I DUMPED ChatGPT for This AI NEW Model (Itβs So MUCH Better)
TLDRThe speaker shares their experience switching from Chad GPT to a new AI model, CL 3.5, due to its superior performance in coding tasks and unique features like real-time code execution previews. They demonstrate creating SVG art, JavaScript animations, and custom Flutter widgets using the model's chat interface and backend API, showcasing its efficiency in generating and executing code snippets. The video also includes a proof-of-concept app built with Flutter Flow, utilizing the new AI for a chat interface, highlighting its potential for no-code app development.
Takeaways
- π The video discusses the creator's transition from using Chat GPT to a new LLM (Large Language Model) that they find more effective for their specific needs.
- π The creator has been using Chad GPT since its inception but started feeling underwhelmed with the results, especially with Chad GPT 4's verbosity.
- π They discovered a new model by Entropic, which was released around the same time as CLA 3.5 Sonnet, and found it promising based on comparative metrics.
- π The new LLM is praised for its ability to write code, generate snippets, and build apps, which the creator finds superior for programming tasks.
- π The video will demonstrate a proof of concept app built with Flutter Flow that uses the new LLM as its backend for a chat interface.
- π Patreon community members have access to all apps and resources discussed, including the ability to clone them.
- π» The new LLM offers both a front-end chat interface and a back-end API for more technical interactions.
- π A standout feature of the new model is the ability to create 'artifacts,' which are real-time previews of code execution.
- π οΈ The model can generate custom widgets, functions, and actions for Flutter Flow apps, which can be easily integrated and customized.
- π The video provides a step-by-step guide on using the new LLM's features, including creating custom code snippets and integrating them into no-code platforms like Flutter Flow.
- π The creator encourages viewers to join their Patreon community for access to the proof of concept app, additional resources, and a supportive network of no-code enthusiasts.
Q & A
What is the main issue the speaker has with Chad GPT 4?
-The main issue the speaker has with Chad GPT 4 is that it's fairly wordy, often providing more information than necessary, even when asked for small modifications or code snippets.
What new LLM model did the speaker switch to and why?
-The speaker switched to an LLM model from Entropic, specifically CLA 3.5 Sonet, because it claimed to be better than GPT 4 in various metrics and seemed promising for programming tasks.
What is a unique feature of the new LLM model that the speaker appreciates?
-A unique feature the speaker appreciates is the ability to create artifacts, which allow the user to see what the generated code looks like when executed, providing immediate visual feedback.
How can one access the new LLM model's chat interface?
-To access the new LLM model's chat interface, one can Google for CL 3.5, which will lead to the main page or a blog article, and from there, clicking the provided button will redirect to the chat interface.
What is the difference between the front-end chat interface and the back-end interface of the new LLM model?
-The front-end chat interface allows users to have a conversation with the model, asking questions and solving issues, while the back-end interface is more technical, involving API keys and programmatic interaction.
What is a proof of concept app mentioned in the script?
-The proof of concept app mentioned is a chat client built using Flutter Flow, which uses the new LLM model as its backend and provides an easy-to-use chat interface.
How does the speaker use the new LLM model in their Flutter Flow apps?
-The speaker uses the new LLM model to generate custom code, functions, actions, and widgets for their Flutter Flow apps, utilizing the model's ability to create artifacts and execute code.
What are some of the features of the new LLM model that make it powerful for coding?
-Some powerful features for coding include the ability to generate and execute code snippets, create artifacts for immediate visual feedback, and the capacity to understand and maintain context in a conversation for more accurate responses.
How does the speaker plan to share the custom prompts they created with their Patreon community?
-The speaker plans to make all of the custom prompts they created available to their Patreon subscribers, allowing them to quickly start experimenting with their own Flutter Flow apps by creating custom code.
What additional benefits does the speaker mention for joining their Patreon community?
-In addition to accessing the custom prompts and apps, joining the Patreon community provides access to extra content, Q&As, a Patreon-supported Master Class Series, and a supportive community of like-minded individuals.
