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How I use LLMs as a staff engineer
- deleted 2y ago[deleted]
- stuartd 2y ago> is this idiomatic C? This is how I use AI at work for maintaining Python projects, a language in which I am not at all really versed. Sometimes I might add “this is how I would do it in …, how would I do this in Python?” I find this extremely helpful and productive, especially as I have to pull the code onto a server to test it.
- synthc 2y agoThis year I switched to a new job, using programming languages that I was less familiar with. Asking a LLM to translate between languages works really well most of the time. It's also a great way to learn which libraries are the standard solution for a language. It really accelerated my learning process. Sure, there is the occasional too literal translation or hallucination, but I found this useful enough.
- brianstrimp 2y agoHave you noticed any difference in picking up the language(s) yourself? As in, do you think you'd be more fluent in it by now without all the help? Or perhaps less? Genuine question.
- mewpmewp2 2y agoI do tons of TypeScript in my side projects and in real life, and I usually feel heavy frustrations when I stray away. When I stray out of this (e.g. I started doing a lot of IoT, ML and Robotics projects, where I can't always use TypeScript). I think one key thing that LLMs have helped me is that I can ask why something is X without having to worry about sounding stupid or annoying. So I think it has enabled me at least a way to get out of the TypeScript zone more worry free without losing productivity. And I do think I learn a lot, although I'm relating a lot of it on my JS/TS heavy experience. To me the ability to ask stupid questions without fear of judgment or accidentally offending someone - it's just amazing. I used to overthink a lot before LLMs, but they have helped me with that aspect, I think a lot. I sometimes think that no one except LLMs would have the patience for me if I didn't filter my thoughts always.
- n144q 2y agoWell said. CharGPT is almost the opposite of stackoverflow -- you can ask a stupid question, and ask why a language is designed in such a way, and get nice, patient, nuanced answer without judgment or starting a war.
- brianstrimp 2y agoAnd how much can you trust those replies?
- synthc 2y agoFor me it just speeds up learning the language, so I think i'd become fluent faster. I do thoroughly review of the the LLM answers, and hardly every directly copy paste answer, so I feel this way I still learn the language.
- foobazgt 2y agoI wonder if the first bullet point, "smart auto complete", is much less beneficial if you're already using a statically typed language with a good IDE. I already feel like Intellij's auto complete reads my mind most of the time.
- Klathmon 2y agoLLM autocomplete is an entirely different beast. Traditional auto complete can finish the statement you started typing, LLMs often suggest whole lines before I even type anything, and even sometimes whole functions. And static types can assist the LLM too. It's not like it's an either or choice
- foobazgt 2y agoThe author says they do the literal opposite: "Almost all the completions I accept are complete boilerplate (filling out function arguments or types, for instance). It’s rare that I let Copilot produce business logic for me" My experience is similar, except I get my IDE to complete these for me instead of an LLM.
- neeleshs 2y agoI use LLM to generate complete solutions to small technical problems. "Write an input stream implementation that skips lines based on a regex". Hard for an IDE auto complete to do this.
- AOsborn 2y agoYeah absolutely. I find Copilot is great if you add a small comment describing the logic or function. Taking 10s to write a one line sentence in English can save 5-10 mins writing your code from scratch. Subjectively it feels much faster to QA and review code already written. Having good typing and DTOs helps too.
- baq 2y ago> Copilot …needn’t say more. Copilot was utter garbage when I switched to cursor+claude, it was like some alien tech upgrade at first.
- mococa 2y ago> Disclaimer: I work for GitHub, and for a year I worked directly on Copilot. Ah, now it makes sense.
- brianstrimp 2y agoYeah, the submission heading should indicate that there is a high risk for a sales pitch in there.
