https://www.tiktok.com/@theaiconsultinglab/video/7472894662848662830 https://console.anthropic.com/dashboard https://platform.openai.com/playground/chat?models=gpt-4o Did you know that both Anthropic and OpenAI have prompt generator tools that can save you probably 90-95% of time writing prompts for LLM's? *Disclaimer* you will need to create an account on their developer platform and fund it with $5, but there is no ongoing fee to access this platform, and the $5 will go a LONG way for creating prompts. Prompt engineering is important, there's no doubt about that, but the model companies are making more progress towards a world where it becomes less important. With every new model that comes out, the reliance on well structured and engineered prompts becomes less important because the models get better at understanding user intents. On top of that, we could start seeing some of these companies implement a type of workflow similar to this prompt generator tool, which translates your requests into well structured prompts automatically. You will still need to be able to diagnose and troubleshoot your prompts if they don't produce the desired result, but using these tools can save you a massive amount of time. For most of my use cases, I will typically use the Anthropic console to write my prompts, and it requires very little editing. Have you tried these tools out yet, if so, what are your impressions of the quality of the prompts they produce? #ai #chatgpt #aiconsulting #llm #deepseek #claude #openai

https://youtu.be/TfqioNAP1W4?si=BaUNulKcAGQq1axA In this video, I’ll show you the simplest method to equip your AI agents with tools in seconds, using nothing but natural language! With this approach, you can spin up advanced AI agents in minutes, allowing them to take action, retrieve data, and automate workflows effortlessly. Whether you're a beginner or more advanced, this method makes building AI agents easier than ever.

https://youtu.be/grc0YSEdUQY?si=NmKZDmR-SlUBWwIy 14 mins watching "How To Build Web Apps using V0 + Claude AI + Cursor AI" Handson. l tied this AI workflow to build a web app not bad !

UI-TARS is a next-generation native GUI agent model designed to interact seamlessly with graphical user interfaces (GUIs) using human-like perception, reasoning, and action capabilities. Unlike traditional modular frameworks, UI-TARS integrates all key components—perception, reasoning, grounding, and memory—within a single vision-language model (VLM), enabling end-to-end task automation without predefined workflows or manual rules. Useful Links: - https://github.com/bytedance/UI-TARS?tab=readme-ov-file - https://github.com/bytedance/UI-TARS/blob/main/README.md - https://sourceforge.net/projects/ui-tars-desktop.mirror/ - https://www.producthunt.com/posts/ui-tars-desktop -

https://astral.sh/ Useful Links: - https://docs.astral.sh/uv/getting-started/ - https://www.datacamp.com/tutorial/python-uv - https://www.mrcoder701.com/2024/08/04/how-to-create-python-virtual-environment-with-uv/ UV is a modern, high-performance Python package manager and installer written in Rust. It serves as a drop-in replacement for traditional Python package management tools like pip, offering significant improvements in speed, reliability, and dependency resolution. This tool represents a new generation of Python package managers, designed to address common pain points in the Python ecosystem such as slow installation times, dependency conflicts, and environment management complexity. UV achieves this through its innovative architecture and efficient implementation, making it 10-100 times faster than traditional package managers. Key features that make UV stand out: Lightning-fast package installation and dependency resolution Compatible with existing Python tools and workflows Built-in virtual environment management Support for modern packaging standards Reliable dependency locking and reproducible environments Memory-efficient operation, especially for large projects Whether working on small personal projects or managing large-scale Python applications, UV provides a robust and efficient solution for package management. In this tutorial, we will cover all essential aspects of UV so you can start using it immediately. #browser_use #computer_use #astral #uv #python_package_manager

https://youtu.be/E05tO8ic45E?si=9oBYRCL5G8_Y7QgW Ultimate Guide to Building and Automating with DeepSeek R1 - Game Development, Web Projects & More In this comprehensive tutorial, learn how to utilize DeepSeek R1 to build and automate a variety of projects, from games to websites. Starting with chat.deepseek.com, users can create diverse applications with a single prompt. This video covers running DeepSeek R1 locally via Olama for faster and offline usage, and exploring multiple models for varying performance. Additional tools like Bolt DIY and Make.com are demonstrated for creating useful applications and automating workflows. Discover how to seamlessly integrate DeepSeek R1 into different environments, including browser web UIs for advanced automation. Whether you're developing complex apps or seeking to enhance productivity, this guide provides all the steps and insights needed to master DeepSeek R1.

https://databutton.com/ Work with AI to build the app you need, whether it's a SaaS product or a complex internal application. Ship your idea in days, not weeks, with Databutton: the world's first fully AI app developer. Databutton acts as your app developer – Databutton is able to take your requests and turn them into plans, research, and finally app code. You are still in the cockpit, though, and need to provide your vision and expertise in order to build the right apps. Databutton specializes in building AI applications – whether it is a chat experience on a knowledge base, an AI workflow tool to speed up processes, ways to add more personalization to communications, or more. Apps built with Databutton are full-stack, with React as the frontend and Python (FastAPI) backends. If the app isn't exactly as you want it, you have full access to the code editor to directly manipulate the app's look, feel, and functionality.

https://www.freecodecamp.org/news/learn-generative-ai-in-23-hours/ Artificial Intelligence is revolutionizing industries and workflows, and learning to work with AI in the cloud is an important skill for modern developers. Whether you're a beginner or looking to deepen your understanding of generative AI, this course is your all-in-one guide to mastering the development lifecycle of AI systems.

https://n8n.io/ n8n is a free and open node-based Workflow Automation Tool. It can be self-hosted, easily extended, and used with third party web applications or custom in-house tools to automate repetitive tasks. With n8n, for the first time, people can move beyond simple integrations to build multi-step workflows that combine both 3rd party APIs and your own internal tools to create easy to use automations that snap together all the pieces of what would otherwise be very complex, disconnected systems. n8n is headquartered in Berlin and was founded by Jan Oberhauser in 2019. Useful Links https://youtu.be/XQPUnVEvh10?si=bTCEwibKtYlNExAf https://youtu.be/UwemeU5uKXM?si=J6yCmyNR3wjg-gaT

Smithery [https://smithery.ai/ ] is a registry of Model Context Protocols, designed to help developers find the right tools to build their AI agentic applications. Smithery addresses this challenge by providing: A centralized hub for discovering model context protocols Standardized interfaces for tool integration and configs Easy-to-use resources for agent development Community-driven protocol sharing and collaboration Model Context Protocol The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLMs and external data sources and tools. It is a universal standard for connecting AI systems with the context they need, eliminating information silos and fragmented integrations. By providing a standard way to connect AI systems with data sources, MCP simplifies the development and maintenance of agentic applications. This makes it easier to build agents like intelligent IDEs, chat interfaces and custom AI workflows. Instead of writing custom implementations for each new data source, developers can use MCP as a single, standardized protocol. This approach not only makes systems more maintainable but also ensures better scalability as your AI applications grow and evolve.

https://systemprompt.io/ Systemprompt.io is a Rest API built to automate your AI workflow by providing tools for creating, refining, and managing AI prompts. Our platform streamlines automation workflows, integrates sophisticated prompt engineering techniques, and maximizes reusability across AI systems.