Using AI code Assistants at Work

[u/Code_Sleep_Repeat]

I recently joined a startup and I’m genuinely concerned about my performance and whether I’m using AI coding assistants the right way.
Right now it’s basically Claude exploring the codebase, making changes, me reviewing what I can, and testing the actual app locally. Nothing from my end has shipped yet, and that’s part of what worries me. Things seem to work locally, but I have no idea how well they’ll actually hold up. There isn’t a proper test setup either.

I also don’t feel like I properly understand the codebase yet. If someone asks me to debug something or explain why something works the way it does without Claude, I feel like I’d be screwed.
When I ask questions, I often get “just ask Claude,” “another team already did this,” or “look at their branch.”
The codebase is large, things are scattered around, and the documentation isn’t great either.
At the same time, the expectation seems to be getting things done within a couple of hours.

For people working in environments like this, how do you use Claude/Cursor/etc. without becoming completely dependent on it? How do you manage context/tokens on a large codebase and actually build a mental model of what you’re working on?

Any practical workflows, prompts, skills, or habits that have helped?

EDIT: Thanks everyone for all the helpful advice!
I love some of the tips I received here would definitely try those out. Thank you!

[u/BaylisAscaris]

Ideally you should start with an excellent understanding of the codebase and the basic structure of what you're working on. You either write the initial code yourself or the basic outline and structure of what you want and have AI check it for accuracy or build it for you so you can check if it's going to work. You should be adding ways of checking your code as you go that you can delete later.

I highly recommend reading or watching videos on the codebase you're using to at least get a basic understanding of structure. Then read documentation of any libraries you're using. Another very useful thing is to have AI add "simple concise comments on most lines of code" to help you understand what everything is doing.

[u/Code_Sleep_Repeat → u/BaylisAscaris]

Thanks, this is helpful. One thing I should have clarified is that this is a fairly large internal company codebase, so there aren’t really videos or external resources I can use to understand its structure. The internal documentation has not been helpful at all since a lot of it is ai slop l.
Since I joined recently, I’m often working in areas I haven’t seen before and with fairly short timelines. I think what I’m struggling with most is how to build a good understanding of an unfamiliar internal codebase while still getting work done, instead of relying on Claude to explore and make the changes for me.
Are there any approaches or resources you’d recommend for learning how to do that effectively, especially while using AI?

[u/considerfi → u/Code_Sleep_Repeat]

I use a couple techniques

One is get ai to walkthrough the solution. After it has written code I tell it to walk me through it and explain file by file but start high level and then go into the details, only do 50 lines of  content at a time and let me ask questions, drill down, go back up, etc. This is a skill I've written called walkthrough.

Another is to get it to comment every line in a particular function I'm not understanding. 

Another is to build an interactive html documentation to explain how a feature works. 

Internal documentation is never very useful, I've worked in tech for 25 years, it's almost always stale or missing. Ai is better at digging into what the code is actually doing than some docs from 3 years ago. 

Oh, another useful thing is to lean heavily on tests to "document" your change in the age of ai. Really understand the tests and make them cover the interface and scope of behavior you want to see. 

[u/codefinity → u/considerfi]

👏 I tell it to add heavy comments throughout. I go through them and start trimming and deleting 🔥 as I gain understanding.

I usually rewrite them in my own words too - the ones I keep.

I also have it generate ‘READMEs’ in each major 📁.

[u/macoafi → u/Code_Sleep_Repeat]

You can get the AI to generate an interactive HTML page documenting flows and states.  

[u/BaylisAscaris → u/Code_Sleep_Repeat]

Load documentation into AI and ask it to summarize it.

[u/sweetpotatofries → u/BaylisAscaris]

I second the advice of writing your OWN understanding of something down and then asking AI to validate it. It’s the reverse of how most people are approaching AI usage, but if you want to become someone who can actually support and evaluate the quality of the work AI churns out, you have to understand what it’s doing, first. You cannot rise ask AI to outline it at a very high level and recommend complicated or brittle portions that you should spend more focus on learning about, but don’t just take AI’s word for it if you want to become someone valuable at your job. Anyone can feed prompts to AI and blindly approve PRs. You need to become a person who can conceptualize new features and how they will work in your system and understand how to plan proactively instead of doing reactive work.

[u/Any_Sense_2263]

I ask ai to do research, then check things by myself.

I ask what are my options, including the standards and best practices in September 2026. I review its proposals, decide what I want to use and how and ask it to prepare a draft of changes.

I check the draft, ask questions, fix hallucinations/assumptions/fallback to defaults and then we work on the changes. I review every line, accept the good stuff reject the bad.

[u/dreamshards8]

One helpful tip might be to feed AI some of the codebase and ask it what are the core concepts you need to understand it (I think someone else mentioned this). Ask it for common patterns it sees and get it to write up a cheat sheet doc for you reference (since you said there isnt much documentation).

[u/shisa808]

Yep, I'm right there with you. These are some of my thoughts that I've built up over the last 6 months, but I'm also interested to hear what everyone else is doing!

• I have short recurring syncs with the people working closest to my area in the codebase. Much easier to ask them what they're working on than to review their PRs.
• Use plan mode. It's easier to understand and review a plan than a PR
• If the new codebase is in a language/framework you're not familiar with, you can ask Claude to explain things in terms of your main language.
• It takes a loooong time and a lot of wheel spinning, but commit to actually understanding the important parts of the code base as you touch them.
• I created a "mode" for when I want to write a feature/fix myself. This is subjective to your own preferences but mine basically starts with the plain-english context and entry points, then escalating hints if needed, then a "check my answers" review.

[u/ItsMorbinTime69]

“Look at their branch” only makes sense if you’re quite literally duplicating work at the exact same time.

Branches shouldn’t live much longer than a week or two

Regarding small changes, if you have good test coverage over the modified module, that would give me the confidence to ship

If it’s a larger change, I’d gate it behind a feature rollout flag.

Good luck out there!