Date: 2026-02-11
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| # OpenClaw Implementation Prompts | |
| Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter. | |
| --- | |
| ## 1) Personal CRM Intelligence | |
| ``` | |
| Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach. |
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| """ | |
| The most atomic way to train and inference a GPT LLM in pure, dependency-free Python. | |
| Differences from GPT-2 are minor: rmsnorm instead of layer norm, no biases, square ReLU instead of GeLU nonlinearity. | |
| The contents of this file is everything algorithmically needed to train a GPT. Everything else is just efficiency. | |
| Art project by @karpathy. | |
| """ | |
| import os # for os.path.exists | |
| import math # for math.log, math.exp | |
| import random # for random.seed, random.choices |
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