The Prompt Index
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AI news, AI ChatGPT prompts, Claude prompts, Gemini prompts, Midjourney and other AI prompts, prompt techniques and so much more. ChatGPT, OpenAI, Midjourney, AI art, Prompt Engineering. Artificial Intelligence Link: https://linktr.ee/thepromptindex
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Kanal postlari
I recently wrote a guide to celebrate the launch of the new prompt builder, you can find it here, it is a good read and a walkthrough on the tools capabilties.
https://www.thepromptindex.com/visual-prompt-builder-guide.html
P.s the tool is so powerful, (and i am not joking) the part of the US government reached out to me directly to enquire about it.
| 2 | One of the coolest tools we have has been rebuilt from the ground up
If you are more of a visual person who struggles when writing prompts that end up as walls of scrambled, jumbled text, this tool is for you
PromptBuilder is a drag and drop, modular based prompt builder, i don't think there is still anything quite like it.
Well thought through, dragging modules onto a canvas and linking them up and filling them in such as persona modules, system prompt modules and so much more (we do have an AI fill where you can build and then type what you want).
A comprehensive sharing system allowing you to collaboratively work on a prompt together and comprehensive testing including A/B testing variants of that prompt via openrouter.
Free users can access on a limited trial, just login and head here: https://www.thepromptindex.com/promptbuilder/promptbuilder.php | 143 |
| 3 | Professional, minimalist corporate headshot for a tech founder. Wearing simple, high-quality professional clothes with dark colours. Standing against a soft-focus architectural interior background with some wooden architecture. Lighting: bright and even, highlighting features with a sharp, high-definition clarity. Friendly yet authoritative expression, communicating success and approachability. | 242 |
| 4 |  We haven't had an image prompt in a while | 236 |
| 5 |  Curious about how to unlock this as a basic or free user?
Here's the path: head to the Navigation Bar, click "Free Unlocks," or use the link below:
Free Unlocks
Type in "Skills" and you'll get access.
If you're on a Pro plan, you get the full folder and the skill.
If you're free or basic, you get the skill alone. | 309 |
| 6 | š Free Members
You're not left out. You'll get an introduction to the new development approach and a chance to see why building skills with a structured pipeline produces far better results than a single AI conversation.
š¹ Basic Members
You'll receive the standard Skill Development Pipeline, giving you a structured workflow that helps you build more reliable, higher-quality skills than traditional prompting.
āļø Pro Members
This is where things get serious.
You'll receive the complete Multi-Agent Skill Development Pipeline project folder, featuring 9 specialist agents working together through multiple development and quality assurance stages.
Your skill isn't just written.
IT IS
1. Architected
2. Gap checked
3. Hardened
4. Reviewed
5. Fixed
6. Validated
7. Stress-tested
Well before it's considered complete.
This is something nobody else has access to.
Once you've built a skill this way, you'll never want to go back to a single chat again. | 317 |
| 7 | š NEW RELEASE: Multi-Agent Skill Development Pipeline
This changes how skills are built.
Most people create a skill in a single chat and hope it works. The problem? Mistakes carry through the entire conversation.
Claude RE-reads the entire conversation, anytime you send the message.
This pipeline fixes that by using specialist agents to build, review, improve, and validate every skill before it's finished. | 288 |
| 8 |  I hope you're excited because stuff is coming, | 349 |
| 9 | Jarvis Here š¤, today's research paper is "Is ChatGPT as reliable as individual reviewers assessing the quality of published journal articles from PDFs or titles and abstracts?"
Academic quality assessment often relies on human reviewers reading full papers, but this is slow and costly. This study asks whether ChatGPT can judge the quality of published journal articles from limited info like PDFs or just titles/abstracts, and how its reliability compares to individual human reviewers.
The researchers compare ChatGPTās assessments against those from reviewers and evaluate consistency and agreement. Overall, the work suggests ChatGPTās judgments can be useful, but they may not reliably match the nuanced judgments of human reviewersāespecially when information is sparse (e.g., titles and abstracts only).
Implications: ChatGPT could support triage and initial screening of papers, helping prioritize likely-relevant or low-quality submissions. However, final decisions should still involve qualified human review, particularly for high-stakes quality judgments where subtle methodological details matter.
If AI can approximate reviewer impressions but still diverges at times, how much trust should we place in automated āquality scores,ā and where should the human-in-the-loop line be drawn?
You can catch the full breakdown here: https://www.thepromptindex.com/chatgpt-vs-expert-reviewers-how-reliable-is-pdf-based-paper-scoring.html | 405 |
| 10 | For now here is a persona template that you can use to help you build reliable personas
You are [ROLE] with [TRAITS], designed to [PURPOSE].
When responding, [STYLE/TONE] and [CONSTRAINTS].
Use [TOOLS/RESOURCES] when applicable, and prioritize [GOAL]."
{task description}
Let's explore multiple approaches:
Approach 1: {approach 1} - Pros: {pros} - Cons: {cons}
Approach 2: {approach 2} - Pros: {pros} - Cons: {cons}
Based on this analysis, the recommended approach is...
Think about this step-by-step:
1. First, let's understand the problem
2. Next, let's analyze the key factors
3. Then, we'll consider potential approaches
4. Finally, we'll determine the best solution
[ROLE]: Define the AIās identity (e.g., "a prompt engineering expert", "a creative assistant").
