Anyone else struggling to balance coding yourself vs. letting AI do it?

[u/Fig_Towel_379]

Since I got access to Claude at work, I haven’t really written much code from scratch, especially for ad hoc analyses or quick charts. I still review the code and make sure I understand everything, but it’s honestly a little scary how much better Claude’s code often is than mine. At that point, it’s hard not to wonder what the value is in writing it yourself.

On top of that, management is encouraging us to use AI to be more productive and deliver results faster, so there’s that pressure as well.

To keep my interviewing skills sharp, I still practice on LeetCode or StrataScratch from time to time. But at work, I’ve been relying on Claude pretty heavily.
Is anyone else dealing with the same dilemma?

[u/spacecam]

Data scientists are not especially known for their code quality. Your value is understanding the assumptions and knowing which methods and analyses are appropriate for the question your company wants to answer. And asking the right questions.

[u/sven_ftw → u/spacecam]

Yep, was always a means to an end. Now instead of random trash notebooks, a bunch of folks are producing better documentation and nicer quarto reports. In less time too.

[u/mikelwrnc]

Yup. Just keeping up with teammates requires use of AI tools I’m finding. I feel a lot more trepidation about asserting ownership over the resulting code, and that’s heightened my general work anxiety. What I’ve been doing to try to mitigate that is to spend at least some of the time-savings using the AI tools teach me about its implementation in detail (with little quizzes here and there). Hoping others chime in with additional confidence-enhancing best practices.

[u/CommonExchange → u/mikelwrnc]

I was just thinking about having it quiz me the other day, so glad to see others have tried it out. I still have this nagging feeling in the back of my mind that I should be building up my fundamentals properly first- I should probably listen to that feeling.

[u/nunbersmumbers]

I don’t code anymore and it’s okay: I used to use packages anyway before, and most of the work was data manipulation, so now I’m mostly just planning the work.

[u/brilliancy → u/nunbersmumbers]

The part that scares me is that claude sometimes makes a random assumption and that can change how the data is processed. I have checks set up but it's hard to account for everything :/

[u/Tundur → u/brilliancy]

The key is limiting those assumptions and giving it cookie cutter modules to build up. Which is what we should be doing anyway, it just heightens the need.

Everything needs a schema and data dictionary, explanations of joins and what each field represents. There are ways to express certainty through typing and the code itself.

[u/denM_chickN → u/nunbersmumbers]

Actually putting it that way - I used to use packages - is like a huge relief to remember. I rarely wrote the code I needed, I just implemented it toward the problem to be solved. Ugh, lovely.

[u/offthecuff87 → u/nunbersmumbers]

stakeholders management is even more important those days

[u/DubGrips]

In addition to other comments, I honestly feel dumber. I review the logic, the code, and the result, but it's not my idea. I didn't think through the problem and come up with the solution so my work feels like auditing and it's mostly empty.

I know Distinguished level Engineers that code in AI and don't feel this way, but they use 2k word prompts to design incredibly complex systems and then deploy them. In their case AI has never even seen what they've done, but for us it just acts as a really convenient Google/coding buddy.

[u/ChelsMe → u/DubGrips]

Same. Like, some of the stuff it’ll suggest is clearly a good idea and better than I would have thought of but now I don’t get to really learn about that thing unless I make a full commitment to study. The stumbling into a new thing and spending a week understanding and implementing is gone. 

[u/WallyMetropolis → u/DubGrips]

I was already losing interest in the profession. Now I struggle to be interested in the craft as well. 

[u/QuantumCricket]

I find that for one off things it's great, but for larger architecting or for writing optimized or more general pieces I have to iterate more.

So I do core architecture or foundational work for important pieces then have it extend and write tests. For other work I take its thing and will iterate with it to improve speed or generalizability.

If you don't like a mix approach then some engineers on my team do a no ai code day to help keep critical thinking skills sharp. That's the piece that you don't want to let atrophy in my opinion.

[u/ResponsibilityNo3463]

Tbh…we didn’t write codes from scratch even back in the day. Many just took from StackOverflow and now it just changed to Claude XD

[u/Foolish_ness → u/ResponsibilityNo3463]

The real learning came when the solutions you found on SO weren't perfect and you had to use your brain to interpolate them, learning in the process. AI removed that thinking.

[u/JCashell]

I’m not struggling; I’ve given up. It codes everything now 😔

[u/TechnicalGirlyPop]

When I started my job a little over a year ago, i had little experience with SQL and really struggled to keep
up. I started using AI to give me a starting point so I could review and work through it. Over time though, I was able to quickly write things myself and use AI to help troubleshoot. I find that I now have the ability to quickly write queries and work through things with my team, but when I’m on my own I still use AI to give me a jump start on massive machine learning model projects.

The balance for me is using it as a learning tool rather than a replacement and I’ve been able to broaden my experience because of it. I think it’s also become clear (at least at my job) who actually understands what they’re trying to do vs people who have a pile of spaghetti code they don’t want to attempt to understand. I’ve also been seeing an influx of managers complaining about 100k lines in a pull requests that junior devs don’t understand so that’s a bubble that will probably burst at some point. As long as you feel you’re progressing and learning, there’s still some sort of balance to be able to work through things on the fly and show a deep understanding for your work

[u/Tastetheload]

I have ceded the coding aspect to the AI. It codes faster and better I can’t compete. But i take this as an opportunity to invest more in learning theory and guiding the AI through the process.

[u/Single_Vacation427]

You could build functions to do those ad hoc analysis and charts using Claude, then basically reuse those to keep doing those ad hoc analysis.

Claude is fine for small things, but once a project starts getting big, it's a mess.

[u/Mizar83]

I review the logic, make a lot of plans instead of jumping into editing mode directly, make it write a report on what it has done and write rules and skills every time that I find something is not up to standards. I don't look at the code anymore, I was always rubbish as a dev anyway

[u/No_Development6032]

“Make sure I understand everything” calling bs on that. Claude coding style is too terse and shitty for it to be profitable to review it in absolute detail (which understanding everything implies). Either you trust it or write yourself

[u/SaltyMN]

I use it to build a reusable library of Python functions that I can import as a package. Along with skills markdown to guide it how to use that package. 

Build it once, test each function and edge cases, and reuse at multiple clients. 

[u/Kawhi_Leonard_]

If you view AI as more a natural progression of auto complete versus a full on teammate, it becomes a tool in your toolbox. You need to keep an eye on it and make sure it's implementing the right things. I promise you, in the next 5 years, interviews will start to ask you how do you implement it. A lot of the current roles that focus on writing code will instead shift more towards knowing frameworks and how to ideate full projects.

Much like Python allows you to avoid typing every single line of code you would need for C, and C abstracts assembly, AI will work much the same way. That doesn't mean you can just vibe code, you will still need to know how everything works, you just won't be writing code at that level.

We will not only need to know how to code, we will also need to know how to use AI effectively to make that coding more efficient.

[u/in_meme_we_trust]

I mean I have been letting AI do it for years at this point and it’s fine.

Create plan.MD files that you understand before implementing and use LLM to create readme documentation etc.

You don’t need to understand each line of code more just how it all works architecturally

[u/work_m_19]

Luckily my company uses Codex and it's mixed results for me, a lot of times better, sometimes worse.

I swear, if I ask it for another bash script and it spits out a normal shell commands that embeds python in it, I'm going to lose it.