In this video, I walk through the latest updates to our AI-powered website project, where we’re integrating tools like ChatGPT, Claude, and Gemini to develop intelligent web applications. This live session dives deep into chatbot development, optimizing dropdown search features, and structuring the site for large language models (LLMs) to interpret efficiently.
I also talk about the design process behind the interactive AI tool directory on our site, including how we’re categorizing neural tools, managing code in HTML and PHP, and making the system LLM-friendly for future development in the canvas editor.
If you’re curious about how we’re using AI models in real-time to shape a smarter, searchable, and more intuitive platform — you’re in the right place.
Thanks for watching, and don’t forget to subscribe for more updates on our journey to building an AI-first user experience.
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0:00 Introduction and stream setup
0:06 Talking to ChatGPT, Claude, and Gemini
0:23 Overview of updates on the website
0:34 Sharing the live stream on LinkedIn
0:41 Upcoming chatbot for the website
0:47 Long-term project and training data
0:53 Web applications and tool prompts
1:07 Missing chatbot prompt in ChatGPT history
1:16 NLP libraries used in training
1:26 Neural language processing and project context
1:31 Purpose of the YouTube channel and website
1:36 Chatbot plans for front page
1:43 Dropdown search feature
1:51 Sneaky logic in tool filtering
2:00 Tool filtering with exclamation marks
2:08 Testing REAX search integration
2:16 Starting chatbot from scratch
2:22 EEG tool selection demonstration
2:30 Streamlining the landing page
2:38 Code refactoring challenges
2:45 Keyword optimization for dropdown
2:55 Matching keywords with app/blog content
3:03 Ensuring search relevance across content
3:10 Keyword mapping and search testing
3:21 Experimenting with Claude code
3:34 Code context window comparisons
3:45 Google AI and feature comparisons
3:58 Code generation expectations
4:05 Index.html vs. PHP structure
4:15 Meta PHP file management
4:27 Revisiting suggestions from ChatGPT
4:35 Exploring Deepseek login issues
4:43 ChatGPT’s built-in text-to-speech
4:50 Voice quality and speech feedback
4:57 Code split decisions from Gemini
5:06 Optimizing HTML and JavaScript usage
5:12 Choosing between code consolidation or splitting
5:23 Generating overview for TTS
5:32 Code structure performance in production
5:41 Gemini’s suggested split implementation
5:51 Evaluating file formats and LLM usability
5:59 Code setup for LLM processing
6:09 Editing code with canvas interface
6:16 Ensuring isolated and visible edits
6:24 Visualizing and validating edits
6:33 Potential of Deepseek in code editing
6:41 Wrapping up the stream
6:48 Interactive AI tools on the website
6:55 Interactive Venn diagram features
7:01 Future multi-level rabbit hole navigation
7:09 Expanding clickable AI insights
7:18 Final thoughts and call to action
7:30 Outro and sign-off
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