From Copy-Paste to Workspace Integration: A Developer's Experience with AI Coding Evolution
A developer shares their two-year journey with AI coding tools, starting with early ChatGPT attempts that produced unusable code with hallucinated libraries and made-up modules. The initial experience was so frustrating they abandoned the tool for nearly a year.
The Copy-Paste Era
When they returned, the workflow involved opening ChatGPT in a browser, pasting relevant files, describing constraints and interfaces, then copying output back into their editor. After testing, they'd paste broken parts back into chat with explanations and iterate. This worked but had significant limitations.
Context Management Challenges
The main problem was context management degradation. Early in sessions, models would follow conventions and remember architecture, but after about 50 messages they'd start ignoring instructions. By 80 messages, they'd lose track of the project entirely, requiring fresh sessions and 20 minutes of context rebuilding.
Workspace Integration Breakthrough
The developer wanted simple integration: "put the model in my workspace. Give it access to my files. Let it see the codebase instead of making me describe it through a chat window." Claude Code delivered this by running in the terminal and reading files directly, eliminating the copy-paste workflow and context rebuilding.
Current Limitations
Despite improvements, Claude Code still makes confident architectural mistakes, drifts when context gets thin, and needs additional structure that doesn't exist out of the box. The developer notes they're still building that supporting structure.
📖 Read the full source: r/ClaudeAI
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A developer used Claude AI to complete a 3-4 page performance evaluation document by asking it to 'complete this documentation using information you have about me.' The AI generated a detailed document in 5-6 minutes that included work contributions the user had almost forgotten.