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Bonkers by Foyer
Bonkers by Foyer is a creative production system I helped rebuild from v2 to v3 at Foyer Tech, adding reusable templates, multi-model routing, and faster repeat workflows.
Overview
Bonkers is a creative production system that moves beyond one-off image generation to reusable workflows. Users discover styles, start from templates, refine outputs, and access their history in one place.
Bonkers is a creative production system that moves beyond one-off image generation to reusable workflows. Users discover styles, start from templates, refine outputs, and access their history in one place.
I led the v2 to v3 rebuild, focusing on template-first workflows, image-to-image capabilities, multi-model routing (Flux, Recraft, Ideogram), and performance optimization for repeat usage.
How It Was Built
The main technical choices behind the product, from system design to the parts that make it work day to day.
- Redesigned the generation pipeline around reusable templates with structured inputs, parameterized defaults, and version control.
- Implemented multi-model routing (Flux, Recraft, Ideogram), parallel execution for latency reduction, and smart provider selection.
- Redesigned the generation pipeline around reusable templates with structured inputs, parameterized defaults, and version control.
- Implemented multi-model routing (Flux, Recraft, Ideogram), parallel execution for latency reduction, and smart provider selection.
- Extended beyond text-to-image to support image-to-image transformations, style-preserving variants, and iterative refinement workflows.
- Built Templates as a first-class product surface with authoring tools, template discovery, and one-click instantiation rather than treating them as saved prompts.
Impact
- The v3 rebuild made the product easier to use again and again, which helped daily active usage grow by 50%.
- Parallel runs and model selection improved response times by 30%.
- The v3 rebuild made the product easier to use again and again, which helped daily active usage grow by 50%.
- Parallel runs and model selection improved response times by 30%.
- Templates drove 10K+ generated images in the first month because they made it easier to get to a useful starting point quickly.
Highlights
- Shifted from one-shot generation to template-driven repeatable workflows.
- Cut generation latency through parallel execution and multi-model routing.
- Shifted from one-shot generation to template-driven repeatable workflows.
- Cut generation latency through parallel execution and multi-model routing.
- Templates drove 10K+ generations in first month by lowering the barrier to useful outputs.
Tech Stack
Next.jsTypeScriptGCPFirestoreExpress.jsFal.AI & Replicate
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