Comment by SXX

I worked years as backend and desktop software programmer, then in gamedev and now back to SaaS development mostly backend. I didnt have much success with agentic coding with "agents", but had a great success with LLM code generation while keeping all the code in context with Google Gemini.

For gamedev you can really build quite complex 2D game prototype in Pygame or Unity rapidly since 20-50KLOC is enough for a lot of indie games. And it allow you to iterate and try different ideas much faster.

Most of features are either one-shots doing all changes across codebase in one prompt or require few fixing prompts only.

It really helps to isolate simulation from all else with mandatory CQRS for gamestate.

It also helps to generate markdown readmes along the way for all major systems and keep feature checklists ih header of each file. This way LLM dont lose context ot what is being generated.

Basically I generated in 2-3 weeks projects that would take 2-3 months to implement in a team simply because there is much less delay between idea of feature and testing it in some form.

Yes - ocassiinally you will fail to write proper spec or LLM fail to generate working code, but then usually it means you revert everything and rewrite the specification and try again.

So LLMs of today are certainly suitable when "good enough" is sufficient. So they are good for prototyping. Then if you want better architecture you just guide LLM to refactor complete code.

LLMs also good for small self contained projects or microservices where all relevant information fits into context.