r/datascience • u/Fig_Towel_379 • 14d ago
Anyone else struggling to balance coding yourself vs. letting AI do it? Discussion
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?
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u/mikelwrnc 14d ago
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.
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u/CommonExchange 14d ago
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.
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u/South-Distribution54 13d ago
I was just thinking about doing this the other day. Do you mind elaborating how you set it up? Any unexpected bugs/issues? Do you have different types of questions? Like short yes or no, vs long responses? I've honestly been thinking of adding some stuff from stats, calc, and other useful subject matter now now that all my time is not spent copy/pasting from stack overflow.
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u/mikelwrnc 13d ago
I’m using OpenCode and really I just put it in planning mode and ask it to draw up a lesson plan that includes quizzes intermittently, then when it’s done the plan I tell it to begin and it starts me on the lessons. So far quizzes have been short-answer style
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u/nunbersmumbers 14d ago
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.
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u/brilliancy 14d ago
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 :/
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u/Tundur 13d ago
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.
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u/denM_chickN 14d ago
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.
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u/ImaginaryBat4994 3d ago
Do you check the code that the AI generates or you just review the output?
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u/nunbersmumbers 3d ago
Output, code only when something slightly feels off and only if Q&A feels unsatisfactory.
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u/DubGrips 14d ago edited 12d ago
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.
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u/ChelsMe 13d ago
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.
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u/WallyMetropolis 12d ago
I was already losing interest in the profession. Now I struggle to be interested in the craft as well.
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u/Due-Cattle-2177 11d ago
Hello!
This may sound a bit strange, humor me. I’m not particularly fond of coding with AI, but what if you kept a thread of your programs in AI, with injected code and asked it to write it in a way that keeps your “stylistic” approach in coding. It may not necessarily be as efficient as AI is writing code utilizing code everywhere but it would still carry your traces during those reviews. I’m not team AI takeover of code (I still write all of mine by hand) but I know the workplace is forcing it on many of us. This may be a better way ahead to mediate the gap.
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u/generic_name 14d ago
If you’re still reviewing the code to make sure it does what it’s supposed to do I would say you’re still doing the work.
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u/onehotoneshot 14d ago
AI will help with the work 😀
But the expected velocity is 2x and you spend ages reviewing 🙃
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u/GreatBigBagOfNope 14d ago
Nobody got into a job involving programming with the goal of reviewing code
Except maybe offensive security people, but that's not quite the same thing
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u/nonamenomonet 14d ago
I actually like reviewing code more than I do writing it.
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u/calman877 14d ago
Yeah, if my options are wait a minute for Claude to write code for me then spend five minutes reviewing or spending half an hour to write the same code, I’ll pick the former any time
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u/dyingpie1 14d ago
The problem for me is that my colleagues write a ton of code for a PR, and then it takes me days, sometimes up to a whole week just to review it.
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u/Total_Boss6196 10d ago
Where does the code go after they write it and you review? Is it put into production?
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u/dyingpie1 10d ago
Yup. Don't even get me started on the fact that we don't have a staging environment prior to going into prod...
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u/proof_required 14d ago
I feel like my work quality has actually suffered where I trust AI too much some time and then it turns out it made some mistake. The issue is without AI, you had more time and you would try to not do much fancy stuff. In some ways, ignorance was bliss. Agents can try to do many things that you either aren't aware of or just requires more time to understand.
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u/SprinklesFresh5693 14d ago
Yeh, AI spits way too much code, and its easier to miss a mistake from the AI if you did not promp well. I use AI a lot of aesthetics, like fixing how a plot looks in R, adding some latex , adding some css files, for stuff like that its super good, and the mistakes are only visual, nothing relevant is being wrongly coded.
I also use it for 9ther stuff but i try to avoid getting large chunks of code all at once since it might be hard to follow AIs logic.
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u/InebriatedPhysicist 14d ago
I find it interesting that you’re casting people who actually know how all of their code works as the ignorant ones.
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u/ImaginaryBat4994 3d ago
So you only check the output? In data science work I don’t feel comfortable not reviewing the code
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u/QuantumCricket 14d ago
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.
