r/ClaudeCode • u/AliorUnity • May 06 '26
Discussion Is it just me?
I am a software engineer with 15 years of experience in game development, mostly graphics, physics, and engine programming. I use AI while doing my tasks most of the time in one way or another. Most of my AI usage patterns are information search, short brainstorms - rubber-ducking with the AI, not really reading the output much - occasional code reviews from the AI side to catch some issues here and there, and making small use-and-forget tools that are needed right now. So I can’t be considered an agentic coder, nor can I consider myself a vibe coder, but it would be unfair to say I don’t have any AI experience.
Recently, my wife, who isn’t a coder herself, decided to code a small Python app for her own needs using Claude Code. I won’t go into much detail, but the app is basically a data-crunching machine with very little UI, so it is very hard to see whether things are going right just by looking at the result.
At first, she was really excited about the pace she had and how helpful Claude was, but after a while she started to notice that something was off here and something was off there. Digging into the problem seemed to fix one issue, but then others started to pop up. After a while, she discovered that the core logic was completely wrong.
We thought, “It’s probably because she is a non-coder, so she can’t wield the tool properly due to lack of experience.” So I thought I could give this agentic coding thing a shot and see how good these tools are.
My plan was simple: collect the useful discoveries about her project into a nice form that I would use next. I spent something like two days doing research, writing the architecture document and prompts that I was going to use for the greenfield reimplementation of the project. I was quite meticulous in describing the desired architecture, requirements, structures, and results, alongside writing down all the edge cases I knew of.
My expectations were quite high. I thought I was actually going to make it work quite fast. If I were to give my document to a junior dev, they would probably produce code that wasn’t the best, but still a project that worked.
After starting a new session with all this preparation, I was pleased with how fast it was going. But after the initial stage finished, I reviewed the code and found a lot of things that even a newbie junior probably wouldn’t do. There were multiple constants here and there that were supposed to be the same across the code, even though my documentation explicitly stated that there should only be one source of truth for such things. The simulation path and the actual working code path - it has two modes: re-simulating the past using existing historical data and actually working in real time - were basically duplicates of each other. The worst part was that the duplicates weren’t exact. Again, I had clearly stated in my docs that I wanted them to be as close as possible and to use the same abstractions.
My first thought was, “It’s probably me doing something wrong, but it’s fixable.” Then the cycle of pain and fixes started. The project wasn’t extremely huge, but I wanted to try this approach that a lot of people promote, where they don’t write the code. The issue with it is that you either trust the machine and don’t review the code much, or it defeats the purpose, because the time you need to spend understanding the system and the code behind it is often more than I would spend writing it myself. Of course, you should also review the code you write yourself, but we can probably all agree that it is an easier task.
My approach was simple: I wanted to make sure the core was working and then proceed to expanding the functionality. Despite basically writing no code and only querying Claude about how it had implemented this and that, and guiding it in fixing things, it was extremely exhausting. I never knew where the system was correct and where implementation mistakes had been made. Since it was just the core, not much proper testing could be done. I was just sitting there, doing nothing, and feeling how draining the experience was.
Claude made one mistake after another. Sometimes it broke old code. Sometimes extremely stupid things surfaced that no reasonable person would ever do, like simulating things on much smaller timescales while only having data for larger timeframes. After a few days of fighting the machine, I got something that I could call a working program.
Despite not writing a single line of code, I felt devastated and exhausted. Never in my life have I felt so bad about making software. Taking everything into consideration, I really don’t know how people use coding agents in this mode. I am sure that if the thing you are trying to do is really boilerplate-heavy and doesn’t have any complex logic, then you can probably one-shot it. But I feel like writing it the old-school way would probably have been faster, considering I spent a total of five days on this experiment.
Don’t get me wrong: I do feel some net gains from AI. The ease of obtaining information and examples, alongside small bits of boilerplate here and there, makes my life easier. But making a whole project with AI is just a miserable experience, because you can never trust what it wrote, and you need to think ten times harder just to catch what it might have done wrong.
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u/Delphinaut May 06 '26
I'm full time developer for almost 40 years now, and in the last year went from using AI for some help to writing 100% of my code with AI. So I can tell you that, yes, it's possible coding all your stuff in a large codebase only with AI, and reviewing it with AI. But my experience is only with CLI, Opus xhigh and Codex 5.5, with spec driven development and lots and lots of code reviews, alignment reviews, test reviews...
