A developer spent a year, not an evening, building a football management game. Here's why

The myth that modern AI tools allow you to develop a full-fledged project over the weekend has collided with harsh reality. One experienced developer was creating a football manager game, actively using AI. The story took not an evening — an entire year. And this despite the author already having programming experience.

Architecture and Tools Require Decisions

The first month looks simple: you generate code through AI, it seems to move quickly. But already at the planning stage, you have to choose the technology stack yourself, think through the database architecture, ways to save player progress. AI can suggest options, but the decision remains with the person. A failed choice at the start means a complete rework in a month or two.

Mechanics and Balance — It's Long Work

A football manager game requires complex interaction between systems: calculating player ratings, transfer mechanics, match tactics, club economy. AI can write code for each part, but only the developer will check if it works together, if nothing breaks when changing one parameter.

• Player cost balancing
• AI opponent difficulty adjustment
• Economic stability verification
• Rule changes based on player experience
• Refinement of random components and generation

Months are spent on testing and refining each system separately and their interaction as a whole.

Design and Assets — Real Volume of Work

When the mechanics are ready, interface design begins. You need icons, logos, transition animations between screens, error handling in the interface. Assets — player models, club logos, stadium textures — have to be created from scratch or found in open sources, and then brought to a unified style. AI can help with graphics generation, but fitting it to the design — it's still manual work.

Manual Assembly Exceeds Expectations

One non-obvious fact: AI generates chunks of code, but never gives a finished product. The chunks need to be assembled, integrated, fix dependency conflicts, catch bugs that appear only when different parts interact. It's like if you received a package with constructor parts — everything is there, but you have to assemble it yourself, and the instructions aren't perfect.

"Even with AI, a complete product — this is not an evening of work,

but a serious project," — roughly this is the conclusion the author of the story makes.

What This Means

AI really does speed up development, but not by orders of magnitude and not in every part of the project. The expectation of "an app in an evening with ChatGPT" has been dispelled by harsh reality: a complete product requires experience, planning, and time. The tool — it's not a replacement for the developer, but an amplifier of their capabilities.