My Journey Building AI Agents, RAG Systems, and AI-Powered Applications
I have been building AI applications to understand what happens when an LLM has to do more than just answer a prompt. My projects cover research, agentic workflows, RAG, memory, automation, document processing, financial analysis, and AI-powered applications. Here are some of the projects I have built and what each one taught me. 1. Deep Research Agent Status: Live GitHub: Research-AI-Agent Live…
The author's journey of building AI applications, including research agents, financial research agents, an appointment bot, a RAG architecture, a medical compliance SaaS, and a context synthesizer, has taught them key lessons about AI development. Instead of simply connecting an LLM to a prompt, the author discovered that the most challenging aspects involve selecting what information the system can access, which tools it can use, and what kind of structured output is required.
Each project highlighted different challenges and required unique solutions, ranging from handling multiple research stages and financial data workflows to integrating various business processes and compliance workflows. The author emphasizes that building AI applications requires more than just a chatbot interface; it demands careful consideration of data sources, tool integration, memory management, and evaluation mechanisms.
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