed to help you form a mental model of what your specific code is doing.

These loops help you understand the logic behind each part of your project, so you can confidently apply the same thinking to other sections, or even future projects. This approach also ensures everything you learn is directly relevant to what you’re making — so you don’t have to guess when you’ll ever use this.

Why this is vibe learning (not vibe coding)

A key misconception about AI‑assisted development is that it makes learning superficial. AI Builder challenges that by grounding the entire experience in learning science rather than simple code generation. Our entire system is intentionally designed for you to retain knowledge. So, while it might not feel like you’re taking a course, you’re absorbing key concepts just by interacting with AI-generated code.

A Socratic AI, not an answer-spitting chatbot

Our educational AI chatbot is designed to guide you toward an answer through an in-depth questioning approach that’s based on the Socratic method of teaching. Instead of spitting out shortcuts or answers like AI typically does, you get strategic nudges, hints, and questions that build durable mental models.

Research on AI in education shows that just providing an answer makes it harder for learners to retain the information on their own. Zoe compares the Socratic AI to “a personalized tutor, facilitating you acquiring more knowledge, so you’re not totally left on your own.” Our method encourages you to think critically so you really grasp the concepts and can continue to use them in the real world.

Learning loops with real instructional design

Behind the scenes, every learning loop in the Learn tab is built on proven frameworks like inductive learning and the 5E model, a popular STEM teaching framework that’s shorthand for engage, explore, explain, elaborate, and evaluate.

You’ll notice that the questions and exercises in the Learn tab feel different than the rest of our courses and paths, and that’s intentional. “The learning loops are designed very well — they get you there inductively,” Zoe says. They’re exploratory without being overwhelming, and evaluative without feeling like tests.

Negar Vahid, a beta tester for the AI Builder appreciated the AI’s interactive question format. “The question-based learning feels engaging, and the starter project it builds is simple but useful,” she says.

This structure ensures you don’t develop the wrong mental models — a known risk in fully constructivist or student-centered environments — while still giving you the freedom to explore.

Why learn when AI can build?

There are some projects that are well-suited for simply vibe coding, like making a personal HTML website or a single-use script to automate a one-time task. Tools like Lovable and v0 are suited exactly for these types of projects.

The longer your code needs to live, and the more complex your project becomes, the more you need to actually understand what you’re building. Joe Holmes, Codecademy Curriculum Developer in the AI and machine learning domain, uses the term “ignorance debt” to describe what happens when you don’t:

“It’s like tech debt squared. It’s much, much worse,” Joe says. “You don’t know what kind of code is coming out. You just are only looking at: Does this kind of generally appear to be what I asked for? You don’t know if there are security flaws. You don’t know if there are performance flaws. You don’t know if you’re leaking sensitive information. You don’t know how to fix anything.”

The tipping point comes down to two factors: complexity and time. If you’re developing software professionally, you’re legally responsible for the code you output. If you’re building something that will serve actual users, you need to be accountable for security, performance, and maintainability. And if your project will need updates or fixes over time (which most do) understanding your codebase becomes essential, not optional.

The good news? Learning doesn’t have to feel like eating your vegetables. “Kids hate veggies and broccoli because we don’t cook it well enough to make it tasty when we first introduce it to them,” says Nhi Pham, Codecademy Curriculum Developer. The same is true for teaching AI: “If you do it well, you’re inspiring people to have these very hygienic practices when working with AI,” she says.

That’s exactly what AI Builder is designed to do — make learning feel as immediate and rewarding as building, so you develop good habits from the start rather than building a lifelong aversion to understanding your own code.

Get started with the AI Builder

AI isn’t a replacement for learning, it’s a tool — and a powerful one when it comes to education. Our new AI Builder allows for “just‑in‑time learning that’s highly personalized,” Zoe says. Even the best teachers or bootcamps can’t deliver that for every learner, on every project, instantly. Perhaps the most exciting vision is how AI changes what a learning environment can be.

Zoe described it beautifully: “I imagine the AI Builder as a workspace… like having all your resources around you and an AI tutor in the background.”

That’s the shift: from learning before you build to learning while you build. We can’t wait to see what you create.

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Why we created the AI Builder

Build first; learn continuously

Your project becomes the curriculum

Why this is vibe learning (not vibe coding)

A Socratic AI, not an answer-spitting chatbot

Learning loops with real instructional design

Why learn when AI can build?

Get started with the AI Builder

Recent Posts