Personal details
Tony S.
Summary
- AI apps development (chatbots, content automation, decision making)
My tech stack is:
- Python
- OpenAI API (GPT-3.5, GPT-4)
- LangChain
- Pinecone
- Flask/Streamlit
- Git
- Docker
- Prompt Engineering
I've dedicated 800+ hours this year alone writing prompts and teaching it to others.
I'm an entrepreneur and coder with experience in marketing (19y) data science (10y) and AI (1.5y).
Some of my AI work:
-
An LLM app that collects, overviews and asnwers questions about AI news and other AI related content. The tool also creates social media content based on these overviews for me.
https://www.youtube.com/watch?v=0fDhtJ8PxLk -
Prompt Engineering case-study: https://www.notion.so/valueto/Prompt-Engineering-Case-Study-collecting-categorising-and-repurposing-content-by-Tony-AI-Champ-43354a95777a49fb90e1f35c5385ca1d
-
Airi Onboardwell, an AI conversational chatbot. In this instance, Airi is trained on data about a social media role in the company named InsightWhale (that serve web3 clients) to help new employee on this role onboard faster and save InsighWhale 1 salary out of 6 that a company normally spend on onboarding a new employee. You can ask her questions about the role details. Airi is trained the way that if she doesn't know the answer, she will raise the question to the relevant person in the company, get an answer and memorise it so that next time a similar question emerges, she can answer it.
https://aiemploy-ee-airi-onboardwell-flask-sg.onrender.com -
My Udemy prompt engineering course with over 1700 students with an average rating of 4.5/5: https://www.udemy.com/course/chatgpt-for-data-science-and-data-analysis-in-python/