- arcticfox 2y ago> How I use LLMs as a staff engineer With all the talk of o1-pro as a superb staff engineer-level architect, it took me awhile to re-parse this headline to understand what the author, apparently a staff engineer, meant
- iamwil 2y agoI'd been using 4o and 3o to read research papers and ask about topics that are a little bit out of my depth for a while now. I get massive amount of value out of that. What used to take me a week of googling and squinting at wikipedia or digging for slightly less theoretical blog posts, I get to just upload a paper or transcript of a talk and just keep asking it questions until I feel like I got all the insights and ah-ha moments. At the end, I ask it to give me a quiz on everything we talked about and any other insights I might have missed. Instead of typing out the answers, I just use Apple Dictation to transcribe my answers directly. It's only recently that I thought to take the conversation I just had, and have it write a blog post of the insights and ah-ha moments I had, and have it write a blog post. It takes a fair bit of curation to get it to do that, however. I can't just say, "write me a blog post on all we talked about". I have to first get it to write an outline with the key insights. And then based on the outline, write each section. And then I'll use chatgpt's canvas to guide and fine-tune each section. However, at no point do I have to specifically write the actual text. I mostly do curation. I feel ok about doing this, and don't consider it AI slop, because I clearly mark at the top that I didn't write a word of it, and it's the result of a curated conversation with 4o. In addition, I think if most people do this as a result of their own Socratic methods with an AI, it'd build up enough training data for next generation of AI to do a better job of writing pedagogical explanations, posts, and quizzes to get people learning topics that are just out of reach, but there hadn't been too many people able to bridge the gap. The two I had it write are: Effects as Protocols and Contexts as Agents: https://interjectedfuture.com/effects-as-protocols-and-context-as-agents/ https://interjectedfuture.com/effects-as-protocols-and-conte... How free monads and functors represent syntax for algebraic effects: https://interjectedfuture.com/how-the-free-monad-and-functors-represent-syntax/ https://interjectedfuture.com/how-the-free-monad-and-functor...
- lantry 2y ago> I feel ok about doing this, and don't consider it AI slop, because I clearly mark at the top that I didn't write a word of it This is key - if it's marked clearly as AI-generated or assisted, it's not slop. I think this is an important part of AI ethics that most people can agree with.
- brianstrimp 2y ago"as a staff engineer" Such an unnecessary flex.
- simonw 2y agoIt's entirely relevant here. The opinions of a staff engineer on this stuff should be interpreted very differently from the opinions of a developer with much less experience.
- phist_mcgee 2y agoReminds me of TechLead https://www.youtube.com/watch?v=AbUU-D2Hil0 https://www.youtube.com/watch?v=AbUU-D2Hil0
- devmor 2y agoIt's not relevant here, because this is a post from someone who worked on copilot. It's a shady sales pitch, disguised as an engineer's honest opinion.
- theoryofx 2y agoNot really because "Staff software engineer" has become the new "Senior Software Engineer" due to title inflation. It's become an essentially meaningless distinction at many companies. Case in point, this person has around around 7 years of professional experience at just two companies, Zendesk and GitHub. I don't mean this as a personal dig in any way (truly) but this simply isn't what we used to mean by a "Staff" level software engineer. This person is early-mid career, which we used to just call "Software engineer" then "Senior Software Engineer" and now (often enough) "Staff Software Engineer"
- brianstrimp 2y agoThey are at a place in their career where it still feels relevant to mention that title.
- theshrike79 2y agoExactly. I've been in the business for 20+ years and I think my title is still "Senior Software Engineer". Not because of lack of skill, but I don't care. I could ask for a fancier one and most likely get it, but why?
- jppope 2y agoMy experience is similar: great for boilerplate, great for autocomplete, starts to fall apart on complex tasks, doesn't do much as far as business logic (how would it know?)- All in all very useful, but not replacing a decent practitioner any time soon. LLMs can absolutely bust out some corporate docs super crazy fast too... probably a reasonable thing to re-evaluate the value though
- nicksergeant 2y agoI've had kind of great experiences even doing complex tasks with lots of steps, as long as I tell it to take things slowly and verify each step. I had a working and complete version of Apple MapKit JS rendering a map for an address (along with the server side token generation), and last night I told it I wanted to switch to Google Maps for "reasons". It nailed it on the first try, and even gave me quick steps for creating the API keys in Google Dev Console (which is always _super_ fun to navigate). As Simon has said elsewhere in these comments, it's all about the context you give it (a working example in a slightly different paradigm really couldn't be any better).
- jppope 2y agototally agree, what you are saying is aligned. The LLM needs you in the drivers seat, it can't do it with out you
- theshrike79 2y agoExactly. For unit/integration tests I've found it to be a pretty good assistant. I have a project with a bunch of tests already, then I pick a test file and write `public Task Test` and wait a few seconds, in most cases it writes down a pretty sane basis for a test - and in a few cases it figured out an edge case I missed.
- callamdelaney 2y agoMy experience of copilot is that it’s completely useless and almost completely incapable of anything. 4o is reasonable though.
- ddgflorida 2y agoYou summed it up well and your experience matches mine.
- nvarsj 2y agoI'm trying to understand the point of the affix "as a staff engineer", but I cannot.
