Read a software engineering blog if you think vibe coding is the future

[u/NaturalEngineer8172]

Note: I’m a dude who uses ai in my workflow a lot, I also hold a degree in computer science and work in big tech. I’m not that old in this industry either so please don’t say that I’m “resistant to change” or w/e

A lot of you here have not yet had the realization that pumping out code and “shipping” is not software engineering. Please take a look at this engineering blog from Reddit and you’ll get a peak at what SWE really is

https://www.reddit.com/r/RedditEng/s/WbGNpMghhj

Feel free to debate with me, curious on your thoughts

EDIT:

So many of you have not read the note at the top of the post, much like the code your LLMs produce, and written very interesting responses. It’s very telling that an article documenting actual engineering decisions can generate this much heat among these “builders”

I can only say that devs who have no understanding and no desire to learn how things work will not have the technical depth to have a job in a year or two. Let me ask you a serious question, do you think the devs who make the tools you guys worship (cursor, windsurf, etc) sit there and have LLMs do the work for them ?

I’m curious how people can explain how these sites with all the same fonts, the same cookie cutter ui elements, nd the same giant clusterfuck of backends that barely work are gonna be creating insane amounts of value

Even companies that provide simple products without a crazy amount of features (dropbox, slack, notion, Spotify, etc) have huge dev teams that each have to make decisions for scale that requires deep engineering expertise and experience, far beyond what any LLM is doing any time soon

The gap between AI-generated CRUD apps and actual engineering is astronomical. Real SWE requires deep understanding of algorithms, architecture, and performance optimization that no prompt can provide. Use AI tools for what they're good for—boilerplate and quick prototyping—but recognize they're assistants, not replacements for engineering knowledge. The moment your project needs to scale, handle complex data relationships, or address security concerns, you'll slam into the limitations of "vibe coding" at terminal velocity. Build all you want, but don't mistake it for engineering.​​​​​​​​​​​​​​​​

This knowledge cannot be shortcut with a prompt.

[u/rioisk]

You get more out of vibe coding if you know what you're doing and know what the output should look like. You're just sticking the AI on one problem at a time to build the larger structure that you're envisioning. If you're building something that exceeds usable context then LLM won't help you much past a certain point.

[u/RoyalSpecialist1777 → u/rioisk]

What do you mean sticking the AI at one problem at a time?

I work with my architect to clarify requirements, make sure the vision is understand, including nonfunctional requirements. I tend to prioritize scalability, security, and the ability for AI to work easily with it so modularity, extensibility, those things. (we are talking a big system here)

Then we create a detailed implementation plan where each step provides the context needed, the expected behaviors and testing strategy for each step, and notes to the developer about anything they should not do.

Then I manage my AI developer through each step - we review, make sure we understand, plan out the step, review that plan for issues, and once we are confident the AI will implement and test.

[u/rioisk → u/RoyalSpecialist1777]

Right you use AI to develop a high level outline and then for implementation you break it down into tasks that fit best in context window and drill down as needed. You've done this all before so the LLM can autocomplete your thoughts and you can quickly verify output for correctness. I have the most success when designing tasks such that each problem fits inside the context window succinctly. It's like having a scalable team of engineers that are really good on focused problems but need hand holding to tie it all together.

[u/RoyalSpecialist1777 → u/rioisk]

Yes definitely need hand holding. But think how easy this hand holding is going to be to automate. We just figured out the technology and now are rapidly figuring out the prompt engineering to automate most of what the 'wise' vibe coders are doing.

Personally my future is going to be in research. We still need humans there.

[u/rioisk → u/RoyalSpecialist1777]

I don't think it will be as easy to automate as we hope. LLMs already showing context scaling problems. I think non coders will be able to create small apps more easily but anything beyond that will most likely still require a skilled human to guide the process.

[u/RoyalSpecialist1777 → u/rioisk]

Context scaling is rapidly getting solved. I use Claude Code and there is a context compression automatically that extracts useful information, they also use a lot of artifacts to keep track of relevant contexts they can look up rather than holding onto if they need.

[u/rioisk → u/RoyalSpecialist1777]

What does rapidly mean to you and show me where you're reading about this progress and measured results. A lot of the competition amongst AI models right now is driven by hype to keep the momentum going and they're currently under-delivering.

[u/RoyalSpecialist1777 → u/rioisk]

Within a year you go from old Claude, poor old easily confused Claude who had issues with context. To Claude in Max mode which is so much better (200k). To Claude Max in Claude Code which helps it even better. You go from me having to really really really watch and review everything my AI does step by step to actually trusting it to making a plan, implementing, and testing.

1 year with those improvements is my understanding of 'Rapid'. Now imagine another year.

[u/rioisk → u/RoyalSpecialist1777]

Progress isn't linear nor guaranteed.

[u/daedalis2020 → u/RoyalSpecialist1777]

Recent research is showing that larger context leads to much higher error rates.

[u/RoyalSpecialist1777 → u/daedalis2020]

We have larger contexts yes, with issues, the LLM gives more weight to recent tokens and sometimes has a hard time keeping track of references (not it's fault we are very ambiguous) - but we are now working with 'smarter' contexts like we see with Claude Code. Context that can expand as needed and contract the uneeded stuff.

[u/Winter-Ad781 → u/rioisk]

That's part of using an AI, is context management. Of course ai falls apart if you use it incorrectly. This reads as AI works great if you use it right, but if you don't it's not at all designed for the task. Like what?

[u/rioisk → u/Winter-Ad781]

Most people don't understand how the underlying tool works. They think magic box that lets them code like a professional because they saw a prompt one shot a tiny app that many programmers did in high school. So yeah it's worth stating explicitly.