Doodlea.day – A daily step-by-step marker drawing lesson

Hacker News

Several weeks ago, I wanted to draw a cowboy hat for a handmade birthday card, so I used ChatGPT to create a drawing tutorial for me. It was impressive how well the image generation was able to break down the end result into a step-by-step lesson, and this led to the idea of creating a daily AI-generated drawing lesson website. Doodlea.day is that. A fresh drawing lesson published most days. I've had some challenges keeping the lessons cumulative. For example, in the first few steps, a character's eyes might be looking to the right, but then in the last three steps the eyes swap to looking to the left. I've been tweaking the prompt and guidance to the point where most lessons are one-shot these days. All of the steps are generated together in a single contact sheet rather than one image at a time. Each panel has a controlled job, like silhouette, contour, features, detail, and finish, and there is a validation process that identifies and rejects broken lesson panels. The project is at a place where I am excited to share it. Taking a little time every day with the family to draw has been a great experience, and I hope others can find the same joy.

Visit product View on Hacker NewsJul 30, 2026

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, single · Missing: mac, agents, macos

52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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