Update README.md

README.md

@@ -24,10 +24,10 @@ I'm named after my creator, Adda, but I take my "stealthy efficiency" cues from
 
 In a sea of PDF resumes, Adda-Bot demonstrates three key high-level competencies that are essential for modern AI and Software Engineering roles:
 
-    * **1. Practical RAG Implementation:** Most developers can prompt an AI, but building a Retrieval-Augmented Generation (RAG) pipeline requires understanding how to process data, manage vector embeddings, and handle context windows. This bot is a live proof-of-concept of my ability to build production-ready AI architectures.
+  **1. Practical RAG Implementation:** Most developers can prompt an AI, but building a Retrieval-Augmented Generation (RAG) pipeline requires understanding how to process data, manage vector embeddings, and handle context windows. This bot is a live proof-of-concept of my ability to build production-ready AI architectures.
 
-    * **2. Solving the "Information Overload" Problem:** Recruiters often have to hunt through pages of text to find a specific skill. This bot respects your time by allowing for natural language querying. Instead of scanning for "Python," you can simply ask, "How has Adda applied Python in a professional setting?" and get an instant, cited answer.
+  **2. Solving the "Information Overload" Problem:** Recruiters often have to hunt through pages of text to find a specific skill. This bot respects your time by allowing for natural language querying. Instead of scanning for "Python," you can simply ask, "How has Adda applied Python in a professional setting?" and get an instant, cited answer.
 
-    * **3. Full-Stack AI Thinking: This project showcases the full lifecycle of a feature:** from data engineering (Markdown parsing) to backend logic (LangChain & ChromaDB) and UI/UX design (Gradio with custom CSS). It proves I can take a concept from a blank page to a deployed, user-facing application.
+  **3. Full-Stack AI Thinking: This project showcases the full lifecycle of a feature:** from data engineering (Markdown parsing) to backend logic (LangChain & ChromaDB) and UI/UX design (Gradio with custom CSS). It proves I can take a concept from a blank page to a deployed, user-facing application.
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference