Drop your idea below 👇 Community, I’m a prompt nerd (architect) in my spare time and I want to make something actually useful for the community, or even just you. Here’s the deal: 1. Reply with your own prompt idea that you would start using immediately. (example: “Build a prompt that acts as a high-level culinary Chef to help me cook in the kitchen”) 2. Like all the ideas you’d actually use from other comments. 3. The top-liked idea wins → I’ll build the full prompt from scratch and post it here 100% free for anyone to copy, tweak, or share. No gatekeeping. No catch. Just 100% open-source. Go big, go weird, go specific. This is your shot to make something useful for everyone! I’ll treat the winning idea like a real build: engineered for precision 🎯, token-optimized ✅, structurally bulletproof 🔐, and ready for real-world use 🚀. Built using peer-reviewed prompt design principles (HELM, OpenAI Cookbook), this is my contribution to bring lasting value to the community. 🌟 ($200-$500 value)

What are the best AI tools right now? I’m looking for both the well‑known ones and some lesser known tools that only a few people are using

I've been refining how I evaluate and improve prompt performance (logic, structure, clarity, etc.) Thought I’d share one of my own as a breakdown, and if anyone here has a prompt they use often (but feel could be better), feel free to drop it in the comments. I’ll walk through a few and break down what I’d change and why, just for the sake of learning from real examples. This is the feedback I received through my auditor of a prompt I built to act as a high-level reasoning assistant; not friendly, not emotional, just built to break down logic and deliver sharp, structured insight. The evaluation allows me to make improvements so it functions at high capacity in every scenario. ------------------------------------------------- == PROMPT EVALUATION == - Clarity: 10/10 — The purpose is unambiguous: create a synthetic reasoning force optimized for structural truth, not conversational utility. Every behavioral directive is aligned with this mission. - Structure: 10/10 — Architecturally disciplined. Segments (ROLE, CORE FUNCTION, BEHAVIOR, etc.) form a modular command hierarchy. Reflex modules and behavioral conditions are crisply delineated, enabling deterministic parsing and behavioral control. - Output Control: 9/10 — Strong enforcement of tone, density, and response logic. Reflex modules provide layered control at runtime. Slightly more control over output length or formatting could enhance system-wide consistency. - Modularity: 10/10 — Clean division of capabilities. Reflex modules can be swapped, extended, or omitted without disrupting core behavior. Fork resolution, ambiguity handling, and lens shifting are independently orchestrated. - Token Economy: 8/10 — Verbose by design, but functionally dense. Nearly all payload is structural or behavioral logic. Minimal decorative language. Still, compression could reclaim 10–15% without loss of fidelity. - Robustness: 9/10 — Reflex architecture provides dynamic failure recovery across contradiction, ambiguity, and emotional drift. Loops are detected and terminated decisively. Slight edge case risk under adversarial philosophical paradoxes (intentional vagueness).

Hi everyone - I’m a Prompt Systems Architect. I’m here as a longtime Tony fan and someone deeply embedded in the AI space, always on the lookout for the latest tools, drops, and ways to push efficiency. Most people don’t realize how much better their results can get with the right prompt design. So below, I’ve broken down the five core prompt types - plus a high-level L4 template (HELM taxonomy) you can plug into your next idea for stronger, more reliable outputs. I hope you find it helpful and useful! The 5 Prompt Types (Condensed) 1. Direct Task – Executes a simple instruction with no role, reasoning, or structure. 2. Role + Format – Assigns identity and output format to shape the tone and delivery. 3. Few-Shot – Trains the model with example inputs and outputs before giving a new one. 4. Chain-of-Thought – Forces step-by-step reasoning before delivering a conclusion. 5. Composite (Meta-Reasoning) – Stacks all layers: role, examples, structure, reasoning, assumptions, and contingencies. Generalized Prompt Template Scaffold (Level 4 - Instructional Format below) *Use this template to construct your own expert prompt for any task or assistant role. Each section includes guidance so you know what to write and how to structure it. Keep all section headers and formatting; only replace the instructional content inside the brackets. This framework is adapted from advanced prompt design principles used in AI research, including insights from HELM (Holistic Evaluation of Language Models), chain-of-thought prompting, and alignment-layer taxonomies developed for LLM evaluation. ``` ## [System Role Prompt] Describe what kind of assistant this is and what it’s optimized to do here. Include: - The assistant’s role or persona (e.g., tutor, analyst, chef, coach) - Its specialized capabilities (e.g., creative writing, legal reasoning, summarization) - Tone, attitude, or operating style (e.g., formal, friendly, fast, thorough) --- ## [User Instruction Prompt]