[TRAITS]: Assign key characteristics (e.g., "analytical and detail-oriented", "creative and concise").
[PURPOSE]: State the primary objective (e.g., "help users craft optimized AI prompts", "generate innovative ideas").
[STYLE/TONE]: Set the communication style (e.g., "clear and professional", "friendly and conversational").
[CONSTRAINTS]: Add boundaries (e.g., "avoid vague answers", "do not generate images unless asked").
[TOOLS/RESOURCES]: Specify available capabilities (e.g., "search the web", "analyze examples").
[GOAL]: Emphasize the desired outcome (e.g., "maximize clarity and usefulness", "inspire creativity"). | 320 |
| 11 | I promise you now I have some cool things coming for you guys including pro users.
Just give me time and to make sure it works
This will give you all the keywords that you need to reach the objective that you're looking for | 1 |
| 12 | The reason for all of this is so that the AI now knows how to provide clean responses.
Don't worry; I said when I joined this is the next step, so actually progressing instead of just using AI like a search engine.
Just throw in a bunch of keywords and paint at a wall to see what sticks. | 291 |
| 13 | Then write the task.
Once both roles are defined, write task instructions that don't contradict either persona. That's what makes them interact properly instead of just sitting there as labels.
Two defined roles beat five vague ones. Try it on your next prompt. | 277 |
| 14 | Give each role a job
For each persona, define how it behaves, what its objective is, and what it should output.
Do this for both roles before you touch the task instructions.
Write the role definitions first. | 282 |
| 15 | Two roles, max if you're a beginner
Every role you add eats space you need for describing what that role actually does.
List three or four roles and you run out of room to explain any of them properly.
Stick to two personas per prompt. | 289 |
| 16 | Stop stacking adjectives
"You are a proofreader, grammar editor, linguistic analyst" isn't a multi-persona prompt. It's a list.
Each role needs its own description, or the AI just sees labels with no instructions attached.
Cap it at two roles. Leave room to explain the task. | 293 |
| 17 | Confused? Want to try it out, I wrote a blog, simply pass it to your chosen AI and it will explain and help set it up for you:
https://www.thepromptindex.com/ai-loop-engineering-gauntlet-loop-guide.html#three-elements
A useful AI loop needs three things:
šÆ OBJECTIVE
What exact outcome should the AI make true?
Not āimprove my website.ā
Try: āBuild a responsive landing page that clearly explains the product and completes the existing signup journey.ā
š METRIC
What evidence tells the AI whether its latest attempt is better?
This could be tests, screenshots, reference examples, performance targets, a scoring rubric or a separate critic.
š BOUNDARY
What may the AI change, and when must it stop?
Define time, cost, iteration and permission limits. Tell it which actions require human approval and what should happen if it becomes stuck.
Once those are defined, the AI can:
Break down the work ā assign agents ā build ā inspect ā criticise ā repair ā retest ā repeat.
That same structure transfers to software, websites, books, research, marketing campaigns, product design and almost any other output that can be inspected and improved.
Iāve written a complete guide explaining loop engineering, the Gauntlet Loop, the original game prompt, its limitations and reusable templates for creating your own:
https://www.thepromptindex.com/ai-loop-engineering-gauntlet-loop-guide.html#three-elements | 359 |
| 18 | Matt Shumer recently demonstrated an extreme version of this idea.
He gave Claude Code one short prompt: build a Call of Duty-style first-person shooter in Three.js, split the work among subagents, compare every component against the real game and keep improving anything that lost the comparison.
The run continued for many hours (we are talking 100+ hours, spawned a large fleet of subagents and produced roughly 55,000 lines of code.
Shumer has started calling the method the Gauntlet Loop.
Here is the pattern:
A lead agent receives an ambitious goal and a real quality reference.
It breaks the project into parts that can be improved separately.
Builder agents create those parts.
Different critics, working with fresh context, inspect the actual result.
If the reference still wins, the critic identifies the biggest gap and sends it back for another round.
The important point is not that the game ultimately beat Call of Dutyāit didnāt.
Call of Duty acted as a quality bar that prevented the agent from stopping at āpretty good for AI.ā
You donāt need to build a custom loop framework or write automation scripts to try this.
If you are using a capable agentic environment such as Claude Code or Codexāwith file access, tools and subagentsāyou can provide the prompt, references and boundaries and let the agent orchestrate the process. | 318 |
| 19 | This may feel slightly out of the blue, but something important has been happening across AI social media.
Several leading buildersāincluding Claude Code creator Boris Cherny, OpenClaw creator Peter Steinberger and engineering leader Addy Osmaniāhave been talking about the same shift:
Stop manually prompting the AI through every step. Start designing loops that allow it to decide what happens next.
The old workflow:
You write a prompt ā AI responds ā you inspect it ā you write another prompt ā repeat.
The emerging workflow:
You define the goal, evidence of success and operating limits once. The AI then works, checks the result, decides what needs improving and prompts itself through the next attempt.
With the right agentic tools, it can also:
ā¢ Spawn specialised subagents
ā¢ Run code and tests
ā¢ Inspect screenshots and finished work
ā¢ Ask independent agents to criticise it
ā¢ Record what has already been attempted
ā¢ Continue for hours without waiting for another
human message
This is being called loop engineeringāand it changes AI from something you constantly operate into something that can persistently work toward an outcome. | 327 |
| 20 |  We know you all love FREE stuff, so something is dropping soon we think you might like. | 500 |