- deleted 2y ago[deleted]
- piuantiderp 2y agoAnytime you read "as an X", spidey senses should tingle and be careful. Caveat lector
- sangnoir 2y agoBoosting their personal brand, perhaps?
- nvarsj 2y agoYes perhaps. I guess we all need to hustle for that F U money :).
- pgm8705 2y agoI used to feel they just served as a great auto complete or stack overflow replacement until I switched from VSCode to Cursor. Cursor's agent mode with Sonnet is pretty remarkable in what it can generate just from prompts. It is such a better experience than any of the AI tools VSCode provides, imo. I think tools like this when paired with an experienced developer to guide it and oversee the output can result in major productivity boosts. I agree with the sentiment that it falls apart with complex tasks or understanding unique business logic, but do think it can take you far beyond boilerplate.
- Prickle 2y agoThe main issue I am having here, is that I can see a measurable drop in my ability to write code because of LLM usage. I need to avoid LLM use to ensure my coding ability stays up to par.
- Aeolun 2y agoThere’s no measurable drop in my ability to write code, but there’s a very significant one in my desire to.
- t8sr 2y agoI guess I'm officially listed as a "staff engineer". I have been at this for 20 years, and I work with multiple teams in pretty different areas, like the kernel, some media/audio logic, security, database stuff... I end up alternating a lot between using Rust, Java, C++, C, Python and Go. Coding assistant LLMs have changed how I work in a couple of ways: 1) They make it a lot easier to context switch between e.g. writing kernel code one day and a Pandas notebook the next, because you're no longer handicapped by slightly forgetting the idiosyncrasies of every single language. It's like having smart code search and documentation search built into the autocomplete. 2) They can do simple transformations of existing code really well, like generating a match expression from an enum. They can extrapolate the rest from 2-3 examples of something repetitive, like converting from Rust types into corresponding Arrow types. I don't find the other use cases the author brings up realistic. The AI is terrible at code review and I have never seen it spot a logic error I missed. Asking the AI to explain how e.g. Unity works might feel nice, but the answers are at least 40% total bullshit and I think it's easier to just read the documentation. I still get a lot of use out of Copilot. The speed boost and removal of friction lets me work on more stacks and, consequently, lead a much bigger span of related projects. Instead of explaining how to do something to a junior engineer, I can often just do it myself. I don't understand how fresh grads can get use out of these things, though. Tools like Copilot need a lot of hand-holding. You can get them to follow simple instructions over a moderate amount of existing code, which works most of the time, or ask them to do something you don't exactly know how to do without looking it up, and then it's a crapshoot. The main reason I get a lot of mileage out of Copilot is exactly because I have been doing this job for two decades and understand what's happening. People who are starting in the industry today, IMO, should be very judicious with how they use these tools, lest they end up with only a superficial knowledge of computing. Every project is a chance to learn, and by going all trial-and-error with a chatbot you're robbing yourself of that. (Not to mention the resulting code is almost certainly half-broken.)
- chasd00 2y agoThis is pretty much how i use llm for coding. I already know what i want i just don't want to type it out. I ask the llm to do the typing for me and then i check it over, copy/paste it in, and make any adjustments or extensions.
- toprerules 2y agoAs a fellow "staff engineer" LLMs are terrible at writing or teaching how to write idiomatic code, and they are actually causing me to spend more time reviewing than I was previously due to the influx of junior to senior engineers trying to sneak in LLM garbage. In my opinion, using LLMs to write code comes as a faustian deal where you learn terrible practices and rely on code quantity, boilerplate, and indeterministic outputs - all hallmarks of poor software craftsmanship. Until ML can actually go end to end on requirements to product and they fire all of us, you can't cut corners on building intuition as a human by forgoing reading and writing code yourself. I do think that there is a place for LLMs in generating ideas or exploring an untrusted knowledge base of information, but using code generated from an LLM is pure madness unless what you are building is truly going to be thrown away and rewritten from scratch, as is relying on it as a linting, debugging, or source of truth tool.
- doug_durham 2y agoI've had exactly the opposite experience with generating idiomatic code. I find that the models have a lot of information on the standard idioms of a particular language. If I'm having to write in a language I'm new in, I find it very useful to have the LLM do an idiomatic rewrite. I learn a lot and it helps me to get up to speed more quickly.
