AI Foundations: Introduction
By Cursor
Summary
## Key takeaways - **AI for programmers, not ML engineers**: This course focuses on developers using AI models and tools to be more effective, rather than on machine learning or training models. [00:04] - **AI tools require understanding models and limitations**: To effectively use AI tools, developers need to understand how the models work, the different types available, and their limitations. [00:23] - **AI code completion saves time**: AI-powered features like Cursor's tab completion can significantly speed up coding by suggesting and completing lines of code, imports, or even navigating between files. [02:05] - **Understanding AI is key to avoiding frustration**: Without a solid mental model of how AI works and its limitations, developers can face frustrating experiences with incorrect code generation and debugging cycles. [03:13]
Topics Covered
- Choosing developer tools: Time, money, reliability, effort.
- The evolution of coding tools: From Vim to AI.
- Why a mental model of AI prevents coding frustration.
Full Transcript
Welcome to Cursor Learn. This course
will teach you how to use AI to be more
effective as a programmer. It's not a
course about machine learning or how to
train your own models, but instead a
course focused on developers writing
software using AI models and tools.
[Music]
Now, to really use AI tools, well, you
need to have an understanding of how the
models work, the different types of
models, and what some of their
limitations are. So, let me give you an
analogy. Imagine you're trying to get
across town. You could walk. Of course,
that's free, but may take a little
longer. You could ride a bike, but
that's going to require a little bit of
money and it's slightly faster. or you
could drive a car. It costs the most
money, but it's going to be the fastest
way. Now, you're probably thinking,
"What about public transportation?" And
I'm sorry if you live in New York or
somewhere in Europe. I get it. Now, the
reason I like this example is because
you have the choice between time, money,
reliability, and effort. Now, let's
apply the same idea to building a
software product. If we go look at
cursor for example, I might do export
default function page. You know, it's
just it could be really slow, but you
could get really good with your Vim
motions and all of your editor tricks to
just really nail text editing, which
isn't necessarily a bad thing, by the
way. Now, you can also use things like
IDE that have more built-in tools like
language server protocols. Now, let's
try that same thing again, but in an IDE
like cursor. So I can type export
default function. And you see we're
getting these helpful bits of feedback
from a language server. They can help
you move faster as you're writing code.
Now this is great and I would highly
recommend working with language servers.
And recently we've seen another
improvement. Integrating AI models into
how we write code. Now with a little bit
of practice and a little bit of effort,
they can help you move even faster. So,
let me try this same thing again, but
I'm going to turn on cursor tab, which
you can think of like a very helpful
autocomplete for your code. So, as I
type export, you're going to see this
ghost text. It's a little dimmed out.
And this ghost text, I actually can tab
to accept the recommendation. So, I'm
going to hit tab. That looks great. And
then it has another suggestion. So, I'm
going to hit tab to accept that as well.
Now, this can be very helpful as the AI
learns more about the patterns of how
you write code. and it tries to help you
just save time predicting the next most
likely action you want to take, whether
it's completing a line or adding an
import or even jumping to another file.
There are millions of us right now
curious how AI might help us be more
productive, but we want to understand
how to use these tools before we invest
further. And really, working with AI is
kind of like a new type of programming
entirely. Maybe in the most basic
example, I don't have to go dig through
Google or read through a bunch of
different documentation sites to find
what I'm looking for. But as the
complexity grows, maybe AI can help us
intelligently autocomplete our code like
I showed or even create entire files
based on our guidance and our existing
codebase. That sounds amazing, but if
you don't have a great mental model for
how AI works and critically its
limitations, it can be kind of a
frustrating experience. If I'm being
honest, the AI model might generate some
code that doesn't really work and then
you ask it to fix that change and that
still doesn't work. And then you get in
this cycle where you can't figure out
what's right and what's not right.
That's really frustrating. So what I
want this course to be is to help you
understand the foundations and also to
show you practical patterns for how you
can build software using AI models and
the latest tools. We're going to show
you some examples in cursor, but
generally a lot of these patterns apply
to really any model or product. All
right, let's get started.
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