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Ihor Codes: post #176 — TG.ME

Ihor Codes@ihor_codes · 1K subscribers Open in TelegramOpen

fun

https://cursor.com/2025

t.me/ihor_codes/176

6

5

December 21, 2025 2.6K 7

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https://boristane.com/blog/the-software-development-lifecycle-is-dead/ 1.5K·Feb 25 My Cursor workflow: 1. I first use my brain to understand what I need and how I would solve it. 2. I read the codebase and find the places where I need to make changes - this also gives me an understanding of the effort: whether the llm can one-shot it or if I need to split it into smaller steps. 3. I tag related files (the most important ones, not all) and describe the feature I want - I type this myself. I tried switching to voice, but when i type, my brain thinks more and i like it : ) 4. I always run it first in Plan mode with Sonnet 4.5. 5. If I like the plan, I execute it with: • Opus 4.5 when the code change is small and I understand it fits into the 200k context window (its fast and reliable, but worse on large changes) • GPT-5.2 Codex if the problem is hard - it follows commands a bit better without deviations, but it’s super slow (slow, good in following plan) • Sonnet 4.5 when it’s a big change across many projects (fast, reliable enough for day to day tasks) • When I need to design UI, I go to Google AI Studio (gemini 3 pro). Usually 2-3 shots are enough to get a design I like. Then I export it as a zip, paste it into my codebase, and ask Sonnet 4.5 to integrate it into the project. Works like a charm. If i dont like the plan - do 1-4 again. 6. Once the feature is ready, I accept all changes right away and test it. If everything works fine, I briefly read the PR and merge it. If there are errors, I prompt the model to fix them - but at this point, I study the implementation more carefully and make sure I understand the changes. • I noticed that if it works on the first try, it usually means the plan was followed well, so I don’t need to pay much attention to it. • But if there’s a bug, there’s a high chance something went wrong, and I need to make sure there were no deviations from the plan. I usually spend around $300-400 per month on this ($200 sub + credits). Would be happy to hear your workflows. These days everything changes super fast, and its nice to hear what other people are doing. That's the motivation for that post. 2.2K·Jan 24 Im happily surprised by the results, I thought that much fewer people use AI. For me, it’s 100%. I forgot when was the last time I wrote something on my own. Last year, Cursor did this: - wrote infra scripts for setting up switches / routers / machines in an on-premise data center (which is crazy if you ask me. I thought this one was not going to work, but after a few hundred bucks in credits, it solved it. single script to set up all the hardware I had) - built numerous full-stack apps (shoutout to the gemini 3 that now does amazing UIs for everything that i do) - rewrote one app after it got a lot of traffic. The first implementation was "not optimal"... 20 minutes later - fully covered with tests, 20 minutes later - redis for queues and caching. same business logic, 100x performance + full documentation with system design-like graphs). I specifically selected those 3 use cases because they show us that now AI can: build basic apps, scale them if needed and fully cover the infra part. disclaimer: of course, without my expertise it would not work. on its own, it often hallucinates and ends up in a broken state. so, it doesn’t replace us, it empowers us to do 100x more. I love the future 🚀 3.2K·Jan 7 [media post] 8.7K·Jan 7

fun https://cursor.com/2025 2.6K·Dec 21

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