“No Duh,” say senior developers everywhere.
The article explains that vibe code often is close, but not quite, functional, requiring developers to go in and find where the problems are - resulting in a net slowdown of development rather than productivity gains.
Thank you for reading my comment. I’m on the train headed to work and I’ll try to answer completely. I love talking about this stuff.
For my work, absolutely. My work is a lot of tickets that were setup from multiple stories and multiple epics. It would be like asking me if I am really framing a house faster with a nail gun and compressor. If I were just hanging up a picture or a few pictures in the hallway, it’s probably faster to use a hammer than to set up the compressor and nail gun, plus cleanup.
However, a lot of that documentation already exists by the time it gets to me. All of the Design Documents and Product Requirement Documents have already been formed, discussed, and approved by our architecture team and team leads. Imagine if you already had this documentation for the asteroid game; how much better do you think your LLM would do? Maybe this is the benefit of using LLMs for development at an established company. Btw, a lot of those Documents were also created with the assistance of AI by the Product Team, Architects, and Principle/Staff/Leads anyway.
With the help of our existing documents and codebase(s) I feel I dont have any issues with the model knowing what we’re doing. I do have to set up my own context for how I want it to be done. To me this is like explaining to a Junior Engineer what I need them to help me with. If you’re familiar with “Know when to Direct, when to Delegate, or when to Develop” I would say it lands in between Direct and Delegate. I have markdown files with my rules and guidelines and provide that as context. I use Augment Code which is pretty good with codebase context.
I would try “Let’s plan out the steps needed to write an Asteroids game using JavaScript and HTML 5. Identify and explain each step of the development plan. The game must build with no errors, be playable, and pass all tests. Do not wrote code at this time until our plan is approved” Then once it comes back with the initial steps, I would guide it further if needed. Finally I would approve the plan and tell it to execute while tracking it’s steps (Augment Code uses a task log).
We are required to use the frontier models that my employer has contracts with and are forbidden from using local models. In our enterprise contracts we have negotiated for no training on our data. I imagine we pay for that. I’m not involved in that level of interaction on the accounts.
We have other teams that handle a lot of these tasks. These teams are also using AI tools to get the job done. In addition, we have static testing tools on our repo like CodeRabbit and another one I can’t remember the name of that looks specifically for security concerns. It will comment on the PR directly and our merge would be blocked until handled. Code coverage for testing is at 85% or it blocks the merge and we have a full QA department of Analysts and SDETs to QA. In addition to that we still have human approvals required (2 devs + Sr+). All of these people involved are still using AI tools to help them in each step.
I hope that answers your questions and gives you some insight into how I’ve found success in my experience with it. I will say that on my personal projects I don’t go this far with process and I don’t experience the same AI output that I do at work.
Thanks for your reply, and I can still see how it might work.
I’m curious if you have any resources that do some end-to-end examples. This is where I struggle. If I have an atomic piece of code I need and I can maybe get it started with a LLM and finish it by hand, but anything larger seems to just always fail. So far the best video I found to try a start-to-finish demo was this: https://www.youtube.com/watch?v=8AWEPx5cHWQ
He spends plenty of time describing the tools and how to use them, but when we get to the actual work, we spend 20 minutes telling the LLM that it’s doing stuff wrong. There’s eventually a prototype, but to get there he had to alternate between ‘I still can’t jump’ and ‘here’s the new error.’ He eventually modified code himself, so even getting a ‘mario clone’ running requires an actual developer and the final result was underwhelming at best.
For me, a ‘game’ is this tiny product that could be a viable unit. It doesn’t need to talk to other services, it just needs to react to user input. I want to see a speed-run of someone using LLMs to make a game that is playable. It doesn’t need to be “fun”, but the video above only got to the ‘player can jump and gets game over if hitting enemy’ stage. How much extra effort would it take to make the background not flat blue? Is there a win condition? How to refactor this so that the level is not hard-coded? Multiple enemy types? Shoot a fireball that bounces? Power Ups? And does doing any of those break jump functionality again? How much time do I have to spend telling the LLM that the fireball still goes through the floor and doesn’t kill an enemy when it hits them?
I could imagine that if the LLM was handed a well described design document and technical spec that it could do better, but I have yet to see that demonstrated. Given what it produces for people publishing tutorials online, I would never let it handle anything business critical.
The video is an hour long, and spends about 20 minutes in the middle actually working on the project. I probably couldn’t do better, but I’ve mostly forgotten my javascript and HTML canvas. If kaboom.js was my focus, though, I imagine I could knock out what he did in well under 20 minutes and have a better architected design that handled the above questions.
I’ve, luckily, not yet been mandated that I embed AI into my pseudo-developer role, but they are asking.