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I see a lot of founders add AI to give people a reason to use a feature. I don't think it works.
It usually ships before anyone decides which manual work the AI should take away. So it lands in a chat or a separate screen, and people can't see why it suggested what it did.
If they don't act on it, the feature the business case rests on goes unused, and fixing it means paying the team twice.
AI is leverage when it takes manual work out of a step people already do.
Before you build it, I like to ask:
→ Which part of the step is manual work, and which part is a decision?
→ Where do people already do that step?
→ What does the AI show so people can check it?
On a fintech platform's CSV import, Auto-match fills every column that fits one field, right in the mapping table. A column that fits two fields is a decision, so the person opens the cell and picks the "Best fit" field. Then they press Confirm.
When AI takes the manual work out of the step, people are more likely to act on it and get their data in.
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"High-Performance Creative Web Exploration"
A civic bureau seals your letter to 2126 under molten wax, witnessed. A civic bureau that seals letters for exactly one hundred years. Write a message to 2126, watch it set in wax, and receive your engraved certificate of deposit.
I built this project to test A civic bureau seals your letter to 2126 under molten wax, witnessed. A civic bureau that seals letters for exactly one hundred years. Write a message to 2126, watch it set in wax, and receive your engraved certificate of deposit. The core engineering challenge was sustaining uncompromised 60 FPS rendering using Canvas2D while handling continuous user interaction without framework overhead.
WHAT I WAS TESTING:
I focused on two core engineering benchmarks:
Precision implementation of wax-seal SVG under continuous interactive user input
Sustained 60 FPS render performance and zero-dependency browser execution
THE TECHNICAL SIDE:
Engineered directly in the browser with Canvas2D, Wax-seal SVG. The application runs without third-party frameworks or build-step dependencies, using hardware-accelerated rendering and custom event loops to achieve zero-latency response.
Everything executes in the browser using Canvas2D, Wax-seal SVG. No third-party frameworks, no heavy runtime bundles, and zero external tracking.
WHAT I LEARNED:
Balancing the mathematical rigors of wax-seal SVG with tactile browser interaction required tuning event throttling and memory allocation to eliminate all garbage collection stutters.
Finding the sweet spot between mathematical precision and frame budget took careful profiling, but the result runs at a steady 60 FPS even on modest hardware.
TRY IT YOURSELF:
The live build is deployed on Netlify. Open it in your browser, test the controls, and observe the render response times.
If you are building high-performance 3D, physics, or creative web systems and want to collaborate, reach out here on Contra.
Dynamic or static?
A procedural shaded-relief cartographer's table; export the map as PNG.
I built this project to test A procedural shaded-relief cartographer's table; export the map as PNG. The core engineering challenge was sustaining uncompromised 60 FPS rendering using Canvas2D while handling continuous user interaction without framework overhead.
WHAT I WAS TESTING:
I focused on two core engineering benchmarks:
Real-time topographic contour line extraction using Marching Squares
Mountain ridge carving and hydrographic river basin generation
THE TECHNICAL SIDE:
Combines domain-warped fractional brownian motion (fBm) with Marching Squares contour generation. Renders vintage parchment styled topographic maps with seeded coordinates.
Everything executes in the browser using Canvas2D, Procedural Cartography, Contour Line Marching Squares. No third-party frameworks, no heavy runtime bundles, and zero external tracking.
WHAT I LEARNED:
Contour line marching squares often generated disconnected micro-segments. Stitching adjacent line segments into continuous polyline paths allowed smooth canvas stroke rendering.
Finding the sweet spot between mathematical precision and frame budget took careful profiling, but the result runs at a steady 60 FPS even on modest hardware.
TRY IT YOURSELF:
The live build is deployed on Netlify. Open it in your browser, test the controls, and observe the render response times.
If you are building high-performance 3D, physics, or creative web systems and want to collaborate, reach out here on Contra.
Really nice map detail