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NEW

Python dotenv for LangChain Agents: Safe .env Patterns for RAG, Tools, and Local LLM Apps

Watch: Build a RAG (Retrieval-Augmented Generation) System from Scratch | Python + Vector DB + LLM by CodeVisium Python-dotenv gives local LangChain projects a simple way to keep credentials out of source code while still making them available through os.environ. It works well for solo prototypes,…
Thumbnail Image of Tutorial Python dotenv for LangChain Agents: Safe .env Patterns for RAG, Tools, and Local LLM Apps
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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NEW

Let Your Internal AI Agent Rewrite Its Own Prompts From Failed Runs

When you build AI agents that rewrite their own prompts after failed runs, you're addressing a gap that's been draining engineering time: the hidden orchestration tax of manual prompt iteration. The shift matters because every ambiguity in an agent prompt compounds across steps, turning vague…
Thumbnail Image of Tutorial Let Your Internal AI Agent Rewrite Its Own Prompts From Failed Runs
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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NEW

Grep Beats Embeddings for Some AI Coding Tool Tasks: Use Deterministic Search Before You Build RAG

Watch: Is RAG Still Needed? Choosing the Best Approach for LLMs by IBM Technology Short version: A SWE-Bench Verified agent using only grep and find reached the top of the leaderboard without any semantic indexing. A single exact-name query can use far fewer tokens with grep than broad embedding…
Thumbnail Image of Tutorial Grep Beats Embeddings for Some AI Coding Tool Tasks: Use Deterministic Search Before You Build RAG
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Build an AI Agent in 60 Lines of Python Before Reaching for LangChain

Watch: Build an AI Agent From Scratch in Python - Tutorial for Beginners by Tech With Tim Understanding the agent loop stopped being optional the moment you tried to change one thing in a framework demo and couldn't find where the loop lived. Quickstarts run fine until you need to touch them. A…
Thumbnail Image of Tutorial Build an AI Agent in 60 Lines of Python Before Reaching for LangChain
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
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Express for AI Inference in 2026: Build a Low-Latency RAG API with PGVector or FAISS

Latency stopped being optional the moment you put retrieval in front of an LLM. Every millisecond your vector search burns is a millisecond before the first token appears. Express stays lean by design, which leaves the vector store owning most of your retrieval headroom. This guide is a project…
Thumbnail Image of Tutorial Express for AI Inference in 2026: Build a Low-Latency RAG API with PGVector or FAISS
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
00
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