The Night I Lost Faith in AI
Last Tuesday, I was on a deadline. A client wanted a real-time dashboard with authentication, dark mode, an...
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That excitement-to-despair cycle, yeah, everyone goes through it. But here's what I find wild: even your 7 "failures" taught you more about auth, WebSocket, and security patterns in one evening than most devs learn in a month of tutorials pre AI. The learning curve right now is insane, and the AI that "failed" is still accelerating it.
You're absolutely right and honestly, I didn't think about it that way until I read your comment.
The "failures" taught me more than the successes:
Kimi taught me why auth should NEVER be optional
Replit AI taught me to test in production-like environments
Cody taught me to verify every API endpoint before trusting it
You're spot on about the learning curve. AI isn't replacing the need to understand code it's just making the cost of mistakes lower, so we can learn faster by breaking things.
What's been your biggest failure that actually taught you the most? Would love to hear your experience. 🔥
This is even a very successful experience! In my tests, no one always succeeds, either because the task is too difficult or I don’t know how to explain.
I use Copilot and ChatGPT for complex tasks, but also use Easemate for smaller ones. He certainly gives me mixed feelings, offering all the models in one pile, but his Gemini 3 is really good (although his limit is too generous 🤔). Maybe I'm too contemptuous.
That's a really interesting mix! Copilot + ChatGPT + Easemate — sounds like you've built your own AI stack.
I haven't tried Easemate yet the all models in one pile sounds intriguing. Gemini 3 being surprisingly good doesn't shock me though. Google's been quietly improving while everyone's distracted by OpenAI vs Anthropic drama 😂
You mentioned mixed feelings what's been your biggest frustration with using multiple tools? For me, it's context switching between different interfaces. I'd love to know how you manage your workflow!
Also, totally agree on the task too difficult or I don't know how to explain part sometimes I spend more time crafting the perfect prompt than I would writing the code myself. Relatable. 🙃
I have a bad ISP (or rather, a good one, in that it somehow manages to ban me when I try to connect to pypi.org), and that's the whole problem. I constantly have to toggle the VPN off and on because one interface only loads halfway, another can't load at all, and another has problems because it doesn't trust the VPN IP address. It's truly strange. 😧
Oh man, that ISP + VPN + PyPI situation sounds like a technical horror story 😭
The half loads, half doesn't, half doesn't trust my IP I've been there. It's like each tool is playing its own game and you're just caught in the middle.
Have you tried WireGuard instead of OpenVPN? Helped me with the untrusted IP issue sometimes.
Also PyPI blocking VPNs is WILD. Hope your ISP stops being the villain soon! 😅☠️
Great research, excited to see "AI-Ready Code Review" framework, built something like that and posted about it yesterday. But also why just not use Claude Code with Opus or Codex they are light years ahead of these models.
Thanks Andrej! 🙌 And just checked your profile you're doing some really solid work on AI tooling. Respect.
You're absolutely right about Claude Code with Opus. I actually used Cursor with Claude 3.7 for the winner — which is essentially Claude under the hood. The difference was the tooling layer (context management, auto-fixes) made it easier to work with.
I haven't tried Codex extensively would you say it's significantly better than Claude Code for complex apps? Genuinely curious because I'm planning a follow-up with more advanced tools.
Also, would love to read your post on the AI-Ready Code Review framework! Drop the link here so others can check it out too.
Always learning from devs like you who are building in this space.
Thank you, appreciated! Well I have been using Claude thru CLI as my main driver for 2 months or so, and I have Codex subscription thru my work (so free basically).
I would say both struggle with specific UI styling, Codex just loves to make "AI slop" UI. But regarding the coding I prefer Claude since I configured my workflow around it so I might be biased towards it. But Codex can be also very powerful on coding.
For example I would send the codebase I did with Claude and have Codex to do a run and find tons of mistakes, maybe nothing that wouldn't stop you know but when you hit production even the small mistake can set you back.
In my opinion there is no better or worse, models are evolving and if you use flagship models it comes back to your workflow and preferences. Also I can send you the pass for a week of Claude Code if you are interested!
This is the link. Have to say this just a demo for now to inspire people, might evolve it. Hit me up if you're interested for collaboration.
Great breakdown. AI definitely boosts speed, but the real challenge is validation, security, and context — which still require strong dev skills.
Exactly! You hit the nail on the head. 💯
The AI writes code fast — but the REAL work starts after:
Is the auth actually secure?
Does this WebSocket implementation handle edge cases?
Is the context management correct across 20 files?
AI gives you 80% in 20% of the time. But that last 20% (security, validation, edge cases) still needs human expertise.
That's actually why I'm building the "AI-Ready Code Review" framework — a checklist to validate exactly what you mentioned.
What's your approach to validating AI-generated code? Would love to hear your process!
I usually review AI-generated code line by line, test each module independently, and focus especially on auth, edge cases, and security. AI is great for speed, but I always stay in control of the quality.
Solid workflow! Line-by-line + independent module testing is exactly how it should be done. 👏
I've found that auth and edge cases are where AI messes up most. So I have a "security first" rule — any AI-generated auth code gets reviewed twice, no exceptions.
Do you use any specific testing tools, or is it mostly manual? I'm always looking to optimize my review process.
Also curious have you ever caught something in review that AI confidently got wrong? Would love to hear the story 😄