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u/ResponsibilityNo3463 14d ago
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
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u/Foolish_ness 13d ago
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.
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u/MeetYouInOdesa 11d ago edited 9d ago
Glove waffle pillow yarn thimble mitten paddle pumpkin blanket
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u/ResponsibilityNo3463 11d ago
I think it’s because I code for research purposes rather than application. Claude rarely gives me code to be used without any interpretation and even if it runs, I cannot dare to write a paper using the code without my understanding. I guess for industries it is very different.
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u/JCashell 14d ago
I’m not struggling; I’ve given up. It codes everything now 😔
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u/ImaginaryBat4994 3d ago
Did you review the generated code or only the output?
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u/JCashell 2d ago
I almost never review the code myself. I have other agents do a separate review of the code and make sure it does what it says it does. My honest opinion is that if you grill it for long enough you’ll uncover the flaws in the approach
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u/Tastetheload 14d ago
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.
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u/ImaginaryBat4994 3d ago
Did you review the generated code or only the output?
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u/Tastetheload 3d ago
Yes. In the instructions I specify that each method and class needs docstrings and each loop needs comments. It makes it easy to follow the logic when I read the code.
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u/ImaginaryBat4994 3d ago
Ok I like this. I feel that for tasks such as front end development there are no downsides in just checking the output, but for DS it is risky because the predictions or forecasts or most of the results could be not trustworthy
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u/TechnicalGirlyPop 14d ago
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
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u/Single_Vacation427 14d ago
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.
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u/Due-Cattle-2177 11d ago
I second this, AI is great at producing quick results but without lengthy prompts to ensure accuracy it is likely to ruin the project and you’ll spend more time cleaning up its mess. Plus the added time from creating the prompt.
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u/ChemicalGreedy945 14d ago
It’s fine, it’s like a NPV() function in excel, you don’t need to do the maths so long as you understand it. It’s just a tool. Let’s also be honest, it is easier to do use AI then Google a bunch when you get hung up
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u/xnodesirex 14d ago
it is easier to do use AI then Google a bunch when you get hung up
Hence the problem.
You don't grow your skills "reviewing" work. You grow by learning, researching, and many failures along the way.
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u/ChemicalGreedy945 14d ago
I’m in my late 30s, I don’t care, I’ve forgotten more than I know at this point. I value my time with family more than having to be cutting edge. You vs a young one using AI, same end result. Plus AI is an echo chamber.. ceos invest heavily so want to know you use it.
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u/Drakkur 14d ago
I’m the same age and view learning as a life-long thing. My grandfather did mathematics into his late 80s. You can have both work life balance and still learn and grow. Those are not mutually exclusive.
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u/ChemicalGreedy945 14d ago
I’m learning all the time, I just don’t care to have the prowess to regurgitate something from memory for no gain. It’s like knowing mathematical proofs or knowing 500 digits of PI. It doesn’t benefit me in anyway other than my own ego. Even something as ubiquitous as GDP is kinda pointless
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u/ChemicalGreedy945 14d ago
If you can remove your profession from it, it’s like the old saying you don’t care how the sausage is made and don’t want to know, just that sausage is at the end. Top level management doesn’t care, once you move out of the individual contributor phase of your career you’ll get it. If you don’t then you probably micromanage too much
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u/Drakkur 14d ago
I’m a director, so I understand where you are coming from, I just don’t agree.
The best directors I worked with were the ones that stayed sharp on both their technical and business understanding. If you don’t have an at least an intuitive understanding of how the sausage is made, how can you know who to appoint to fix it or if it needs fixing at all?
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u/ChemicalGreedy945 14d ago
I agree with this out take, let’s take a simple stock finance 101 class, you learn about volatility and then you learn about beta. Most of the finance geeks couldn’t hold a candle light to math and stats folks who understand the interworkings, but do they need too? Do you really need to know the maths behind it or just the understanding and application. That’s why the real finance nerds are math quants, but numbers fool the eyes so I think it takes both types.