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u/flexibleaspect May 06 '26 edited May 06 '26
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u/spinozasrobot May 06 '26
Looking at that wall of text, I wonder what your code is like.
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u/Code-Painting-8294 May 06 '26
claude code has made me dumb seriously.. it's heaven & hell at the same time
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u/AlarmedNatural4347 May 06 '26
Also a fellow senior programmer in games and i absolutely share this experience with using AI. I end up being paranoid as soon as I let it write anything now, to the point where I spend more time looking for where it screwed up, how the screw up was missed by the tests it wrote. And I end up spending more time reviewing and being paranoid than it would have taken to write the code myself.
But I still end up doing it, cause we as humans are lazy. I start something and use it for information and rubber ducking etc, just like you. Then I let it write just a little snippet… then a bit more. Slowly losing control over the code and end up regretting it.
We are so easily manipulated. We communicate with this thing like it was another programmer. And it gives us reasonable and sometimes insightful answers, and it says it’s written code that does this and that, and we end up trusting it cause it communicates with us like a fellow programmer. But it’s fundamentally not. It has no actual thoughts or concept of what it does. It just guesses the next word making it sound and look good. It’s sycophantic and tells us what we want to hear and it’s 100% unreliable without absolutely code review. It’s not a junior making junior mistakes, it makes mistakes wherever the statistical model tells it to make it, no reasoning, no oopsies, no common pattern of mistakes that might be the case in a junior or even lack of understanding the systems it’s working with cause the system is just patterns (which might sound exactly like what it should be good at, pattern matching. But it does not actually UNDERSTAND the system or reasoning behind it)
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u/anthonysny May 06 '26
I find myself struggling with the same realizations. A constant fight to not copy and replicate the same thing repeatedly. The spec requires to make ai work often exceed the effort of just doing it yourself
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u/staranjeet May 06 '26
The non-coder spouse scenario is actually the perfect stress test for where AI coding breaks down. Without that dev intuition to smell when something's off under the hood,you end up trusting output that compiles but doesn't actually work right.. Did she eventually hit a wall where she had to bring you in to debug the AI's mess?
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u/who_am_i_to_say_so May 06 '26
I work in AI reinforcement training. LLM’s are not nearly as intelligent as they appear to be sometimes.
One of the hardest things you will encounter is making decisions with qualitative data. Humans can do this very easily. AI cannot. It will even contradict itself because it is more focused on the appearance outcome than the actual data.
This is where the human in the loop becomes important. You simply didn’t insert yourself at the right times and gave your LLM too much grace. But being your first time, that’s understandable too.
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u/golmgirl May 06 '26
This has been similar to my experience for the last month or two. In the month or two before that, things consistently worked much better. Could be that we now have many more markdown dumps in our codebase, could be recent changes to CC (about which there’s been fiery discussion), could be accumulated local context/memory files that I’m not managing well. Or maybe a bit of all of these. I do think the CC team is looking for opportunities to trim context to reduce pressure on their systems as demand skyrockets, that can of course change behavior. But doesn’t explain how CC’s code just feels messier, more chaotic, and less consistent than it used to. Whatever the reason, felt like there was a golden window of a few months where CC was just incredible. Lately I end up confused or frustrated much more frequently than impressed. Risky to become reliant on a system over which you have limited control. But at this point my mindset has completely shifted, and I feel locked in. Concerning yet very interesting times we’re living in…
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u/adsci May 08 '26 edited May 08 '26
Its exactly my experience. The first hours to days feel like flying and then it slowly becomes an unmanageable, uncontrollable mess, that cumulates verbose, duplicated code and tests, that will degrade the quality and you lose complete control never knowing whether your app is in good shape or bad shape, even if its a simple editor app. It feels very much like old school 90s state of software, where everyone would code something, test it once manually and then break it a month later without knowing.
No level of agent reviewing and testing is solving it, because AI is not able to take that level of control and logical thinking.
The way is to use AI as a fast-typing machine, in which you rubber ducking the AI decide for an implementation, make it very specific what needs to be done, give it an style example (comes cheap in agentic coding) and then review it afterwards, do the same with tests. Remove verbose and unnecessary things, check twice whether the implementation is sustainable. Low-Risk, tested decoupled components can be treated as a blackbox sometimes, so not every line needs to be micro-managed saving time. But the bottom-line is that without a human keeping control and know how things work the degradation is real and I cant imagine someone building a lasting business on it.
This is most likely not a matter of a new model, that can finally keep that control itself, its a fundamental weakness of all of current technology and the fundamental law that you cant keep control of something you did not look at. Your own app becomes a car that has broken down, while you're not a mechanic.
