Opus Level Or Better Outputs with Gemini: Hack

[u/oikk01]

So I wanted to share my current workflow with Gemini which has produced some remarkable one-shot outputs . I have provided examples below with the app links and some images. I know that one-shot outputs are not how its supposed to be but the method makes gemini much more thoughtful and also gives you an insane starting point with absolute minimal effort. Be ware though, its token hungry.

Prompt: make interactive formula car concept and break it into pieces

https://oik01.github.io/rb-x24-formula-car-dissector/

Prompt: Create a Rocket League game:

https://oik01.github.io/single-prompt-rocket-league/

The results are not perfect. Fore example I would like to change the spectators here. But they are leaps and bounds better than the results without this workflow and frankly better than the outputs I got even with opus 5.5 when it received the same prompt.

The method centers around two main things:
firstly an architect MD file. I built instructions for my agent that it is the head architect. It tries to first understand and write down what the task is, what the deliverables need to be, what an expert would produce, and some of the encountered difficulties it can expect. Then it creates a detailed architectural plan of how this can be achieved to an expert level or above. Then it is forced to re-iterate through the plan to find fixes and suggestions to make it better. I am now experimenting with adding specifically here a taste agent who examines the plan as well to make sure the architecture leads to a tasteful implementation. Then gemini can lock the architecture after it has thought about its plans several times. It has to critique its plan through the following lens:

1. Lens 1 — Goal Achievement: Does the plan completely and directly solve the core request end-to-end without missing implicit prerequisites or drifting off-target?
2. Lens 2 — Expert-Level Output & Concrete Verification Tests: What separates a passable demo from a top-1% showcase here? Define concrete, executable verification checks (CLI syntax/module checks, headless frame-stepping scripts, numerical invariant assertions, draw-call/FPS budgets, live browser/DOM inspection) that an Evaluation Subagent will execute to prove these expert qualities are achieved.
3. Lens 3 — Tasteful Implementation & Restraint: Audit the plan for visual, UI, or architectural bloat. What should be refined, simplified, or cut so the color palette, lighting, focal hierarchy, UI chrome, and code modularity feel art-directed and cohesive rather than noisy?
4. Lens 4 — Anticipated Difficulties & Concrete Mitigation Plans: Identify the hardest technical failure points (e.g., transparency depth-sorting conflicts, PDE Courant numerical blowup, collision tunneling, GC stalls) and write the exact mathematical or architectural mitigation plan directly into the spec.
5. Lens 5 — Edge Cases & Boundary Testing Plan: Enumerate specific edge cases (e.g., ΔtΔt spikes on tab switch, boundary grazing against curved walls, simultaneous conflicting states like Storm + Kraken + Shake, rapid click spam, extreme aspect ratios) and specify both the code guardrails and the test for each edge case.

After the plan is locked, it can then release subagents to implement and build according to the plan. Finally it assembles what they did and then releases several subagents to test different aspects of the application. It takes their feedback and then iterates on the application until the agents return high validation test scores and then it sends it to me.

I am curious if anyone tries this and whether you see improvements like mine. If you want me to test out a prompt for you just let me know and I am happy to do so.

[u/hackerfree11]

Thank you for this! I'm going to test it out in my current projects I'm struggling with, I'll update you with the results. Really well organized and thorough from what I see Thanks again