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Awesome Prompts (ai-boost)

Updated Jul 7, 2026

Awesome Prompts by ai-boost is a curated, engineering-biased prompt resource covering copy-paste prompts (coding, DevOps, AI/ML, product, legal, healthcare, writing), prompt engineering frameworks (DSPy, promptfoo, TextGrad, Guidance), system prompt leaks, agent ecosystem references, and 100+ research papers on LLM reasoning, RAG, and safety.

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What it does

  • Prompts section — 20+ topic categories

    Copy-paste prompts for coding, DevOps, data engineering, AI/ML, product, healthcare, legal, and more — all open, click and copy.

  • Frameworks section — Prompt Programming

    Covers DSPy (compile LM programs), TextGrad (automatic prompt optimization), promptfoo (eval & regression testing), and Guidance (structural generation control).

  • System Prompt Leaks section

    Collected leaked system prompts from real production AI products — useful for understanding what prompt patterns deployed systems actually use.

  • Papers section

    100+ research papers on LLM foundations, optimization, reasoning, RAG, agents, multi-agent systems, safety, tool use, evaluation, memory, and multimodal — organized by topic.

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OVERVIEW.mdprimary · markdown · 2.3 KB
## What it does

Awesome Prompts by ai-boost is a curated, engineering-biased prompt resource that covers both prompt templates and the "prompt as engineering" camp. The project explicitly separates the two: prompt templates (copy-paste recipes) and prompt engineering (compiling LM programs, testing and regressing prompts, optimizing prompts automatically).

Copy-paste ready prompts span: Coding & Development, DevOps & SRE, Data Engineering, AI & ML, Product & Strategy, Project Management, Healthcare & Clinical, Industrial & Automotive, Legal & Compliance, Knowledge & Documentation, Writing & Academic, Learning & Education, Research & Analysis, Productivity & Tasks, Safety & Compliance, Meta & Prompt Engineering, Image/Video/Audio Generation, Creative & Role-play, Game Development, Translation, and Legacy 2023-era prompts.

The Frameworks section covers the engineering camp: Prompt Programming (DSPy for LM program compilation), Automatic Prompt Optimization (TextGrad, GEPA), Eval & Testing (promptfoo), Red Team & Security (adversarial prompt testing), and Low-Code & Workflow Platforms. The System Prompt Leaks section collects leaked production system prompts from real products — useful for studying what prompt patterns deployed AI systems use. The Papers section covers 100+ LLM research papers organized into Foundations, Optimization, Reasoning, RAG, Agents, Multi-Agent, Safety, Self-Improving Agents, Tool Use, Evaluation, Memory, and Multimodal.

## Install / access

Repository: https://github.com/ai-boost/awesome-prompts

Browse sections on GitHub and copy the relevant prompts directly. No install required. The repo is best used as a reference and discovery resource rather than a structured workflow tool — it indexes and links rather than providing self-contained installation.

## When to use

Use this when you want a curated starting point for prompt engineering techniques, frameworks, or research — particularly if you are building AI-powered features or tools and need to understand what the current prompt engineering landscape looks like. The System Prompt Leaks section is genuinely useful for learning production prompt patterns. For structured, workflow-ready prompts, the /prompts section is useful but not as deep as role-specific libraries like useful-ai-prompts or product-manager-prompts.