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... 16:5
This Simple AI System Changed My Life!

Jeff Su

1+ months ago 11K views

AI users thrive by integrating AI tools into daily workflows through simple, effective systems. This video presents a method for creating a prompts database in Notion to streamline AI interactions, save time, and maintain an organized workflow. By capturing and tagging AI prompts efficiently, users can revisit them during weekly reviews to enhance their productivity and ensure accessibility. The guide emphasizes the importance of optimizing AI interactions for various professional needs, enabling users to harness AI capabilities effortlessly, regardless of their technical skills.
03:24 - 03:32

Utilizing templates ensures efficient addition to the prompts database.

Text generation Education
... 9:15
PasteMax + FREE Grok-3, Claude, O3 : This OPENSOURCE AI Coder IS KINDA AMAZING!

AICodeKing

1+ months ago 9K views

Repo Prompt allows users to copy code contexts from projects and integrate them into chat interfaces like ChatGPT, enabling efficient code modifications. While Repo Prompt has paid features and is not open source, an alternative called Paste Max offers similar functionalities for free. Paste Max enables users to browse directories and manage file content for use with AI tools, streamlining the coding process. The video also highlights Dart AI, an effective project management tool that leverages AI for task management and collaboration. Clear instructions on running Paste Max locally and utilizing it with AI models are provided.
02:26 - 03:36

Dart AI enhances project management through AI-driven task automation and collaboration.

Machine Learning Tech & Hardware
... 26:52
DAY-2 | AI Assisted DevOps | Prompt Engineer Explained In 30 Minutes

Abhishek.Veeramalla

1+ months ago 3K views

Prompt engineering is crucial for optimizing AI model outputs, particularly in DevOps environments. This entails enhancing user inputs—called prompts—to elicit desired results from AI models. Different prompting techniques, such as zero-shot, few-shot, and multi-shot prompting are explored, highlighting their practical applications in real-world scenarios. Effective prompting can significantly reduce costs associated with AI model utilization. By providing structured and specific prompts, users can achieve outputs that align closely with organizational requirements, thereby streamlining workflows and maximizing productivity in AI-assisted DevOps tasks.
05:24 - 05:30

Cost optimization in organizations can be achieved through effective prompting.

Machine Learning Education
... 22:7
Build AI AGENTS 3x Faster with this Prompt Agent

Simon Scrapes | AI Agents & Automation

1+ months ago 2K views

Build AI agents three times faster with an effective prompting agent, simplifying the complex and time-consuming process of writing prompts. Through a template, the method streamlines prompt creation, ensuring comprehensive outputs that reduce rework and enhance productivity. By answering targeted clarification questions, a user can refine a broad prompt into a detailed, functional instruction set for an AI agent. This structured approach not only speeds up the prompt-building process but also increases the quality of outputs, resulting in more efficient AI solutions tailored to specific tasks.
04:20 - 05:10

Generating prompts tailored to specific tasks improves overall AI output quality.

Machine Learning AI Startups
... 26:29
Google AI Studio in 26 Minutes

Tina Huang

1+ months ago 15K views

Google AI Studio is a powerful tool for building applications and enhancing productivity through AI. The interface may seem overwhelming at first, but it unlocks numerous possibilities once users become familiar with its features. The video covers effective prompt engineering techniques, emphasizing the importance of system prompts for guiding AI behavior. Key features include real-time interaction, model comparison, and streamlining code execution. The speaker presents a framework for constructing high-quality prompts, enabling better results in AI-generated outputs. The session concludes with insights on the role of tutorials and detailed interactions with AI.
09:50 - 10:02

Discussion on the high context window for video analysis in AI.

Google Machine Learning Education
... 4:34
The Top AI Prompt Writing Tips You Must Know About

Bernard Marr

1+ months ago 2K views

Creating effective AI prompts relies on context, role assignment, and structured formatting. Clear directives increase AI output quality, with techniques like demonstrating styles and limiting output parameters. Adjusting creativity levels based on task type and using iterative design produces better results. Effective prompts include context, specific roles, explicit goals, stylistic guidance, and exclusions. Constant refinement and attention to AI reasoning enhance the development of high-quality AI-generated content.
01:23 - 01:26

Using examples to illustrate style improves AI writing quality.

Natural Language Processing (NLP) Education
... 12:31
You’re Overpaying for AI Coding | Roo Code System Prompt Override

GosuCoder

1+ months ago 4K views

The video discusses the effectiveness of a new prompting system in AI tools, focusing on how altering system prompts can significantly reduce token usage and costs when coding. Specific examples, such as debugging a Tetris game and cleaning up code in a repository, highlight improvements in efficiency and cost-effectiveness. By customizing prompts to fit unique needs, substantial savings can be achieved, demonstrating the potential for fine-tuning AI tools for particular applications and enhancing user experience with coding assistants.
03:00 - 03:05

Significant reduction of token usage shown through practical examples.

RooCode Machine Learning Education
... 23:54
This new AI prompting technique REDUCES token usage SIGNIFICANTLY

GosuCoder

1+ months ago 3K views

My company utilizes numerous API calls to OpenAI and Claw, primarily for building prompts. Encountering challenges during prompt creation led to the investigation of Chain of Draft, which focuses on optimizing thought processes for enhanced results with local models. This approach demonstrates that prompt engineering can both reduce costs and improve accuracy. Various experiments, including a standard house problem and a math problem, reveal trade-offs in token usage and accuracy across different models, ultimately showcasing the value of careful prompt design in leveraging AI models effectively.
01:51 - 02:19

Testing Chain of Thought shows a trade-off between tokens used and answer accuracy.

Natural Language Processing (NLP) Education
... 23:54
This new AI prompting technique REDUCES token usage SIGNIFICANTLY

GosuCoder

1+ months ago 3K views

My company utilizes numerous API calls to OpenAI and Claw, primarily for building prompts. Encountering challenges during prompt creation led to the investigation of Chain of Draft, which focuses on optimizing thought processes for enhanced results with local models. This approach demonstrates that prompt engineering can both reduce costs and improve accuracy. Various experiments, including a standard house problem and a math problem, reveal trade-offs in token usage and accuracy across different models, ultimately showcasing the value of careful prompt design in leveraging AI models effectively.
01:51 - 02:19

Testing Chain of Thought shows a trade-off between tokens used and answer accuracy.

Natural Language Processing (NLP) Education