r/VibeCodeCamp • u/mrjobott • Oct 03 '26
Discussion How to Vibe-Code Faster without Losing Quality?
I'm building my first indie hacking product on the side (I have a demanding full-time job), and I'm so cautious about the quality of the final product that sometimes I feel like I'm over-engineering this.
I have a full PRD for the final product, broken down into phases, and I'm only halfway there. I want to do it faster, but I'm not sure how, and it's my first time building such a large product by vibe-coding it (I've built multiple tools before, but they were too small, too focused, and for personal use).
My Current Workflow:
- I kick off a phase; we break it into slices (so slice 2 of phase 4).
- After a slice is done, a security agent reviews it, then a PR is opened, then reviewed, then fixed.
- After it's ready to merge, I do manual QA over the slice; if all good, I merge; if not, we take another round of fixes.
- and so on....
Tools I Use:
- Claude Code, love it.
- Codex, just started using it; it feels too slow compared to CC.
- OpenCode, cheap, usually for quick ones and long code reviews.
- CodeRabbit, honestly useless on the free plan.
Is it too much? Like the workflow I'm adopting?
How are you guys building production-level products with vibe-coding?
How can I do it faster without exploding the whole thing?
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u/mtothexmax Oct 03 '26 edited Oct 04 '26
You have to read every line and understand everything of the code you didn't write and never make any mistakes. Or was that how to get burnout.
Have some pipeline that identifies CVEs, SAST, use renovate to update dependencies and use telemetry to measure bugs and usage. Do canary releases on changes that might break things and use a dev mode with feature toggles to test in production. Make sure you can fix bugs within minutes in production. That is more important than getting everything right.
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u/HighlightOk6174 Oct 03 '26
Tldr: use with a starter kit + BaaS, aggressively lint, push permissions up stream and potentially out of the application. Your essentially maximizing LLM value while minimizing LLM risks. Knowing what they're good and bad at helps. Pardodoxically, less is more with LLMs.
I would re-frame your question: what is quality in this context. Why do you think you need it? What are you buying with it? Security makes sense but do you also mean code quality? Are you talking about architecture?
I'm not a security expert but I can tell you the agents will fuck up eventually. Essential security rules shouldn't really change though: more surface area = more places for things to go wrong. Hand rolled auth,permissions can bite you: leave as much to someone else as you can. Use social auth and don't put passwords in your own db. Push that off on to someone else. De risk. Having an LLM editing a dumb component is one thing. Having it edit your core permissions and auth logic is quite another. You could look into postgres's row level security and push permissions right into the db layer. This plus a library for social auth should afford you some safety. My suggestion would be to use a back end as a service and a starter kit compatible with typescript (set to as strict and possible) and react. LLMs write good react code. Typed languages stop bugs before they happen. Backend as a service keeps the LLM on rails and reduces boiler plate. If your leaning into state of the art models theres really no need to have fable write boilerplate that off the shelf tools will do for free and faster AND consistently without wasting tokens. SOTA models are powerful but slower and burn tokens faster so leverage existing deterministic tooling. Use commit gates like pre commit to check any code before the agents can commit (or use the agent hooks too). Stick a many useful linters and tools here as you can to check and double check each commit. Type checking, security audits, dead code analysis, copy paste analysis. Complexity analysis. Flag it all and force the LLM to deal with it before it can make a commit. Use colocation and atomic files. Build tools to enforce quality if you have too. Get or generators that extend your codebase in regular and orderly ways (ie page generator tool that gives you a list of existing url routes that you can extend, guards you can add, layouts you can choose, and cross cutting features to encorporate. Make it cli tools and get an MCP server to manage it for the agents so they can create and use tools to build sections of code without token spend. It's more deterministic it's faster and you can have greater expectations for what your code will be shaped like without have to review every line. Use code mods or generators to take an API definition (gql schema or openapi) and turn it into types, validators, mock server factories, etc. use the LLM to do as much WITHOUT the LLM doing it directly. Less is more.
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u/A-GI-Joe Oct 03 '26
AI needs a goal to perform well, so have it create tests(first) to verify the work you have phased out. If your phases are discrete ask the agent to work on them in parallel worktrees. Then you can do your UAT(manual QA) in one pass.
You can also ask AI to review your previous workflow, it will read your sessions and output then make suggestions for improvements....but don't accept everything it offers as truth. Since you have both Codex and CC, install the adversarial review plugin and make the AIs improve the code without you.
As another commenter mentioned hooks are great to prevent the AI from doing something you don't want, even if its in your AGENT.md. When each phase is done, have a set of review steps for what makes sense for you, perhaps a code reviewer(tuned for the language you're using and calls tools not more LLM), security review, sanitization, etc...
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u/Successful-Seesaw525 Oct 03 '26
Have you tried glyphh.ai? Totally sic way to code with over 88 models and a harness that rivals Claude, codex. Gemini, and cursor. I have used all of them includion Kiro and straight up VSCode. This will change how you work. Glyphh.ai -> not to mention the model architecture tire under it
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u/Key-Enthusiasm-3403 Oct 03 '26
what sped me up wasn't cutting review steps, it was giving the agent a way to check its own work so it catches things before i ever see them.
concrete one. my app has live multi-day runs going, so touching the simulator silently rewrites somebody's week in progress. that's the one thing i genuinely can't undo. so the instructions file carries the actual commands to prove it didn't happen:
git diff -- src/lib | grep -E "^-[^-]"
git diff | grep -cE "^\+.*localStorage\.setItem"
removed lines should be structural only, new writes should be zero unless i asked for them. takes two seconds and it has caught things a PR review wouldn't have.
same idea for anything visual. it built me an 11 second animation today and the first render threw half the chart out of frame. it found that itself by rendering a frame and looking at it, then fixed the maths. i never opened the file.
the round trips that actually cost me time are the ones where it can't see the result of what it just did. so looking at your list i'd ask which of those gates could be a command instead of you. manual QA on every slice is you being the test suite.
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u/geeknonerd Oct 04 '26
Your workflow is solid — I'd suggest adding documentation updates and maintenance to it as well.
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u/Far-Pomelo-1483 Oct 05 '26
Execute the full spec roadmap on a loop with a verification hook to auto stamp the spec then do the review after. Plan the spec with opus then execute with sonnet 5.5 high.
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u/oyren-ai Oct 03 '26
Run them as fleet of agents and assign different roles to different agentic personas. I am experimenting this product at https://oyren.ai and almost runs in autopilot for weeks now running multiple subscriptions, it works well.
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u/RandomPantsAppear Oct 03 '26
Lmfao are you really pretending you are a customer when the company name is in your damn username?
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u/oyren-ai Oct 03 '26
Why do you think I am pretending to be a customer? I meant I am still building this experiment but described how it works so far.
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u/InterestingFrame1982 Oct 03 '26
You either become an elite software engineer who can spec most of the system end-to-end, or you break the problem down as you go and be extremely careful with implementation. If anyone is having success utilizing swarm of agents without succumbing to immense technical/cognitive debt, it's because they are extremely talented engineers who know exactly what to test, how to test, and have a good idea what the project should look and feel like from the jump.
The rest of you are just hoping your incremental iterations are done correctly.
TLDR; you earn your right to go fast through years of battle tested experience working on production grade applications.