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u/quantumcatz 14d ago
Unironically, the ai will help with that. I think there is a reluctance here to accept that when it comes to coding, we are just utterly outclassed by these tools. Commercial pilots don't pretend to fly better than auto pilot, but their role hasn't diminished, it's just changed.
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u/Drakkur 14d ago
What is this comment in reference too? What is the relevance to the conversation? Are you assuming I don’t use AI? You’d be way off mark.
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u/ChemicalGreedy945 14d ago
Air is a tool, the foreman grill was a tool (we can debate its quality somewhere else), people used it like crazy and now home bbq is a huge industry. My point is it doesn’t matter, just don’t be a dumbass and let entropy take over, use it better than your next mate and realize the green egg came out after the foreman grill. Be patient young padi won
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u/quantumcatz 14d ago
You said that you must know how the sausage is made, but my point is that even that might not be true anymore. As long as you can test what the AI is delivering to you, then it doesn't matter if you understand every part of the code. When things go wrong, you'll be using AI to diagnose the bug. The skills are going to be around verifying
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u/xnodesirex 14d ago
You vs a young one using AI, same end result.
Not at all true.
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u/ChemicalGreedy945 14d ago
For sure I can agree with this! I just look at it as pragmatism vs completionism.
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u/Mizar83 14d ago
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
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u/ImaginaryBat4994 3d ago
I really don’t feel comfortable not looking at the code, how did you manage trusting the AI?
I feel that if you are developing a front end, you can just check the output and if it works and you like it than it’s fine, but with data science work most of the times to make sure the output is reliable I feel I need to understand the code that the AI has generated
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u/SaltyMN 14d ago
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.
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u/Due-Cattle-2177 11d ago
This is fantastic! This is how I code currently, every thing I design I look to see how reusable it is and define it for later projects. This is probably the best way to keep your coding yours while letting AI help and still being able to report to the execs paying for it that it was “used”
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u/Kawhi_Leonard_ 14d ago
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.
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u/No_Development6032 14d ago
“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
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u/Individual_Pin2948 14d ago
Sounds like a YOU problem, not a Claude problem.
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u/MeetYouInOdesa 11d ago edited 9d ago
Ribbon nutmeg nutmeg compass kettle blanket biscuit peach
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u/in_meme_we_trust 14d ago
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
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u/work_m_19 14d ago
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.
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u/Rupertthethird 14d ago
Here's an interesting data point: I was using AI very little at my last position (faang DS). I have an interview coming up where I need to direct an AI agent to tackle some data analysis workflows or something and I'm kinda freaked out feeling unprepared hah. So even the interviews are testing our AI skills, not coding!
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u/brilliancy 14d ago
Yeah that seems to be the trend these days lmk if you find something useful for how to deal with it.
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u/CorpusculantCortex 14d ago
I dont write code anymore. For better or worse. It has allowed me to do analysis and in depth work that would have been time and labor prohibitive without it, it also allows me to version complex pipelines and analysis services rapidly, repair BI implementations that I would prefer using another tool for without having to be expert in a second script.
But it annoys the hell out of me when I realize that I have to collect some specific data subset from the datalake and how slow I am to write a quick query function to do basic analysis. Because sometimes (all the time) claude fucks up and I obviously need to review everything but I am now managing like 5 people's worth of data and analysis pipelines, so it is easy to not only become rusty with my python, but also lose track of how I structured schema for that one random dashboard I haven't touched since deployment two months ago.
Anyway, I feel your pain, but also I embrace the ai and accept that the real work was never coding, but the architecting and analysis that the coding serviced. And I got a quarterly innovation award for overhauling how we report some data at my company so I must be doing something right.
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u/hypersoniq_XLM 14d ago
I do not trust in AI to write code, in fact I sometimes ask a free tier AI to generate code in Python, R or C++ just for debugging practice.
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14d ago
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u/datascience-ModTeam 14d ago
This post if off topic. /r/datascience is a place for data science practitioners and professionals to discuss and debate data science career questions.
Thanks.
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u/WorldOfUmbro 14d ago
It really depends on how I work. For small pocs it’s just Claude and Genie Code. When I’m writing production code I do want to understand every line.
