The truth about AI coding inflation: The "God Object" tragedy after 7 months of Vibe Coding

Core conclusion

A developer used Claude AI for 7 months of "vibe coding" to create a GPU cluster management tool k10s. Although the 10x speed development felt amazing in the early days, as the code grew, the 1,690 lines of code accumulated by AI unconsciously turned into a "god object" containing 110 switch/case branches, which eventually caused the architecture to completely collapse and had to be rewritten from scratch.

Core lesson: AI is good at writing functions, but not good at designing architecture. The illusion of speed of vibe coding makes developers think that "every feature is free", when in fact the complexity bill keeps piling up.

Key Points

• Incident: Developer Shvbsle used Claude to write the k10s TUI tool, archived and rewritten after 7 months
• Core issue: AI generates "God object" mode by default - a struct containing UI components, K8s client, all view states, navigation history and mouse event handling
• Social response: Hacker News 120 likes, a large number of developers resonated

Background: The True Cost of 7 Months of Vibe Coding

In September 2025, a developer shared his complete experience of using Claude AI for vibe coding on Hacker News. He developed a GPU cluster management interface k10s using the Bubble Tea framework of the Go language. The goal is to make a TUI tool more suitable for GPU operation and maintenance personnel than k9s.

The first few weeks were the "magic time." He only needs to prompt "Add a Pods view with live updates" and Claude can generate a complete resource list view, namespace filtering, log streaming, description panel and keyboard navigation. It only took 3 weekends to have a basically working k9s clone.

But the problem came to a head seven months later.

Key Impact: Five Hidden Pitfalls of AI Coding

This developer pulled 5 ironclad rules from the ashes, revealing the systemic pitfalls of AI-assisted programming:

The Real Risks of Vibe Coding

The most shocking part of this reflection article is: Every piece of AI code is reasonable when viewed independently. Added mouse support, log streaming, shell execution...everything works perfectly in a single prompt. But AI cannot see the architectural decay process of 49 functions sharing the same state structure.

Specifically, in the key processing function of k10s, a key triggers three completely different behaviors in different views:

• In log view = auto scroll
• In Pods view = enter container shell
• in container view = execute command inside container

All branches are written in a flat function, and views are distinguished by string comparison such as m.currentGVR.Resource == "namespaces". This is a typical short-term optimization of AI - only see "make it work now" every prompt, and don't care about the maintenance cost after 6 months.

Adaptation suggestions

For teams and individuals who are using or planning to use AI coding tools:

1. Write the architecture first, then write the code - AI will not take the initiative to help you design modularity. Use CLAUDE.md or AGENTS.md to clarify the architectural rules so that the AI can read these constraints every time it prompts
2. No God Objects - Each view is an independent struct, and views cannot access each other's status.
3. Typed over positional - always use structured types to store data, do not use []string index positions
4. From background tasks to UI state changes, you must go through the message channel - Do not let background goroutine directly modify UI fields
5. Regular code review of AI output – “normal” code for AI may be quietly degrading the architecture

Example: Schema rules in CLAUDE.md

# Architecture Invariants
- Each view implements the View trait. Views do NOT access other views' state.
- All async data arrives via AppMsg variants. No direct field mutation from background tasks.
- Adding a new view MUST NOT require modifying existing views.
- The App struct is a thin router. It owns navigation and message dispatch.
- NEVER flatten structured data into []string or positional arrays.

Reference video/material

• I'm going back to writing code by hand
• Hacker News
• Bubble Tea TUI

Tool entry (trigger tool floating card)

Mentioned in the text: Claude, AI Agent, OpenAI, ChatGPT, n8n

Internal link guidance

• Want to learn AI coding tools systematically? Watch: Claude Code automated writing practice: build an AI content production pipeline in 30 minutes
• Someone made real money using Claude Code: Claude Code 48 hours to start a business: one person + US$29 monthly fee, monthly income in 3 months $9,000