Developer seeks ways to have AI improve existing features rather than suggest new ones
A developer with over a year of AI-assisted project building reports difficulty getting AI to suggest improvements on existing features instead of proposing new ones. They have tried asking the AI to scan a project directory but find it consistently veers toward new feature suggestions.
Entities
Related
Developer seeks feedback on AI-assisted feature development pipeline
A developer shared a detailed 5-step assembly line for feature development using AI, where each step requires passing a checklist before proceeding. The process includes spec writing, plan review, and multiple reviewer passes for risky features. The post asks whether this approach is efficient or wastes tokens.
Developer recounts AI-assisted coding pitfalls after building 4 products in 3 months
A developer built four products almost entirely with AI over three months. Three turned out fine, but one became an unmaintainable mess requiring a complete rewrite. The developer blames their own iterative prompting approach, which layered patches without architectural foresight, leading to a fragile codebase that neither they nor the AI could later fix.
Developer open-sources agent-instructions repo to curb AI coding agent degradation
A developer frustrated by AI coding agents losing context and hallucinating after about 10 minutes created a set of rules to keep them on track. The rules, shared as an open-source GitHub repo, aim to reduce the need for constant reminders and prevent infinite loops. The project has gained attention from other developers facing similar issues.
Reddit user advocates writing exit criteria before prompts to prevent agent project stalling
A Reddit post argues that many agent projects stall because prompts are tuned before clear completion criteria are defined. The author recommends writing success state, required evidence, and handling of missing or partial evidence upfront to avoid agents optimizing for sounding finished.
Software engineers share best practices for using Cursor to write production-grade code
A software engineer asked the community for best practices when using Cursor to write production-grade code. The user currently provides architecture and design principle markdown files to guide the AI, but still encounters issues with object naming and placement not covered in those files.
