This week’s featured collector is kkamauu
Kkamauu is a prolific collector of Ethereum NFTs. Check out their picks at lazy.com/kkamauu
Last week’s EIP-8141 poll split evenly between paying gas with stablecoins and multisig security without wallet migration, each taking 50% of the vote, while batching transactions, private mints and bids, and “something else” all came in at zero. The takeaway is telling: our readers aren’t most excited about convenience features like fewer clicks — they care about the practical economics of collecting (not having to hold ETH just to transact) and protecting what they already own (adding multisig security without the risk and hassle of migrating assets to a new wallet). These are both pain points that collectors live with today and have largely just accepted as the cost of doing business on-chain, so it makes sense they’d be the features that land hardest once EIP-8141 arrives.
A Generative Artist’s Vocabulary, Built One Algorithm at a Time
One of the things we find most valuable as NFT art observers is when artists pull back the curtain on how their practice actually develops — not the polished origin story, but the messy, incremental version. Generative artist Veit Heller recently did exactly that in a personal blog post, tracing his journey from 2016 to now across roughly 114 sketches. Heller isn’t an NFT artist — his practice lives on p5js and personal canvases, not on-chain — but his reflections on how a generative art vocabulary develops over time are deeply relevant to anyone collecting or following the NFT generative art scene.
It starts where a lot of generative art journeys start: with math. Phyllotaxis spirals, trigonometric functions, golden angles. Thirty lines of code producing sunflower patterns. Heller describes this early phase honestly — he was a programmer first, choosing formulas rather than making aesthetic decisions, and whatever the algorithm produced was the work. The results were beautiful in a clean, illustrative way, but they felt more like demonstrations than expressions.
The shift happened gradually. Boredom with pristine mathematical output led to an interest in texture — simulated brush strokes, particle systems mimicking fur or hair, flow fields chosen not for their novelty but for the rich surfaces they could generate. This came alongside what Heller calls his “greyscale period,” where avoiding color was partly aesthetic preference and partly a way to dodge decisions he didn’t feel ready to make. A useful constraint, in retrospect, even if it lasted longer than it needed to.
Then came a quieter revelation: lines, layered densely enough, stop reading as lines and start reading as surfaces. Enough geometric primitives with enough intention can evoke physical materials without simulating them. That insight opened a door. Instead of asking “what does this algorithm look like?” Heller began asking “can I make this look like watercolor?” — working backward from a felt memory of how a medium behaves to the math that might approximate it.
Over time, a small library of simulated materials accumulated: watercolor washes, dry brush, felt-tip pen, cracked glaze, pencil fill. None physically accurate, all convincing enough to carry emotion. Each one taught something. Watercolor taught layering and transparency. Brush strokes taught pressure and variance. Cracked glaze taught that imperfection has its own structure.
Color remains Heller’s self-described weak point — no formal theory, just a slowly growing intuition built through looking, testing, and failing. But comparing recent work to that first phyllotaxis spiral makes the distance visible. The algorithm is still present, but it’s in service of composition, texture, and intent rather than being the point itself.
What resonates most for us is Heller’s framing of all these accumulated techniques as a “vocabulary.” Each algorithm learned, each material simulated, each failed color experiment becomes something available to reach for later. The question evolves from “what can I do?” to “what do I want to say?” — not dramatically, but meaningfully. The tools recede, and something like a personal aesthetic starts to emerge.
That’s a trajectory worth paying attention to as collectors, even when the artist in question has no connection to the NFT world. The generative artists producing the most compelling on-chain work right now aren’t the ones with the most sophisticated algorithms. They’re the ones who’ve spent years building a vocabulary and have started using it to say something. The code is the medium, but the art lives in the accumulated decisions about what to do with it. Heller’s essay is a clear window into what that accumulation actually looks like from the inside.
This post is based on Veit Heller’s Generative Art Over the Years.
Poll: What matters most to you in generative art?
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