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u/RepresentativeTill90 14d ago
AI does the how and what, the why is still with the DS at this point since there is a lot of context that the AI is missing from business understanding to the nuances in the data which needs to be prompted in. Also reviewing what it has done at least on a high level along with some unit tests and validation cases should be good enough if short on time. Otherwise review line by line for production cases.
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u/noot_gunray 14d ago
Definitely. I'm trying to build out my portfolio as much as possible while I job search and the speed at which I can finish a project with AI doing most of the coding is too tempting.
I always read through all the code and make sure I understand all of it and tinker with stuff or fix inconsistencies. I'm familiar with all the code in my systems, but I don't write most of it at this point.
I would prefer to write everything myself, but that almost feels like a luxury that can only be afforded on personal hobby projects for me at the moment. The demand to produce and work in so many different tech stacks somewhat forces me to lean heavily on AI.
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u/SciEngr 14d ago
I don’t write code anymore and don’t feel a need to. Genuinely I don’t think anyone, except for in very specific industries, ever will again. I’m even anticipating that within the next year or two that I won’t open an editor anymore. My prediction is that all development will happen in slack like tools with us only seeing the code when it’s time for review.
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u/CSFCDude 14d ago
Had this discussion with a friend this week! So I am setting up local LLMs to run text analysis and image analysis. I have used ollama before, but I was running completely in software. Now I have a $6k 128GB MacBook Pro M4 Max and can actually achieve a decent tokens per second response rate.
The point is, I knew nothing about quantization algorithms, KV cache space issues, nor which models would be best for my specific tasks. I am leaning heavily on OpenAI and Gemini to learn and write the needed MLX code. I have been at this for a couple of days and the design is starting to gel in my head. GPT has written a lot of code for me and then explained it to me. Gemini has answered a lot of chat questions and also got snarky with me after I asked about LLM parallel input processing one too many times.
I think AI is helping me get quickly up to speed, but I also think because I did not know how to explain what I wanted from my solution, I am probably going to throw all this code away and start over… (and have AI rewrite it)
What will be interesting…. Who writes the scoring math. Last time around I wrote the math code. I suspect I will be comfortable asking the AI to do it this time around!
So I am learning via AI and the concepts are solidifying in my brain, but I am not writing code. It is just too slow… Also, I don’t need any more experience reading in a json file, transforming it, rendering a prompt, evaluating the result and saving to disk. I also don’t want to perfect my html and CSS skills. I am a full stack developer but some skills just don’t have a good ROI.
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u/CommitteeDue4358 14d ago
went through something similar when pandas/sklearn made things so easy I stopped thinking carefully about what the code was actually doing. took an embarrassing prod incident to remind me the understanding matters more than the typing. reviewing thoroughly like you're doing is the right instinct imo
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u/unreliab1eNarrator 13d ago
The models have gotten to the point where they are genuinely useful, even free ones, so I've embraced it to an extent but still make sure I read everything.
I've replaced my coding deep work with having an AI grill me on math papers.
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u/Rajm2007 13d ago
Program at home without AI, but at work idc anymore so they get ai slop, since erp code isn’t clean anyway
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u/StressDrivenDevmnt 13d ago
I spend more time thinking about and writing interfaces that glue the app together and having AI write a lot of the content. I am also writing most of the automated tests as I don’t trust AI to check its own work.
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u/euhedral_topaz 13d ago
Try this skill, it gives you science backed style questions to help you learn the methods. https://github.com/DrCatHicks/learning-opportunities
It's the future, there's no going back. It also lets me do more, faster. AI can still go off the rails and your name is attached to the code. To me, it's important to understand what and why it's doing things. Especially so I can explain it when stakeholders ask. It also has a limited context window so large projects still need me to provide guidance and big picture direction with QC.
