How I Create and Code AI Startup Ideas in 24 hours - OpenAI

Adrian Twarog
27 Oct 202310:04

TLDRIn this video, the creator embarks on a challenge to develop an AI startup within 24 hours. Starting with idea generation, the creator explores various concepts like a Chrome extension for auto-completion and AI chatbots for documentation search, only to pivot due to market saturation. Inspired by a personal coding tutorial struggle, the project evolves into using the YouTube API to download video transcripts and OpenAI's GPT to answer questions about the content. The creator successfully integrates these technologies, faces and overcomes API challenges, and eventually builds a functional MVP with a web interface, demonstrating the potential of combining AI with video content analysis.


  • ๐Ÿ’ก The process of creating an AI business can be fast-paced, requiring quick pivots and idea iterations.
  • ๐Ÿ” It's important to identify gaps in the market that are not yet covered by large companies, like Grammarly or Adobe.
  • ๐Ÿ› ๏ธ The speaker started with the idea of a Chrome extension for auto-completion but pivoted to a different idea due to market saturation.
  • ๐Ÿค– The concept of using AI for image processing was considered, but large companies like Mid Journey were already established in this area.
  • ๐Ÿ”„ Pivoting is a key part of startup culture, as demonstrated by the speaker's shift from one idea to another based on competition and feasibility.
  • ๐Ÿ“ The idea of downloading video transcripts to search for specific information within them emerged from a personal problem experienced by the speaker.
  • ๐Ÿ”— The YouTube API was utilized to download video transcripts, which involved overcoming initial technical challenges.
  • ๐Ÿ“š The transcript data was successfully integrated with OpenAI's chat GPT to answer questions about the content of the videos.
  • ๐Ÿ“ˆ The use of a vector database, specifically Astra DB, was chosen for its suitability with large language models and efficient data handling.
  • ๐Ÿ“ The project involved creating a user interface that allows users to input YouTube URLs, retrieve video details, and interact with chat GPT for insights.
  • ๐Ÿ›‘ The project has limitations, such as the inability to process very long video transcripts in a single chat GPT message, indicating a need for further refinement.

Q & A

  • What was the initial idea for the AI business project?

    -The initial idea was to create a Chrome extension that uses AI for auto-completion in text fields.

  • Why was the Chrome extension idea not pursued?

    -The idea was abandoned because large companies like Grammarly already dominate the space for auto-completion tools.

  • What alternative idea was considered for the AI startup?

    -An alternative idea was to create a startup that searches through documentation of popular libraries and languages and uses AI as a chatbot to provide answers from that documentation.

  • What was the problem the creator faced while trying to use the YouTube captions API?

    -The creator faced issues with downloading the captions and needed an API key, which was not readily available or functional.

  • How did the creator overcome the issue with the YouTube captions API?

    -The creator found a section in the YouTube data API documentation that allowed downloading of transcripts and used a library called 'YouTube transcripts' to successfully retrieve them.

  • What is the purpose of the 'chat GPT' in the project?

    -The 'chat GPT' is used to interact with the downloaded video transcripts, answering questions about the video content based on the text.

  • What was the final MVP (Minimum Viable Product) of the project?

    -The MVP is a system where users can input a YouTube URL, and the system retrieves the video's details and transcript, then asks chat GPT questions about the video to provide insights.

  • What limitations were identified in the project?

    -One limitation is that for very long videos, the entire transcript might not fit into a chat GPT message, requiring the transcript to be split into sections.

  • How does the system handle storing and retrieving video information?

    -The system uses a vector database called Astra DB to store and retrieve video information such as URL, title, description, and transcript.

  • What is the role of the front-end interface in the project?

    -The front-end interface allows users to input a YouTube URL, displays the video details, and presents the questions and answers from chat GPT in an interactive manner.

  • What is the significance of the vector in the context of this project?

    -The vector is a representation of the video content created by OpenAI, which is used to enhance the search and retrieval capabilities of the video transcripts in the database.



๐Ÿค– Building an AI Business in 24 Hours

The speaker embarks on a challenge to create an AI business within a day. Initially, they brainstorm ideas such as a Chrome extension for auto-completion and a chatbot for coding documentation. However, recognizing existing competition, they pivot to a new idea inspired by a personal struggle: downloading video transcripts to search for specific information. They explore using the YouTube API and eventually find success with a library called 'YouTube transcripts'. The plan is to integrate this with OpenAI's GPT to answer questions about video content. After overcoming initial hurdles with the API, they successfully test the concept by querying the AI with video-related questions, receiving accurate responses.


