IdeaWell

Project ideas from Hacker News discussions.

Professional software developers don't vibe, they control

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

1. Mental Exhaustion from AI Wrangling

Many developers report higher productivity but greater fatigue from managing AI agents, missing the relaxing flow of direct coding.
"asmor: Is anyone else getting more mentally exhausted by this? I get more done, but I also miss the relaxing code typing in the middle of the process."
"simonw: Yes, absolutely, I can be mentally wiped out by lunch."
"whynotminot: It feels like we all signed up to be ICs, but now we’re middle managers and our reports are bots."

2. Shift to "Steering Systems" Over Hands-On Coding

AI tools elevate senior devs to architect/manager roles, akin to tech leads delegating to humans or bots.
"runtimepanic: The real skill gap isn’t prompt cleverness, it’s knowing when the agent is confidently wrong and how to fence it in with tests, architecture, and invariants."
"jghn: Once a dev reached a certain level, they often weren't doing much 'relaxing code typing' anyways before the AI movement. I don't find it to be much different than being a tech lead."
"remich: Now that we have agents to do these things, it's not really all that different - although it is a different management style working around their limitations."

3. Divergent Experiences by Skill, Use Case, and Codebase Scale

Adopters praise speed on boilerplate/hobby projects; skeptics decry poor quality, large codebase limits, or prefer craft enjoyment.
"llmslave2: Developers have wildly different standards for what constitutes working code... for the developers with a lower threshold, AI is like crack... For others... it's more like a 10x slowdown."
"William_BB: Coding agents simply don't work at that scale [100x-1000x lines]... not even close to making these agents work at industrial scale."
"banbangtuth: I simply have too much fun programming... I always code by hand all my code. If you want to replace me, replace me."

🚀 Project Ideas

AgentFlow Optimizer

Summary

  • A CLI tool that batches multiple LLM agent tasks into parallel pipelines, simulates deferred compilation (like old-school C++), and provides instant syntax/visual feedback without full execution, reducing mental exhaustion from waiting and context switching.
  • Core value: Restores developer flow by minimizing serial waits, allowing "write a lot, compile later" for agentic coding.

Details

Key Value
Target Audience Senior devs using Claude Code/Codex CLI frustrated by slow iterations
Core Feature Batch prompt queuing, local mock execution, diff-based previews
Tech Stack Rust CLI + local LLM inference (Ollama), Git integration
Difficulty Medium
Monetization Revenue-ready: $10/mo pro tier

Notes

  • "Long iteration cycles are taxing" (bccdee); "painfully slow compile time to code ratio" (9rx) – HN would love deferred feedback like xkcd/303.
  • High utility for large tasks; sparks debates on agent ergonomics.

HybridCraft IDE Plugin

Summary

  • VS Code/Cursor extension that auto-detects "flow state" via typing speed/keystrokes, seamlessly switches to manual coding mode (disabling agents) for craft-focused work, and re-engages AI for boilerplate/outcome tasks.
  • Core value: Lets craft-lovers code manually for dopamine hits while using AI for utility, bridging "deep/craft vs. black box" divide.

Details

Key Value
Target Audience Devs missing "relaxing code typing" (asmor, simonw) and alternating modes (teaearlgraycold)
Core Feature Flow detection AI, one-click mode toggle, AI "patch" for boilerplate
Tech Stack TypeScript/VS Code API + lightweight ML (TensorFlow.js)
Difficulty Medium
Monetization Hobby

Notes

  • "I miss the relaxing code typing" (asmor); "focus on high satisfaction projects" (sanufar) – appeals to "craft-and-decomposition-loving" group (agumonkey).
  • Practical for daily use; fosters workflow sharing threads.

Codebase Modularizer

Summary

  • Service that analyzes large monorepos, auto-suggests/splits into agent-friendly modules (hobby-project sized), generates inter-module docs/tests, enabling effective agent use at scale.
  • Core value: Makes industrial codebases tractable for agents without microservices hell, solving "100x larger than hobby projects" issue.

Details

Key Value
Target Audience Staff engineers on massive codebases (William_BB, bccdee)
Core Feature Dependency graph analysis, module extraction, auto-CI/CD stubs
Tech Stack Python (NetworkX for graphs), Tree-sitter parser, GitHub Actions
Difficulty High
Monetization Revenue-ready: Freemium (free <10k LOC, $20/mo enterprise)

Notes

  • "codebases that are 100x... agents don't work at that scale" (William_BB); "split big code bases into parts" (baq) – directly quotes pain, avoids microservices pitfalls.
  • Utility for teams; potential for HN case studies on monolith-to-modules.

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