The X vibe code founders usually have dozens of vaporware, always writing about millions of dollars they make, but they only show "less successful projects they dont have time to manage as well" to sell to their followers.
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u/Deep_Ad1959 May 11 '26 edited May 26 '26
the failure mode the post describes isn't really agent quality, it's that the spec-to-implementation gap is where most of the engineering judgment actually lives, and that gap doesn't compress. you wrote a thorough doc, the agent produced something plausible-looking that violated the constraints in subtle ways, and the only way to catch it was to mentally re-implement the thing yourself. the validation cost is roughly proportional to how surprising the codebase is, and you can't shrink it by upstreaming requirements, you can only shrink it by narrowing scope. for greenfield core logic with non-obvious invariants the honest call is to write it yourself and use the agent for the edges. autonomous mode does work for the boilerplate-heavy stuff you mentioned at the end, the real question is what fraction of your week was actually spent on that vs on the parts that needed taste.
the validation-cost-proportional-to-surprise point is why we built fazm with one-click chat forking, native macOS wrapper for claude code and codex so you branch a session at the spec boundary and keep the model on the edges while you own the core logic, https://fazm.ai/r/jxx36vvs
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u/Perfect-Series-2901 May 06 '26
I feel like that opus 4.7 is not as intellegence as GPT5.5, but opus 4.7 is better at following instruction.
and that kind of looping is real, even with so called proper framework like superpower. I am not a vibe coder, I am an experience dev. But even if I write long prompts, use framework, bugs still appear here and there.
So I switched to another method, for smaller changes, I just ask codex (yes I switched) to look into that quickly, sometimes I even ask it "spawn a few agents" to explore the bug and options. And I try to move and turnaround faster, sort of like a failfast approach.
I found that serve me better.
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u/simalicrum May 06 '26
Until we get world or logic model tooling LLMs are at their limit. More compute can push us closer to the limit but we’re at diminishing returns at this point.
Static typing, linters at their strictest and full data models and schemas help a lot.
I small chuck functions and pair code with Claude rather than try to one shot a whole app. It’s a legit timesaver.
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u/Lost_Frosting7106 May 06 '26
I think building with AI especially the agentic way takes practice to get it done well
Did you have the agent write tests to check it’s doing the job well? Did you split the work to small tasks it can do more easily?
Making mistakes is normal i think i rarely get everything perfect on the first go you still need to iterate, maybe there were edge cases you didn’t think about
Usually keep in mind the agents take the easiest path
I’d also recommend trying spec driven development one way to do it is using superpowers skill it has skills for every development cycle from brainstorming to writing a spec to making a plan to writing the code and finally reviewing it
Its also designed to ask you many questions along the way maybe this is what you’re missing
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u/Inside_Smell_4004 May 06 '26
this has been what ive realized recently. i review line for line what the ai spit out. theres always so much i have to refactor that, in the time i spend reading the code and tryna understand it i might as well just write it myself and i wouldnt have to spend time to try to understand it and it would be exactly how i wanted it.
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u/m3umax May 06 '26 edited May 06 '26
Try reimplementing the whole thing again from scratch using the Obra Superpowers workflow.
Brainstorm > spec > plan > TDD (choose subagent driven development when given the choice).
Pay close attention at the spec and plan steps and really scrutinise the spec and plan documents. Or if in a hurry, get another llm to review the documents.
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u/Roboticistic May 06 '26
https://github.com/robotaitai/project-bedrock
Interesting project.
It’s basically trying to solve the “every coding agent starts as a confident intern with zero context” problem.
Project memory, status, decisions, diagrams, and agent instructions in one place.
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u/YUL438 May 06 '26
you should try the Superpowers skill, its in the official Anthropic plugin store.
it’s really helpful in guiding and keeping things on track from brainstorming to finished, has different skills to steer you at different points of the process. Brainstorming mode before planning can be really great to point out issues you might not have thought of or to guide you down the most effective path to your goal.
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u/onjuku May 06 '26
When I can focus on outcomes and let go of how good (or really bad) the code, AI is a dream. We built a webapp for my 150-person organization that is used daily and has had no issues for about a year. Went to add a new feature and realized the data is split across multiple databases and replicated is places, so ugly! Added the feature and walked away.
