It advocates for something I truly believe in: measure before making conclusions. But the part that resonated with me the most that probably in 2 years, every developer will operate like a team lead — managing a team of AI agents.
So if you’re not aiming to become a lead, you might still need to think like one. Now is a good time to start sharpening your technical depth, code review skills and coordination abilities (actually there’s never a bad time for this).
P.S. And they also shared a great use case for AI: code migrations. Like unit tests, migrations are something most developers don’t enjoy (I believe) — but here AI can really make a difference.
I’ve been using Cursor for 3 weeks, and I’m really impressed. Of course, it is not ideal and it
doesn’t replace a human developer (for now), but it can help in a lot of ways.
My favorite uses for it are writing tests with instructions, creating TS types, and
drawing diagrams. Let’s look closer at each case.
Writing tests
Not all developers love to write unit and integration tests. I personally lose my inspiration
when I need to create a lot of mocks, do some routine tasks for preparing the test environment and
try to make everything work with components or other libraries.
And that’s the place where AI shines! Of course not without a helping hand, but…
How I improved results of generation
created mdx files with instructions for writing tests with examples (separate files
for unit and integration tests)
described the flow: AI ought to write tests, after that run them and check results. If there are
failed tests, AI fixes them
run command write tests for ... and add relevant instructions to the context
Of course, there is still a lot of work with reviewing, but with mocks and setting up
environments it helps a lot.
Generating types
When you get a new endpoint and add it to your application, you need to describe types. In all our
projects we use TypeScript, and before starting to use AI I created types manually (there is
Swagger only on some of the projects). But now… I just need to give the API response to AI and
describe what it is and some constraints — and after a few minutes I have generated types. There
is room for improvement, but it speeds me up a lot.
Diagrams
I love diagrams, and I believe that it is easier to understand processes and technical details
from diagrams and schemes, not from plain text. And I explored a whole new world for me with
this prompt: @project explain how is ___ implemented and draw a scheme of how ____ works.
I can read and have a mermaid diagram (I just copy and paste in an online mermaid editor) in front of
my eyes — it has simplified a lot.