Built my side project with vibe coding. almost shipped chaos. specs saved it. here’s my workflow

i’m building a small side project right now and i went full vibe mode at the start. it was fun until i realized the same thing keeps happening the AI ships fast, and then i spend 2x time unshipping the “helpful” extras so i switched to a simple process that keeps speed but adds adult supervision what i’m building a small SaaS style tool. FastAPI backend, Next frontend, Supabase for auth and db what changed everything for me i write a tiny spec for every feature before i let any tool touch code my spec template goal in one sentence non goals so it doesn’t add random features files allowed to change api contract. request response errors acceptance checks. exact steps to verify rollback plan. what to revert if it breaks my workflow 1 brain dump into Traycer AI and it turns it into a clean checklist spec 2 implement in small chunks with Claude Code or Codex 3 use Copilot for boring glue edits 4 run tests and force the tool to paste command output. no output. not done example acceptance checks i actually use auth try call endpoint with no token. should fail call with valid token. should pass rate limit hit endpoint 30 times fast. should start returning 429 db confirm Supabase RLS blocks cross user reads why i’m posting i’m curious if other side project people do specs like this or if you just raw vibe it and fix later also if you have any good tricks to stop agents from doing “bonus refactors” nobody asked for i want them if you want i can share the exact spec template file i keep in my repo. it’s short and it’s saved me a stupid amount of time

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FL score

75

out of 100

Verdict

VALIDATE

high confidence

Competition

8

competitors found, emerging market, funded players

Trend

8 community mentions

An AI-assisted spec generation and workflow tool for solo developers to prevent 'vibe coding chaos' and unwanted AI 'helpful extras' on side projects.

The pain

Solo developers building side projects with AI often experience 'vibe coding' that leads to chaos, rework, and spending 2x the time 'unshipping' unwanted features added by AI assistants, causing frustration and inefficiency.

The gap

Existing project management tools are overkill for solo developers and lack developer-specific, pre-code spec features, particularly for managing AI interactions. No current tool focuses on structured specs with non-goals, API contracts, and acceptance checks to guide AI-assisted development effectively.

Build angle

Build a lightweight, developer-first tool offering a structured spec template (goal, non-goals, files, API contract, acceptance checks, rollback plan) with AI assistance to generate and refine these specs from high-level ideas, specifically for solo side project builders using modern tech stacks.

Strengths

  • Extremely specific and relatable pain point for a growing audience (solo builders using AI).
  • Strong founder-problem fit, derived from personal experience.
  • Clear white space in a crowded market of general PM tools.
  • High willingness to pay for a tool that saves significant time and reduces rework.
  • Leverages the trend of AI-assisted development, becoming more essential over time.
  • Simple MVP (template management) is quickly shippable.

Risks

  • The 'AI-assisted' part of spec generation could add significant build complexity for a solo builder.
  • Potential for developers to prefer self-managed markdown templates over a dedicated tool if the value isn't clearly superior.
  • Distribution requires deep engagement within developer communities.
  • Ensuring the tool remains lightweight and focused, avoiding the 'bloat' it aims to solve.

Next steps

  1. Share the exact spec template file, as offered, to validate demand for the structured approach.
  2. Gather more specific feedback on the 'Traycer AI' concept: how much AI generation vs. checklist management is desired?
  3. Build the absolute simplest MVP: a web app for managing and sharing these spec templates, possibly starting with manual input.
  4. Focus initial AI integration on generating first drafts of specs from user input, rather than full 'agent' capabilities, to manage complexity.

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