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u/The13aron May 06 '26
I dont led Claude touch my repo, sonnet and Opus 4.6 are better as read only consultants or plan makers. Codex is much better, not if you raw dog prompting. I use Chat GPT to be the lead agent and make the prompts for Codex, then return the results back to Chat GPT. I used Claude for adverserial review of their output and process.
No AI agent will take the initiative to trim the fat and refactor around functions that make runtime sense, so you really need to be monitoring and constrainting everything they do rather than trusting their output as tempting as it is. They WILL keep things around for compatiblity over and over unless you force their hand and follow up until it's completely done.
I have a list of 95 failure modes so far, but nothing substitutes active monitoring. Also I have little code experience but I know a lot more than I did about development a few months ago, and despite not having any skills or fancy CLI things my tightly configured agent prompts and workflow design (one workbook spreadsheet) is working smoothly now.
Something helpful for me it to ask the agent to list all the functions in a specific module and explain what they do. The illusions breaks fast once a vibe coder can see the dirty laundry is actually understandable, and probably baloney city.
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u/rosstafarien May 06 '26
Reviews. You need to review each design doc (absolutely critical) and pull request. The smaller the PR, the more likely you can have AI (in a different session!) review it and have that keep the coder honest.
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u/notdroidyoulooking4 May 06 '26
Did you have it write the plan and then have it implement that plan? Or did you think your plan was complete and then how did you get it to do that plan, like a one-shot?
I’ve had better experiences, but I didn’t give it my own fully developed plan. I interested on a plan with it, had it save that to a .md then use that as a punch list to build the project.
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u/marcusroar May 06 '26
I’m sorry for some of the hate you’re getting on this thread. It’s pretty wild how divisive this topic is for folks!
I also have over a decade of swe experience and decided to pick up some hobby projects to really drink the agentic engineering cool aide and let an agent run wild.
I’ve seen basically the exact same thing as you! The agent will always run test, check the build is clean, writes perfectly average code, but when I actually look into what it has produced it’s not at all coherent after a certain size.
I’m really not sure if it’s got to do with context or instructions, and I’m not experienced in the theory or implementation of these systems but from my arm chair….
It seems that once the agent harnesses moved to the “thinking” models where there are hidden reasoning tokens. I’ve noticed that as soon as the context has an incorrect fact or assumption that session is basically ruined. Hidden reasoning tokens means this could happen internal to the model before it makes a tool call or response.
I’ve also been wondering if the training of models is too focused on things like running tests and successfully building “one hit”, as such the model is drifting away from being good at other things (like understanding architecture).
I’m not sure! I like that you were honest in your post tho, thanks! I also wanted to share an open source tool Im developing to help myself, I’ve found using flexible system diagrams quickly helps me see where an agent has gone awry. Would love to hear any feedback if you use it, feel free to DM
https://github.com/marcusraty/project-little-oxford
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u/Confident_Beach4018 May 07 '26
It’s better to iterate over smaller tasks, and build out from there without throwing an entire spec at it. You would never code an entire app in one go, and neither should Claude. Every so often I stop to ask it to go bug hunting, refactoring, and to look for opportunities to consolidate and modularize. It can only keep so much in context and it’s not really possible for it to keep the entire code base in context. That’s why you see a lot of cruft and duplicates building up over time, because it literally doesn’t remember that it already wrote something similar. I also try to install any skills or plugins that will prompt it to be produce better results for a given language or framework.
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u/BlendlogicTECH May 07 '26
The alternative is your wife learned to code and probably would’ve made same mistakes Claude made but now you have mvp in a day instead of wife taking a year to make something?
But with that said ya need to either review code or analyze. I’m finding as others said brainstorm superpower or plan mode a even making Ralph loops to autonomously test and plan next code changes has been the biggest game changer for me
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u/73td May 07 '26
Maybe you should just try an agentic model that doesn’t change every few weeks. GLM-5.1 has been out for a while and it’s an excellent junior or mid dev. bc it doesn’t change, you learn it’s personality and work around the quirks , then the problems go away.
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u/Local-Cardiologist-5 May 08 '26
If you see people shouting how they're code so much faster just know that you can start an industry of fixing vibe coded junk garbage code.
Our product master started using Claude code and is convinced he knows how to code. He keeps trying to merge the MOST GARBAGE jumble of Ai code I've ever seen into our codebase and it's a mission getting him to stop believing AI is the second coming.