Outlines
π€ Transition from Chad GPT to a New LLM
The speaker discusses their experience with Chad GPT since its inception, noting dissatisfaction with the recent performance, particularly with Chad GPT 4's verbosity. They transitioned to another LLM, which they found to be more effective for their specific needs. The video promises an introduction to this new LLM, a comparison with Chad GPT, and a demonstration of a proof-of-concept app built with Flutter Flow utilizing the new LLM. The speaker also mentions their Patreon community as a resource for apps and further information.
π Exploring Features of the New LLM
The speaker explores the new LLM's features, highlighting its ability to generate artifacts that allow users to see code execution in real-time. They demonstrate this by having the model create an 8-bit style crab in SVG, an animation of multiple red crabs, and a JavaScript clock animation. The model's capability to update artifacts with new code on-the-fly is also showcased, emphasizing its powerful and immediate feedback for code generation.
π Backend Experience with the New LLM
The discussion shifts to the backend experience with the new LLM, focusing on its programmatic interface and API key usage. The speaker shows how to use the model to generate custom code for Flutter Flow apps, such as functions, actions, and widgets, by setting variables and running prompts. They also mention the ability to experiment with different prompts in the workbench and the ease of integrating the model into no-code platforms like Flutter Flow.
π± Building a Flutter Flow App with the New LLM
The speaker describes the process of building a Flutter Flow app that integrates the new LLM for generating custom widgets. They detail the steps of creating a prompt template, setting variables, and running the model to generate code that can be immediately used in Flutter Flow. The app preview shows a widget listing random food items, with functionality to generate new lists and execute actions based on user interaction.
π Integrating the New LLM into Existing Apps
The speaker provides insights on integrating the new LLM into existing apps, showcasing a chat client built with Flutter Flow that uses the LLM as its backend. They demonstrate the app's functionality, including its ability to maintain context in conversations and respond to questions about previously discussed topics. The video emphasizes the ease of setting up the integration using standard API calls and the potential for using the LLM in various app development scenarios.
π Conclusion and Invitation to the Patreon Community
In conclusion, the speaker expresses their enthusiasm for the new LLM, praising its coding capabilities and unique features over Chad GPT. They invite viewers to join their Patreon community to access the demonstrated app, future apps, and additional learning resources. The speaker highlights the supportive nature of the community and the value of receiving help from fellow members, as well as the satisfaction of contributing to the channel's mission of educating and assisting in no-code app development.
Mindmap
Keywords
π‘LLM (Large Language Model)
π‘Flutter
π‘API keys
π‘Artifacts
π‘No-code app builder
π‘Custom widget
π‘Prompts
π‘Patreon community
π‘Proof of concept
π‘Evaluation
Highlights
Switched from Chad GPT to a new LLM model for better results in specific use cases.
Introduced a proof of concept app built using Flutter Flow with the new LLM as its backend.
The new LLM provides a front-end chat interface and a backend API for technical interaction.
Features of the new LLM include the ability to create artifacts, showing real-time code execution.
Demonstrated creating an 8-bit style SVG craft and animation with the new LLM.
Showed how the new LLM can generate and update code for animations and widgets.
Highlighted the new LLM's capability to modify code based on user requests, like changing clock hands color.
Discussed the limitations of Chad GPT 4, such as verbosity and lack of precision in code snippet generation.
Compared the new LLM with Chad GPT 4, showing superiority in various metrics.
Explored the backend interface of the new LLM, focusing on API keys and programmatic interaction.
Shared custom prompts for generating Flutter widgets, functions, and actions with the new LLM.
Created a custom Flutter widget for listing random food items using the new LLM's backend.
Added functionality to execute a function when a list item is clicked, showcasing the LLM's adaptability.
Provided access to the source code and app for Patreon members to experiment and learn.
Emphasized the community aspect of Patreon, offering support and resources for no-code app development.
Encouraged viewers to join the Patreon community for access to apps, tutorials, and an active support network.
Shared future plans for complex app development and the continuous support for the no-code community.