- deleted 2y ago[deleted]
- qqtt 2y agoI wonder if there is a big disconnect partially due to the fact that people are talking about different models. The top tier coding models (sonnet, o1, deepseek) are all pretty good, but it requires paid subscriptions to make use of them or 400GB of local memory to run deepseek. All the other distilled models and qwen coder and similar are a large step below the above models in terms of most benchmarks. If someone is running a small 20GB model locally, they will not have the same experience as those who run the top of the line models.
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- why-el 2y agoI was hoping the LLM is the staff engineer? can read both ways.
- mvdtnz 2y ago> What about hallucinations? Honestly, since GPT-3.5, I haven’t noticed ChatGPT or Claude doing a lot of hallucinating. See this is what I don't get about the AI Evangelists. Every time I use the technology I am astounded at the amount of incorrect information and straight up fantasy it invents. When someone tells me that they just don't see it, I have to wonder what is motivating them to lie. There is simply no way you're using the same technology as me with such wildly different results.
- mrguyorama 2y ago> I have to wonder what is motivating them to lie. Most of these people who aren't salesmen aren't lying. They just cannot tell when the LLM is making up code. Which is very very sad. That or they could literally be replaced by a script that copy/pastes from stack-overflow. My friend did that a lot and it definitely helped features ship but doesn't make maintainable code.
- simonw 2y ago> There is simply no way you're using the same technology as me with such wildly different results. Prompting styles are incredibly different between different people. It's very possible that they are using the same technology that you are with wildly different results. I think learning to use LLMs to their maximum effectiveness takes months (maybe even years) of effort. How much time have you spent with them so far?
- the_mitsuhiko 2y ago> When someone tells me that they just don't see it, I have to wonder what is motivating them to lie. There is simply no way you're using the same technology as me with such wildly different results. I don’t know what technology you are using but I know that I am getting very different results based on my own prompt qualities. I also do not really consider hallucinations to be much of an issue for programming. It comes up so rarely and it’s caught by the type checker almost immediately. If there are hallucinations it’s often very minor things like imagining a flag that doesn’t exist.
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- dlvhdr 2y agoAnother article that doesn’t introduce anything new
- softwaredoug 2y agoI think people mistakenly use LLMs as research tools, thinking in terms of search, when they're better as collaborators / co-creators of scaffolding you know you need to edit.
- ur-whale 2y agoThis article completely correlates with my so far very positive experience of using LLM's to assist me in writing code.
- simonw 2y agoOn last resort bug fixes: > I don’t do this a lot, but sometimes when I’m really stuck on a bug, I’ll attach the entire file or files to Copilot chat, paste the error message, and just ask “can you help?” The "reasoning" models are MUCH better than this. I've had genuinely fantastic results with this kind of thing against o1 and Gemini Thinking and the new o3-mini - I paste in the whole codebase (usually via my https://github.com/simonw/files-to-prompt https://github.com/simonw/files-to-prompt tool) and describe the bug or just paste in the error message and the model frequently finds the source, sometimes following the path through several modules to get there. Here's a slightly order example: https://gist.github.com/simonw/03776d9f80534aa8e5348580dc6a800b https://gist.github.com/simonw/03776d9f80534aa8e5348580dc6a8... - finding a bug in some Django middleware
- powersnail 2y agoThe "attach the entire file" part is very critical. I've had the experience of seeing some junior dev posting error messages into ChatGPT, applying the suggestions of ChatGPT, and posting the next error message into ChatGPT again. They ended up applying fixes for 3 different kinds of bugs that didn't exist in the code base. --- Another cause, I think, is that they didn't try to understand any of those (not the solutions, and not the problems that those solutions are supposed to fix). If they did, they would have figured out that the solutions were mismatches to what they were witnessing. There's a big difference between using LLM as a tool, and treating it like an oracle.
- theshrike79 2y agoThis is why in-IDE LLMs like Copilot are really good. I just had a case where I was adding stuff to two projects, both open at the same time. I added new fields to the backend project, then I swapped to the front-end side and the LLM autocomplete gave me 100% exactly what I wanted to add there. And similar super-accurate autocompletes happen every day for me. I really don't understand people who complain about "AI slop", what kind of projects are they writing?
- elliotto 2y agoI have picked up the cursor tool which allows me to throw in relevant files with a drop down menu. Previously I was copy pasting files into the chatgpt browser page, but now I point cursor to o1 and do it within the ide. One of my favourite things is to ask it if it thinks there are any bugs - this helps a lot with validating any logic that I might be exploring. I recently ported some code to a different environment with slightly different interfaces and it wasn't working - I asked o1 to carefully go over each implementation in detail why it might be producing a different output. It thought for 2 whole minutes and gave me a report of possible causes - the third of which was entirely correct and had to do with how my environment was coercing pandas data types. There have been 10 or so wow moments over the past few years where I've been shocked by the capabilities of genai and that one made the list.