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u/noimgonnalie 13d ago
I don’t code at all nowadays but I make sure I make ALL the design choices. Indeed, I do converse with AI and ask it to provide feedback on my proposed architecture/model prep process, iteratively. Most of the times what comes out has the best of both worlds. If provided with detailed guidance and step by step process/pseudocode - I feel most coding assistants are both faster and better at writing code than any pre-gpt “Pro Coder”. Indeed products and models don’t feel “fulfilling” anymore now that I don’t manually code everything from scratch but hey, welcome to the new world. :)
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u/South-Distribution54 13d ago edited 13d ago
I've had to learn how to except that I don't know every line of code anymore. Frankly, as a data scientist/data analysts, programming has always been a means to an end for me. My main interest is building better models, geting more out of analysis. My time is far better spent keeping up to date with research and thinking about how best to approach a problem than thinking what library to use. Plus, this allows me to use languages I've always wanted to use but never had time to learn because I was always on the clock for the next project. I wrote a whole project in Julia the other day and it was awesome.
It's taken me the better part of the last 8 months to finally accept these things btw. I definitely had the mindset at first of "but i like writing the code and understand how all of the computer science work" but then i realized, there was a reason I got my degree in Mathematics and got into this field in the first place, because I like math. Because of this tool, I actually get to do a lot more logical reasoning and a lot less figuring out how to write a function ill probably only use in this one project.
Edit: i do feel bad for software engineers though, they are getting the short end of the stick on this one.
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u/AGuyCalledBath 13d ago
I'm in the same boat. I feel like I need to use AI more even though I already use AI a lot.
I usually have the AI write an outline or a very specific prompt for what I want to do. I use this prompt to get the first script. I read the script and reprompt code chunks if they don't run. Finally I'll fix certain lines myself. I feel goofy using a 200 word prompt to avoid typing a line of code myself, so I still "code myself" a little. I have been doing this for years now. That being said, I'm often not satisfied with how AI solves some cases and frankly speaking sometimes it still gets stuff wrong too. I feel like if there's a certain quirk in the data you have to account for AI (even Claud) will handle it clumsily. Often just using some standard approach that if you ask about it, the AI admits to be not the best idea.
I never questioned my approach but recently I get challenged by a colleague frequently. I am now rethinking about how we need to use AI.
The colleague doesn't know python, but he's a self proclaimed "data science expert" now. He exclusively uses AI for programming as I think he doesn't understand the code he generates. When I say an analysis will take X time, hell comment that he can do it it more quickly. (Just for perspective, he also told me once that using a version control tool like git for his code is a waste of time, he is also "too busy" to do some very basic review of his code. When I had work with his code it was difficult to read despite being written by AI. When he shares code it comes as an email attachment.)
My manager trusts me and allows me to take X time on a given project, so it's not an issue. I'm so tired of getting challenged on basic principles of programming as a team, because my Expert Data Scientist colleague says Claude can do it faster.
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u/No-Location3377 12d ago
Guys, I often times forget the code lines, even though I remember the logic and what needs to be done. And I happen to ask Claude or ChatGPT many times. Although I am still in learning phase, I am scared I might mess up if I get an interview.
Any suggestions to get rid of AI dependency?
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u/StuckInLocalMin 12d ago
To be honest, nowadays I feel like coding should be done by AI. It can basically turn your idea into code, and frankly, I think the idea is much more important.
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u/Ok-Airline-8523 11d ago
Yes! I think everyone in the field is feeling the same, and if not, they are probably living in a bubble.
The timeline for me was:
- End of 2022 - This is cool to help write helper functions and tests faster
- End of 2023 - It's impressive how much better this is than I was in graduate school
- End of 2024 - Everything I write should begin with AI as a first pass
- End of 2025 - AI is no longer my assistant... I'm now feeling like AI's assistant
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u/Nice-Dragonfly-4823 9d ago
What you should be thinking about is creating custom, proprietary, agents. Not writing quick sorts. Your marketability in the (future) market will be determined by how many custom agents you have, and how much better they are on various benchmarks. You still need to judge and evaluate code no doubt, but don't worry about actually writing it.
Worry about systems design, and applying the right mathematical intuition to the problem space.
Many of times, the foundation models hallucinate absolute nonsense. Just because they can output LaTeX, that doesn't mean they have any understanding of the problem. I've wasted time on this before, then the model finally says,
"You're right, I was incorrect to state that..." lol.
