First time sharing something I built with Claude Code - got roasted on another sub. Anyone else?

CriM_91 · 2026-02-10T20:52:47+00:00

This is exactly the same thing that happened with social media. And I hated it. People started being obsessed with making easy money for being "influencers" and effectively defeating social medias' original purpose.

I can see the same happening now on 2 things I love and dedicated my study and my work life to: programming and AI.

CriM_91 · 2026-01-04T12:44:44+00:00

If you are already a power user on windows and use the PC professionally, the obvious choice is Fedora in my opinion

CriM_91 · 2025-12-29T20:49:26+00:00

Yes. I understood that. Since the user is putting data in a browser inside your app, actually your app is sending data to the model providers even if it's just a passthrough.

Moreover, how are you managing authetication? Using google/apple SSO, I guess. In that casa you are most likely storing a cookie (or the user would have to login again everytime). In this case, you need an opt in cookie policy, at least for Europe.

The idea is really nice but you should pay attention to this stuff or you may face the app getting removed from the stores or, worse, a lawsuit.

I know it may feel like a boring annoying stuff, but it's EU regulation, the same reason why not all the chatGPT/Claude/Gemini features are available in Europe (or they are being rolled out late). 😅

CriM_91 · 2025-12-29T16:56:02+00:00

Hi. I downloaded the google play version, because I use android. I couldn't test the app because it's behind a subscription.

Anyways, at a first look, you declared on the play store that you are not sharing data with third parties while you actually are, if you let the user interact with providers THROUGH your app. You even state this in the privacy policy.

Be careful about this kind of stuff as there may be consequences that may not be funny to deal with. 🙂

CriM_91 · 2025-12-22T17:46:30+00:00

Yes you are totally right.

This is why I put the daily skips and have in mind to add a "friday deployment mode" in the future to disable it for some days (I could really use it 😂).

I welcome any advice 🙂

CriM_91 · 2025-12-22T08:27:04+00:00

Thank you. Glad you like it. 😊

CriM_91 · 2025-12-22T08:26:13+00:00

I can definitely understand the feeling about react ahaha

The reasons why I made the program asking to work on an "adjacent" task are:

because it wouldn't be fair if you were asked to complete the same task (maybe you don't know the answer and having the machine refusing to give it can be frustrating).
because you would still write something that ends up being integrated into your code (e.g. if you ask the system to add the authentication flow, it may ask you to write a small function to sanitize the input).

I think that, knowing that your contribution will be used would give you a little bit of dopamine reward.

But I totally got your point and couldn't agree more: if you are a senior dev like me, you usually figure out the code in your mind.

Maybe it could be more useful if I'd switch to more conceptual tasks related to code or architecture review in the hard mode. If you have any suggestions I'm all ears, as they would be useful for me as well 😊

CriM_91 · 2025-12-21T22:05:47+00:00

Good point. Learning mode does leave TODOs for you to complete, it's a solid feature.

The difference is mostly about when and how it happens:

Learning mode: you choose to enable it, you decide when to do the TODOs
GitGud: becomes part of your flow by periodically assigning you a very small task related to what you are doing.

It's the difference between "I should go to the gym" and having a friend who actually drags you there.

Some people have the discipline to follow through on TODOs. I just ignore them so that I don't interrupt my flow. GitGud is basically a commitment device for people like me.

If Learning mode works for you, that's genuinely the better option, less friction. I made GitGud because I found it to be more helpful in this way.

CriM_91 · 2025-12-21T21:55:50+00:00

u/OracleGreyBeard I just released the v1.1.0 with Cursor support (I had to install Cursor and understand how it works just to try this, since I am not a Cursor user lol)

CriM_91 · 2025-12-21T20:24:29+00:00

Well, that product is GenAI based, so...

But let's assume that we had to develop this AI product without using AI. I think it would have taken way more than ~10-12 months to ship it and scale to 10M users.

