The difference in coding performance between Claude and models like Gemini or DeepSeek feels quite noticeable. If someone can afford Claude for coding and open-source contributions, what about people who can’t? Do they just code more slowly? The gap sometimes feels like the difference between AOL Search and Google Search in the early days. Do developers without access to the strongest models end up spending far more time on prompt engineering, token usage, tool calling, agent frameworks, skill files, and debugging context drift, while others solve the same problem in a single prompt and contribute to open source much faster? A huge amount of software is built outside large companies—by independent developers, hobbyists, and small businesses. There’s also another question: many prompt-chain and wrapper ecosystems around poor models generate enormous amounts of interaction data. To what extent does that work ultimately become training or labeling data that primarily benefits AI labs rather than the developers themselves? submitted by /u/Impossible_Site7605
Originally posted by u/Impossible_Site7605 on r/ClaudeCode