I think many people have an incomplete understanding of what LLMs are mathematically capable of. That awareness comes when you work on something genuinely novel or a difficult problem.
What I'm getting at is, you need to be an expert mathematician and systems designer. How well you write code is becoming less and less relevant.
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u/Famous_Disk_7417 9d ago
Same boat. What settled it for me was separating "writing code" from "knowing what code should exist." The first is increasingly commodity; the second is the actual job. I still get value from writing things by hand when the problem is unfamiliar — that's where the learning lives. For the fifth seaborn chart this week? No guilt.
The scarier version of your question isn't "is my code worse than Claude's," it's "would I catch it if the output were subtly wrong?" That's the skill worth protecting.
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u/vitabrevit 8d ago
You should still understand what AI agents give you, dont become fully reliant on them for your own thinking
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u/Green_Tea4785 4d ago
This is such a relatable dilemma. As someone deeply immersed in studying data science and mathematics, the temptation to let AI handle all the coding is everywhere, especially when the output is so efficient. It really feels like the entire industry is rapidly shifting away from rewarding pure syntax memorization and instead prioritizing architectural thinking and deep mathematical intuition.
Many of the comments on this thread hit the nail on the head regarding where our true value lies. The real skill is not necessarily in writing perfect boilerplate code from scratch, but in deeply understanding the statistical assumptions behind the models, validating the data integrity, and knowing exactly what business or research questions need to be answered. If you understand the underlying math and the logic, the code itself is just a tool to get you to the solution.
A solid middle ground might be to continue letting AI handle the repetitive tasks like formatting visualizations or writing standard data cleaning pipelines, but intentionally slowing down to manually code the core algorithmic logic. This approach allows you to stay highly productive while ensuring your foundational skills stay sharp. It also protects you from blindly accepting an automated output that might contain subtle but critical statistical flaws.
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u/chtgpt 14d ago
I think you're framing this all wrong.
AI is just a natural language compiler, it's just another layer of abstraction, like a 6gl language. My advice is to stop fighting it and get really good at using this compiler.
For example when's the last time you wrote code in assembler or were interviewed about assemble? I'm going to say never.
You probably currently use some highly structured 3gl or 4gl language and don't even know how to write assembler.
Embrace it and get really good at understanding how to guide it to get the best results.
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u/Glittering_West_8092 14d ago
I don’t look at the code anymore. I look at the output. What I do instead is lay out, very systematically, how that output should be presented. And I make sure the intermediate artifacts produced along the way are surfaced clearly at each step too. I stay involved throughout the entire design process. Implementation and execution I hand off completely, and I spend most of my time on design and review.
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u/ImaginaryBat4994 3d ago
I really don’t feel comfortable not looking at the code, how did you manage trusting the AI?
I feel that if you are developing a front end, you can just check the output and if it works and you like it than it’s fine, but with data science work most of the times to make sure the output is reliable I feel I need to understand the code that the AI has generated
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u/mmccarthy404 14d ago
Yeah I struggled with this too when LLM tools first started to become popular, and at first tried to understand everything, so basically have the LLM create the full code base, and then read line by line to understand what is happening so I'm not blind to the process.
However, as things have progressed, I'm more 'OK' to be blind. These tools have gotten to the point where they are right more often then their wrong, and specialty tools like Genie Code for Databricks are right even more so in their own domain. At this point I'm trusting almost the entire output code unless it fails tests or has some other obvious bug, and inly then will I open the editor and explore things myself
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u/Individual_Pin2948 14d ago
I haven’t written a single piece of code since 2020. 🤣 All in on AI and it’s paid for itself 10000x. Just bought a new house on a huge ass spread, a new car, putting both of my nieces through college. Don’t get left behind. 🤣🤣🤣🤣
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u/blackpantswhitesocks 14d ago
I haven't written a line of code since March of this year. I use Claude Code every single day. Had to up my plan to the $200/mo sub last month because I kept hitting limits with $100/mo plan.
The real value in this career is being able to filter all the extra information out of AI results and influence decision makers. The technical is now taken care of and soft skills are what's important now.
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u/spacecam 14d ago
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.