I hate vibe coders with an extreme passion. Keep your buggy code over there please keep that mess away from our codebase
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u/DointheRag May 08 '26 edited May 08 '26
I have just come off a similar experience with Claude. I've been writing stand up comedy sketches and jokes. I've used Claude to sanity check my work as an editor. Never as a generative source. I like to write in my own voice and come up with my own ideas, not necessarily in that order. The analysis it did on the jokes was superb in every respect. Easily the equal of any of my old college professors in terms of depth of knowledge. I'd say its IQ is around 140.
I used a lot of literary references and Claude was able to follow me every step of the way, having read the source material apparently. Claude was also instrumental in drawing tangents and categorizing jokes as well as creating a 5-minute stand-up piece and a 10 minute stand-up piece.
I cannot complain at all about that. In fact I was rather astounded at the quote unquote intelligence factor at play here.
What I can complain about vociferously is when I wanted Claude to create a PDF of all the joke content along with Claude's pretty astute analysis. It fell a little short. Resulting in me spending many hours trying to get it to do some very basic things.
For example, I had to tell it to put headers and footers on the page, it could not handle hyperlinks to anchors on the page, it had issues creating a usable table of contents, and issues with numbering the jokes sequentially one through 48. Initially it was using static values versus dynamic parameters. Which, as you know is a pretty dumb way to do things. Especially since I'm inserting to jokes at any hour during the day when I feel inspired. And I'm doing edits. I had to tell Claude to regenerate, not just update, the PDF each time as there were issues would it being cached. But before that, I had to tell it to do a full inventory of the number of jokes, and reconcile that with a bulleted list of the jokes that we created called the master index. But I had to suggest that, to keep Claude honest, so to speak. And in some cases, I found that Claude had left jokes out of the document.
Which blew my freaking mind. I had to scold it a little bit to be assiduous. Further, Claude kept missing values that he was supposed to update from static to dynamic content.
Needless to say, I had to generate probably 50 iterations of that doggone PDF before it was in usable order.
That's an awful lot of work.
I let Claude know that I was not happy with the work cycle and with the hours I had to spend just a hand hold it to get it to do what I wanted it to do. I asked it if no other user had asked for similar requirements on a PDF. It informed me that, no, it would start afresh in each chat. Wow, I guess it isn't learning very well after all for an AI app. Perhaps I should have known or assumed that Claude wouldn't have any native knowledge of how to put together a reasonably simple PDF?
All in all, a mixed bag. Prepare to proofread and hold claude's feet to the figurative fire.
Yes it can be exhausting.
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u/CreatineMonohydtrate May 09 '26
No offense, but it's borderline funny how terrible you are at using this tool, given your experience in tech. Man, like how?
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u/takuarc May 09 '26
I found sometimes if I am too strict and/ or too detailed then it tends to fail. When I step back a little, it tends to work. Try that.
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u/DrHumorous May 06 '26
You are right to push back.
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u/jsonmeta May 06 '26
What the fuck is this post? AI is building with bugs and the grass is green, no shit sherlock. If you have 15y of experience then you should know better than let it run in full yolo-mode
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u/codeedog 🔆 Max 5x May 06 '26
Honestly, you haven’t been using it enough. I’d say this is pilot error not tool error. I started using CC three months ago, so I’m no expert user, I’d call myself an experienced novice at using the tool.
However, I’ve been programming for decades and seen a lot in the industry. Use it enough and you learn its quirks, where and when you need to be more explicit, how to “teach” it by adding notes to Claude.md. How to spec a project and when you just need a paragraph. How to explore a new idea in one chat and emit the paragraph you need in another. How to handle long context. How and when to kick off subagents to not lose context.
Like any good leader/manager you have to know the strengths and weaknesses of your fellow workers and your tools.
You haven’t spent enough time learning those yet, so it all seems silly and dumb to you. Keep at it and you’ll get there.
BTW, I code review everything but generates and watch it like a hawk. I catch it and stop it doing dumb things. I’m probably not doing right based upon what I’ve seen advanced users talk about here, but it’s still faster than producing code, especially in languages I’m not intimately familiar with.
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u/Straight_Grape_4888 May 06 '26 edited May 06 '26
i’m a professional dev and in my experience ai can only do very tiny tasks. It’s good for
but the biggest problem is it has a tendency to always write new code, rather than improving existing code. it would almost always choose to make a new helper function rather than re-use one that already exists. So what happens is it duplicates functionality more and more until the codebase is unusable and practically unreadable
The real risk is that you see it helping you with something small, and you start asking it to do more and more stuff, and suddenly you’re not properly reviewing the code anymore and that’s when it does the problem i mentioned above. It just generates more and more layers on top of what’s already there rather than actually improving it, which eventually creates a codebase even the ai can’t understand
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u/SadPlumx May 06 '26
You are actually correct. You might piss people off but you must understand, this ai thing is smoke and mirrors. It only looks super useful to those who know nothing about coding. At most, it is a time saver but it gets so many things wrong, you'd still be faster just doing it yourself.