- n144q 2y agoAgree with many of the points here, especially the part with one-off, non-production code. I had great experience letting ChatGPT writing utility code. Once it provided Go code for an ad-hoc task which runs exactly as expected on first try, when it could cost me at least 30 minutes that's mostly spent on looking up APIs that I am not familiar with. Another time it created an HTTP server that worked with only minor tweaks. I don't want to think about life before LLMs existed. One thing that is not mentioned -- code review. It is not great at it, often pointing out trivial or non issues. But if it finds 1 area for improvement out of 10 bullet points, that's still worth it -- most human code reviewers don't notice all the issues in the code anyway.
- elwillbo 2y agoI'm in your boat with having to write a significant amount of English documents. I always write them myself, and have ChatGPT analyze them as well. I just had a thought - I wonder if I could paste in technical documentation, and code, to validate my documentation? Will have to try that later. CoPilot is used for simple boilerplate code, and also for the autocomplete. It's often a starting point for unit tests (but a thorough review is needed - you can't just accept it, I've seen it misinterpret code). I started experimenting with RA.Aid (https://github.com/ai-christianson/RA.Aid https://github.com/ai-christianson/RA.Aid) after seeing a post on it here today. The multi-step actions are very promising. I'm about to try files-to-prompt (https://github.com/simonw/files-to-prompt https://github.com/simonw/files-to-prompt) mentioned elsewhere in the thread. For now, LLMs are a level-up in tooling but not a replacement for developers (at least yet)
- devmor 2y agoHow I use LLMs as a senior engineer: 1. Try to write some code 2. Wonder why my IDE is providing irrelevant, confusing and obnoxious suggestions 3. Realize the AI completion plugin somehow turned itself back on 4. Turn it off 5. Do my job better than everyone that didn't do step 4
- ggregoire 2y agoDon't people actually enjoy writing code and solving problems on their own? I would be so bored if my job consisted of writing prompts all day long.
- simonw 2y agoI use LLMs to support my programming all day, and I'm not "writing prompts all day long". I'm working just like I used to, only faster. LLMs make it quicker for me to: - Decipher obscure error messages - Knock out a quick exploratory prototype of a new idea, both backend and frontend code - Write boiler plate code against commonly used libraries - Debug things: feeding a gnarly bug plus my codebase into Gemini (for long context) or o3-mini can save me a TON of frustration - Research potential options for libraries that might help with a problem - Refactor - they're so good at refactoring now - Write tests. Sometimes I'll have the LLM sketch out a bunch of tests that cover branches I may have not bothered to cover otherwise. I enjoy working like this a whole lot more than I enjoyed working without them, and I enjoyed programming a lot prior to LLMs.
- Aeolun 2y agoI enjoy building things. Writing code, well, I could take or leave that.
- n144q 2y agoUsing LLMs to write code for you is solving problems. The argument is almost like saying "using a third party library is not solving a problem on your own". If it gets the job done, it works. I enjoy writing code, but I enjoy seeing getting a feature out even more. In fact, I don't quite enjoy the part of writing basic logic or tweaking CSS which an intern can easily do. I don't think anybody is writing prompts all day long. If you don't actually know how to write code, maybe. But at this point, a professional software engineer still works with a code base with a hands-on approach most of the time, and even heavy LLM users still spend a lot of time hand writing code.
- fosterfriends 2y ago"Proofreading for typos and logic mistakes: I write a fair amount of English documents: ADRs, technical summaries, internal posts, and so on. I never allow the LLM to write these for me. Part of that is that I think I can write more clearly than current LLMs. Part of it is my general distaste for the ChatGPT house style. What I do occasionally do is feed a draft into the LLM and ask for feedback. LLMs are great at catching typos, and will sometimes raise an interesting point that becomes an edit to my draft." -- I work on Graphite Reviewer (https://graphite.dev/features/reviewer https://graphite.dev/features/reviewer). I'm also partly dyslexic. I lean massively on Grammarly (using it to write this comment) and type-safe compiled languages. When I engineered at Airbnb, I caused multiple site outages due to typos in my ruby code that I didn't see and wasn't able to execute before prod. The ability for LLMs to proofread code is a godsend. We've tuned Graphite Reviewer to shut up about subjective stylistic comments and focus on real bugs, mistakes, and typos. Fascinatingly, it catches a minor mistake in ~1/5 PRs in prod at real companies (we've run it on a few million PRs now). Those issues it catches result in a pre-merge code change 75% of the time, about equal to what a human comment does. AIs aren't perfect, but Im thrilled that they work as fancy code spell-checkers :)
- hinkley 2y agoSome of the stuff in these explanations sounds like missing tools. There's a similar thread for a different article going around today, and I kept thinking at various points, "Maybe instead of having an LLM write you unit tests, you should check out Property Based Testing?" The question I keep asking myself is, "Should we be making tools that auto-write code for us, or should we be using this training data to suss out the missing tools we have where everyone writes the same code 10 times in their careers?"
