A More Complex Vibe-Coding Workflow Isn’t Always Better

It is tempting to make vibe coding feel more professional by adding more steps: first a planner, then a builder, then a reviewer. I tried that on a small browser-game project. The result worked, but I preferred the design of the version built from one relatively open prompt.

The bigger improvement came later, when I gave the builder a much clearer description of the experience I wanted. Design, sound, feedback and technical expectations were made explicit before implementation. That version became my favourite.

The lesson I am taking away is not “never plan.” It is to ask what each step is supposed to improve. A detailed workflow cannot replace a clear idea of what good should look and feel like. Here is what I would carry into my next small creative project—and what this experiment cannot tell us.

Before choosing how many stages or agents a project needs, I would now describe what a successful result actually means. A working feature list is only part of that. In a browser game, it includes responsive controls, understandable feedback, pace, sound and a visual identity I want to return to.

My test case was three versions of a neon Snake game. A started from one open prompt. B used separate planning, implementation and review phases. C went back to one coherent build, but with eight Markdown specifications defining the intended experience. A later received a separate review and targeted fixes, becoming A+. The screenshots below are the evidence behind the lessons, rather than the point of the article.

This was not a controlled benchmark. Reasoning settings and instructions differed, and C explicitly asked for qualities the earlier briefs had not spelled out. I can describe what worked for me; I cannot isolate one variable and claim it caused the improvement.

The staged build was functional, but looked more like a standard implementation: a grid, score and buttons. The open-prompt version had a more distinctive arcade interface, stronger typography and a more considered HUD. More process had not automatically produced more character.

My practical takeaway: do not assume a planning step will supply your creative direction. Describe the visual hierarchy, atmosphere and interaction qualities that matter to you. Then look at the actual result. A technically organised implementation and a convincing design are different questions.

For your next project, write down three observable signs of quality before building. “The main action is obvious without an explanation” is something you can inspect. “Make it premium” leaves much more open to interpretation. That is a briefing habit I would try next, rather than a technique this experiment has independently proven.

Review earned its place when it looked for concrete failures. In the staged build, it found lost active time around pause or restart, and a stale second tab overwriting a higher highscore. Those findings were reproducible and could be fixed. That is a much clearer contribution than simply asking another agent to “make it better.”

I would separate creative judgement from bug review. First, use the prototype and decide whether its direction is worth keeping. Then ask the reviewer to reproduce functional problems, explain the expected behaviour and provide regression tests. Tell it which design and UX decisions must survive.

The screenshot below shows the visually simpler build. Its review still did useful work. A result can teach me something technically without becoming my preferred creative direction.

The first build passed all 17 existing tests. A later independent review nevertheless reproduced four additional issues: stale-tab highscore handling, lost simulation time on slow frames, tones continuing after mute, and interrupted multitouch control.

That changed how I read a test summary. A green result tells me the checked scenarios passed. It does not tell me every important scenario was included, or whether I will enjoy using the result. Before asking for more tests, I want to ask: which behaviour are we still uncertain about?

The useful follow-up was targeted repair, with the visual design protected. Only game.js changed among the production files in the A+ fix. The existing report documents the original 17 tests and 12 supplementary checks passing, with a timing-test route corrected as disclosed in the report. This was evidence for those fixes, not an exhaustive cross-browser guarantee.

A review prompt I would reuse is: reproduce the mismatch first, add a test that demonstrates it, fix the cause and check that the approved experience survives.

The most interesting improvement came when I changed the brief. Instead of relying on the agent to infer what “a good game” meant, I supplied a structured specification covering the intended experience as well as the rules.

The package happened to contain eight Markdown files. Eight is not a magic number. These were the dimensions it covered; for a smaller project, some could fit into one short document:

Those specifications left implementation choices open while making the intended effect much clearer. The builder was also explicitly asked to use generated image assets where available, and to implement sound and effects.

If one of those qualities matters to you, put it in the brief. It is hard to fairly criticise a build for omitting an experience you never clearly requested.

That was my verdict after playing: design, sound and game dynamics made the result feel better. But the qualification matters as much as the praise. C received a richer creative brief. We cannot attribute the improvement solely to Markdown, fewer handoffs or a particular model setting.

For me, the reusable lesson is to invest effort in the information the builder needs. Adding another phase is useful only if it resolves a problem the existing workflow is leaving open.

I would use a planning conversation when I cannot yet explain the behaviour I want, when choices depend on one another, or when a wrong assumption would be expensive to undo. I would ask it to show the options and tradeoffs, rather than quietly inventing the creative direction for me.

Those are recommendations I take from the experience, not outcomes this three-build comparison has measured. This experiment was small. It tells us little about work involving many contributors, existing production systems or safety-critical requirements. In those situations, additional structure may address concerns that never appeared here.

There is another limitation worth keeping in view: the open-prompt build used Very High reasoning, while the staged implementation used Low/Medium reasoning, with stronger settings for planning and review. The difference in results does not establish that planning itself made B worse.

My decision rule is therefore a question: what specific risk, ambiguity or quality gap will this extra step address? If I cannot answer that, I would first improve the brief or inspect the prototype.

This is a new template derived from the lessons, not an original chat prompt. Adapt it for a small website, tool or game:

What I want to keep from this experiment is a useful division of work: I supply the creative intent and judge the experience; the builder implements it; a reviewer investigates problems with a clear remit. That is a workflow I want to keep testing, not a universal formula.

The three demos above let you inspect the concrete examples behind these observations. A serves the reviewed A+ version, B includes its QA fixes, and C is the current richer-brief build. They are companion experiments, not frozen snapshots of every earlier stage or entries in my main games catalogue.

For related experience, read how I build and judge browser-game prototypes, what building my own CMS taught me or how everyday annoyances became practical tools.

These lessons come from my Snake A, B, A+ and C projects on 5 November 2026: project conversations, local files, review reports and my own play impressions. The quote about design, sound and game dynamics comes from a short follow-up interview. Screenshots show actual interfaces inside illustrative monitor frames; C includes AI-generated game artwork.

Before hosting these review copies, the 17-test A+ suite, expanded 21-test B suite and 35-test C suite were rerun successfully. Those suites cover different scenarios and their totals are not comparable quality scores. Historical audit findings are attributed to existing reports. Model settings, instructions, assets, test scope and development time were not held constant; preferences about design and game feel were mine, not results from a blinded panel.

The practical suggestions in this article extend my observations into a workflow to try. They are not an external benchmark or a claim that a simpler process is always better. Prepared with AI assistance and awaiting my editorial review.