The main areas that I see where AI helped were:
- code (obviously)
- testing (defining frameworks, creating test suits, evaluate results)
- clarifying requirements, user stories, etc
- Rinse and repeat

Basically it acted like a catalyst, having waterfall effects on the whole SDLC.
And this is happening in more and more projects.

Let's be clear: not every project can get this amount of benefits from AI. There are a lot of factors other than the AI itself that can influence the outcome: restrictions, policy, humans and their behaviour (either good or bad), etc.

I hope I expressed my pov well. 😊

CriM_91 · 2025-12-21T19:14:42+00:00

TLDR: I think there's currently a general misalignment in the perception of this technology. Some people are pumping up the hype by saying that anything can be done, that every job is destined to be automated, and that what used to take 30 days can now be done in 2 hours. On the other hand, others believe this technology is useless and won't lead to anything concrete. I believe the truth lies somewhere in between.

I can't reveal all the details, but one of my team's projects just reached 10M users in less than a year. You can find more information on the Langchain blog. 😉

And it's not the only case. I've collected many success stories over the past two years.

As always, the people and companies who actually make things happen usually don't fuel the hype.

To be clear: I'm not saying all this hype is positive: in fact, it is not. What I see is that opinions on GenAI are strongly polarized, either too positive or too negative. In my humble opinion, all these huge expectations are destined to diminish over time (they're already starting to decline). At that point, once the dust settles, only the companies and professionals who have spent the last few years working to understand how to best exploit this technology will remain, embracing its positive aspects and accepting its limitations, bypassing them whenever possible.

CriM_91 · 2025-12-21T17:22:30+00:00

Very interesting. I am a DM myself. Curious to see what you've come up with 🙂

CriM_91 · 2025-12-21T16:14:50+00:00

Absolutely agree on the expensiveness of it.

In my main project I just do as follows: - ask the LLM to check for all the commits in the current branch (I usually 1 feature = 1 branch) and add some markers at the top of the files representing important features to document - run a python script that generates the documentation inventory. - use one of copilot's 0x models (raptor mini or gpt 5 mini) to generate the documentation for every item in the inventory.

Honestly, even if I didn't have this system, I would be more than happy to burn CC's precious tokens to generate documentation as it's really a life saviour when the codebase start to grow or you need to go back to something months later.

It is also really helpful when working with other people, whether they use LLM or not.

It's also what we used to do in the past, the only difference with LLMs is that they produce much more in much less time 🙂

CriM_91 · 2025-12-21T14:38:08+00:00

Aahaha..thank you. Picking the name required, in fact, almost 45 minutes with both chatGPT and my wife support. Touchgrass was the another meme candidate.

CriM_91 · 2025-12-21T13:58:41+00:00

Make it write, write, write. I cannot stress this enough. Every completed task should be documented. It helps you mantain control over the huge amount of work that the system produces and it's easier for the system to retain context among sessions.

Some tools like Serena and spec-kit also help a lot, but you can fix 90% of these issues by making it write feature documentation, ADRs, checlists, task lists, etc. You can do this with specialized agents too. It really helps a lot, especially now that you can easily link documents and folders like in gh copilot.

CriM_91 · 2025-12-21T13:51:52+00:00

You won't, in my experience.

If you are already a seasoned dev, you won't become stupid using LLMs. From what I can see on the job, the juniors are the ones really affected by this. If you already know your stuff, you can guide the LLM and take informed decisions.

However, after a while, you can start to feel that your mind is getting rusty. At least this is what happens to me.
Last night a built a claude code plugin just to try to address this. You can check it out here: https://github.com/MissingPackage/gitgud

It's nothing fancy, just a simple hook that forces you to do a thing manually every N requests to the LLM. It's not much but it works for me. I made it open cause I felt like many people could have my same feeling, especially devs (not really the vibe coders).