- emseetech 2y agoI used Copilot for a while (since the beta whenever that was) but recently I stopped and I'm glad I did. I use Claude and DeepSeek for searching documentation and rubber ducking/pair programming style conversations when I'm stuck, but that's about it. I stick to a "no copy & paste" rule and that includes autocomplete. Interactions are a conversation but I write all my code myself.
- asdev 2y agoif you write your code with good dependency injection/abstraction, you can one shot unit tests a lot of the time
- bsder 2y agoThe big problem with LLMs as a "staff engineer" is that LLMs are precisely suited to the kind of tasks that I would normally assign to a junior engineer or cooperative engineering student. That's bad because it makes "not training your juniors" the default path for senior people. I can assign the task to one of my junior engineers and they will take several days of back and forth with me to work out the details--that's annoying but it's how you train the next generation. Or I can ask the LLM and it will spit back something from its innards that got indexed from Github or StackOverflow. And for a "junior engineer" task it will probably be correct with the occasional hallucination--just like my junior engineers. And all I have to do for the LLM is click a couple of keys.
- VenturingVole 2y agoMy first thought upon reading this was the observation about the fact software engineers are deeply split: How can they be so negative? A mixture of emotions. Then I reflected, how very true it was. In fact, as of writing this there are 138 comments and I started simply scrolling through what was shown to assess the negative/neutral/positive bias based upon a highly subjective personal assessment: 2/3 were negative and so I decided to stop. As a profession, it seems many of us have become accustomed to dealing in absolutes when reality is subjective. Judging LLMs prematurely with a level of perfectionism not even cast upon fellow humans.. or at least, if cast upon humans I'd be glad not to be their colleagues. Honestly right now - I would use this as a litmus test in hiring and the majority would fail based upon their closed-mindedness and ability to understand how to effectively utilise tools at their disposal. It won't exist as a signal for much longer, sadly!
- notTooFarGone 2y agoIt boils down to responsibility. We need to trust machines more than humans because machines can't get responsibility. That code that you pushed and broke prd - you can't point at the machine. It is also predictability/growth in a sense. I can assess certain people and know what they will probably get wrong and develop the person and adjust it. If that person uses LLMs it disguises that exposure of skill and leads to a very hard signal to read as a senior dev, hampering their growth.
- VenturingVole 2y agoI absolutely agree with your points - assuming that "machines" to mean the code as opposed to the LLMs: As a "Staff+" IC type and mentoring and training a couple of apprentice-level developers I've already asked on several occasions "why did you do this?" and had a response of "oh, that's what the AI did." I'm very patient, but have made clear that's something to never utter - at least not until one has the experience to deeply understand boundaries/constraints effectively. I did see a paper recently on the impact of AI/LLMs and danger to critical thinking skills - it's a very real issue and I'm having to actively counter this seemingly natural tendency many have. With respect to signals, mine was around the attitude in general. I'd much rather work with someone who goes "Yes, but.." than one who is outright dismissive. Increasing awareness of the importance of context will be a topic for a long time to come!
- SquibblesRedux 2y agoI have found LLMs to be "good enough" for: - imprecise semantic search - simple auto-completion (1-5 tokens) - copying patterns with substitutions - inserting commonly-used templates
- floppiplopp 2y agoYes, LLMs are great at generating corporate bullshit to appease the clueless middle management. I wouldn't trust its code generation for production systems though, but I can see how inexperienced devs might do just that.
- nbaugh1 2y agoOne thing I don't see mentioned often but is definitely true for me - I use Google like 90% less frequently now. I spend zero time crawling through various blogs or stack overflow questions to do things like understand an error I haven't seen before. Google is basically now a means of directing me to official docsites if I don't already know the URL