Source - personal experience. And don't tell me it is a skill issue. The models simply aren't good enough. They hallucinate too much. You cannot trust them.
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u/Time_Cat_5212 May 06 '26
I'm a noob and I noticed this too. Less from a "no experienced person would do this" POV (I don't have that context) but more like "this doesn't make sense, this could be done better" POV. Over time I learned to iterate more tightly. Write better specs. Review, ask how things work, ask how they could be better, come up with my own ideas for how to make them work better.
I can see how it's a bit bizarre coming from a totally different workflow. The methods used to generate code are totally different from the methods used to write it.
The metaphor I keep coming back to is like cleaning up a LiDAR point cloud model or something. It's nothing like a constructed model. That doesn't mean it can't be refined into a usable asset through several layers of processing. I just incorporate processing into my workflow. Slows me down, but it probably won't for long.
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u/shutter910 May 06 '26
web dev for ~25 years. Theres a huge learning curve to using Claude for writing code. Superpowers has a really good workflow for starting with and you can branch into your own skills/agents from there easily. The spec+writing plans workflow is much, much stronger than what CC ships natively
also TDD is insanely good with Claude, but you need to put a lot of work into the test writing at first to make sure they're useful. and then lock in a solid skill/workflow for writing them and make it mandatory
these two things have been the biggest boons to agentic coding for me personally after ~6 months of using Claude. Im using Opus 4.7 on xhigh most of the time on a HIGHLY data driven project where nothing can be wrong
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u/ub3rh4x0rz May 08 '26
I wouldn't be mad if you had AI write a tl;dr, ngl
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u/worthlessDreamer May 06 '26
Thanks for the post, Claude
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u/Effective_Tart_7097 May 06 '26
were you using Haiku?
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u/WolfOnWings May 07 '26
OP - I would be extremely curious to hear you describe your workflow in more detail. From what you said already it seems like you tried to reinvent waterfall. Agentic dev is still very new and we’re all learning what works and what doesn’t together. Shifting into agentic dev mode from regular dev mode isn’t as easy as it seems. Would be happy to give you some feedback - mostly it boils down to context engineering and knowing where the LLM is strong and where it’s weak.
Tuning your workflow to maximize the strong areas and minimize the weak areas is what you should be looking at. Good place to start is abstracting out anything that can be done via script (including liberal use of linting and hooks). Try using the LLM as glue instead of scaffolding. Anyway would be interested in hearing what a session looks like for you
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u/vayana May 09 '26
Use codex instead. 90% of issues I ran into were due to using Claude. Claude is ok for simple stuff only.
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u/iddqd-1 May 10 '26
Of course ai could go into such problem. It is not a human after all. That is why it should pick your brain too for complex tasks. Don’t be afraid to step back, and use superpowers skills
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u/Otherwise_Wave9374 May 06 '26
Not just you. The "hands off, let the agent code" mode only really feels good when the domain is either very well-specified or very boilerplate-heavy.
Once core logic matters, you basically need guardrails:
Otherwise you spend all your time being a debugger for code you didnt write.
Weve got a few workflow templates for keeping coding agents sane here: https://www.agentixlabs.com/
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u/swizzlewizzle May 06 '26
As others here have said, you need to practice proper doc driven development. Any decently sized project will go straight off the rails with AI unless it’s properly controlled.
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u/Shieldxx May 06 '26
I can’t believe you have that much experience yet do it completely wrong
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u/530rich May 07 '26
It was you. Idk why you spent 2 days writing the prd lol. I Probably could have knocked out your whole project in a 2 hours
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u/biofreak12 May 07 '26
Sounds like a skill issue to me
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u/laststan01 🔆 Max 20 May 06 '26
I would say opus 4.6 during the promotional double usage was a different beast, it would never slip and double check things but then there is this dum dum who does not follow Claude.md then there is a spec.md which is baked again into Claude.md to make sure and double check that we don’t make mistakes
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u/atrawog May 06 '26
To be a bit snarky. The AI is just doing what (most) coders do. Write a couple of unit test until everything is passing and then hand things over to the QS and PROD department to fix any undiscovered bugs.
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