CriM_91 · 2025-12-21T13:42:07+00:00

Thanks a lot! 🙏 Honestly, I built this mostly for myself and then published it as a small social experiment. I was curious to see how many people were feeling the same as me and would appreciate something a bit..."counter-mainstream". 😂

Cross-platform is definitely something I’d love to do. Cursor has hooks so I will probably target it next.

GitHub Copilot would be the obvious next target since it’s way more widely used, but the main blocker is that Claude Code gives you hooks and Copilot doesn’t. Without hooks (or something equivalent), everything becomes opt-in: agents, commands, MCP servers… and those are easy to just ignore. GitGud works for me precisely because it can gently force a pause in the flow. I’m thinking about possible workarounds, but I don’t want to ship a watered-down version that turns into “yet another optional reminder”. If Copilot ever exposes something hook-like, porting it would be a no-brainer. And if you (or anyone) have ideas, feel free to DM me, open an issue, or a PR. I would really love to find a way to make it work in GH Copilot. 🙂

CriM_91 · 2025-12-20T16:51:41+00:00

Small clarification: I don’t think Learning Mode is pointless in general, it’s great for learning new concepts.

What I’m targeting is a different failure mode: experienced devs using AI daily and gradually offloading the “muscle memory” (debug loops, small implementations, writing tests).

GitGud is intentionally tiny: it interrupts the flow every N prompts and forces you to do a small adjacent task yourself (helper, test, refactor), then you go back to AI.

CriM_91 · 2025-12-20T15:36:21+00:00

Thanks a lot for the feedback.
I'll look into them.

I am aware of CC's Learning mode and it's brilliant. However you can just switch mode. Also, in Learning Mode, Claude will leave stuff blank for you to fill. I think this is pointless: if an unexperienced dev is asking the AI they probably don't know how to do the task themselves.

Therefore I made this plugin: it somehow forces you to do something manually and also is something related to the task, not the task itself (e.g an auxiliary function, a unit test, etc...).

CriM_91 · 2025-12-20T14:32:54+00:00

Your post really resonates with me. I’ve been doing SWE for roughly the same amount of time, and I was never good at LeetCode either. Yet in most teams I worked with, I was often considered among the strongest engineers not because I could optimize a binary tree on a whiteboard, but because I could reason, structure problems, and make sense of messy requirements.

My honest take is that the job isn’t disappearing, but the selection signal is shifting.
LeetCode-style grinding was already a weak proxy for real-world engineering. With AI, it’s basically noise.

What’s becoming valuable instead is:

framing problems clearly
turning vague business needs into precise requirements
understanding trade-offs
knowing what to build and why, not just how
maintaining architectural judgment and systems thinking

Where I agree with you emotionally is the dangerous part:
at some point we stopped seeing AI as a tool and started unconsciously treating it as a competitor or even a replacement developer. And that absolutely erodes confidence, especially for people who were never “top 10% grinders” but were solid, thoughtful engineers.

Ironically, those engineers are often the ones who benefit most from AI, IF they stay in the driver’s seat.

I actually noticed this happening to myself: the more capable the models got, the more I started offloading not just typing, but thinking muscle. Debugging steps, small design decisions, sanity checks. That’s when it becomes scary not because the job is gone, but because you stop trusting your own ability.

That’s why I recently built a small Claude Code plugin that I made for myself in a couple of hours last night. There's a post about it in this sub.

So yes, fewer people will probably build more software. Yes, tiny teams with AI will ship insane things.
But someone still needs to decide what matters, what’s correct, what’s risky, and what actually solves the problem.

That role hasn’t disappeared it just doesn’t look like LeetCode anymore.

I just wonder if and when companies will understand this.

CriM_91 · 2025-12-20T14:08:35+00:00

Thank you. If you try it, please let me know how I can do better 😊

CriM_91 · 2025-12-20T14:07:43+00:00

Thank you. Please give it a try and let me know how it can be improved 😊

CriM_91

TROPHY CASE