๐Ÿ”— Integrating YouTube Transcripts with AI

The speaker delves into the technical process of creating their AI project. They describe setting up an Astra DB vector search database to store YouTube video transcripts and metadata. After a brief tutorial on Astra DB, they create a database and begin coding, using a boilerplate template provided by Astra DB as a starting point. They refactor the code to create a clean, modular system and build a model in MongoDB for storing video data. They encounter and resolve issues with database collection persistence and successfully store and retrieve video information. The project culminates in a simple web interface that allows users to input a YouTube URL, query the database, and receive answers from the integrated chat GPT based on the video transcript. The speaker acknowledges limitations regarding long video transcripts and suggests improvements for future development.




AI, or Artificial Intelligence, refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the context of the video, AI is used to create innovative business ideas, such as auto-completion in text fields, chatbots for documentation, and image processing. The script discusses the challenges of finding a unique AI application due to competition from established companies.

๐Ÿ’กChrome extension

A Chrome extension is a software module that adds functionality to the Google Chrome browser. The video script mentions the idea of creating a Chrome extension that uses AI for auto-completion in text fields, suggesting a tool that could enhance user experience by predicting and completing phrases as users type.


Auto-completes is a feature that predicts and suggests completions for the text a user is typing, based on patterns and previous inputs. In the script, the concept is explored for a potential Chrome extension, aiming to assist users in writing more efficiently with AI-generated text suggestions.


Documentation in the context of the video refers to the official manuals or instructions that come with software libraries and programming languages. The script discusses the idea of using AI to search through this documentation and provide answers via a chatbot, demonstrating an application of AI in assisting developers with technical inquiries.

๐Ÿ’กImage processing

Image processing involves the manipulation of images using software or AI algorithms to perform tasks such as editing, enhancing, or analyzing visual content. The script briefly mentions the idea of using AI for image processing, indicating a potential business application where AI could upscale images or perform other enhancements.


To pivot in a business context means to change the direction or focus of a project or product in response to new information or challenges. The video script describes the process of pivoting an AI startup idea when faced with competition, emphasizing the importance of adaptability in the startup culture.

๐Ÿ’กYouTube API

The YouTube API is a set of tools provided by YouTube that allows developers to interact with and extract data from the platform. In the script, the YouTube API is used to download video transcripts, which are then utilized to create a searchable database and interact with an AI chatbot for answering questions about video content.


A transcript is a written version of spoken dialogue, often used for videos to provide a text alternative to the audio content. The video script details the process of downloading YouTube video transcripts and using them in conjunction with AI to answer questions about the content of the videos.

๐Ÿ’กChat GPT

Chat GPT refers to a type of AI chatbot that can engage in conversation, answer questions, and provide information. In the video, Chat GPT is used to interact with the downloaded transcripts, providing answers to questions about the content of YouTube videos.

๐Ÿ’กVector database

A vector database is a type of database designed to store and retrieve data based on vector similarity rather than exact matches. The script discusses the use of a vector database, specifically Astra DB, to store and manage the transcripts and vectors generated from the AI analysis of YouTube videos, allowing for efficient searching and retrieval of video content.

๐Ÿ’กAstra DB

Astra DB is a database service that offers a vector database feature, which is used in the video script to store and manage YouTube video transcripts and their associated vectors. The use of Astra DB demonstrates a practical application of a vector database in handling large volumes of text data for AI analysis.


Building an AI business in 24 hours is possible, showcasing the process from idea generation to implementation.

Initial idea of a Chrome extension for auto-completion in text fields was discarded due to competition from Grammarly.

A startup that uses AI to search through documentation and provide answers as a chatbot was considered.

Image processing idea was also dropped due to competition from companies like Mid Journey and Adobe.

The concept of pivoting and changing ideas quickly in startup culture is emphasized.

The creator's past problem of finding specific information in a long video tutorial inspired a new idea.

Using the YouTube API to download video transcripts and searching within them for answers was proposed.

The creator faced challenges with the YouTube captions API and sought solutions through online research.

A successful attempt to connect directly to the YouTube API and use it with Chat GPT was made.

A function to download YouTube transcripts was implemented using the YouTube transcripts library.

The transcript was beautified and merged into a file to be used with Chat GPT.

Chat GPT accurately answered questions about the content of the video based on the transcript.

The limitations of Chat GPT without access to visuals were acknowledged.

The idea of using a vector database for storing and retrieving video transcripts was introduced.

Astra DB was chosen for its vector database capabilities and ease of use.

A boilerplate template provided by Astra DB was adapted for the project.

The project was refactored for better organization and functionality.

A web user interface was created for interacting with the backend and Chat GPT.

The final project allows users to input YouTube URLs, retrieve video details, and ask questions about the content.

The creator discusses potential improvements, such as splitting long transcripts into sections for better interaction with Chat GPT.

Astra DB is thanked for sponsoring the video, highlighting the importance of community and support in project development.