Transformer Primitives – A visual explainer you can send to anyone

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I have had a few conversations in the past year with non-technical folks (traditional finance types, consultants) who asked for a simple explainer on how GPTs work. These people generally have the horsepower to grasp new concepts quickly but don't necessarily have the math background to dig in super deeply and want a stronger framework than "they predict words". I had generally been pointing them to Karpathy, Illustrated Transformer, and other youtube content but I figured something more hands on without the math requirement might be better at explaining questions like "why matrix multiplication?". I built this as a simple 60-70 minute interactive course with some demos I could send along to them. I've found it effective as the initial foray into understanding jargon and concepts before they graduate to Karpathy et al. It's free, no signup required. I would love feedback on where it might lose a non-technical reader, and where someone who does this for a living thinks I have simplified past the point of being correct. understandgpt.xyz

Visit product View on Hacker NewsJun 23, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, visual, plain · Missing: mac, agents, macos

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

63%63% 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

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

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