Rohit Gupta's contributions

Learn what Agentic AI vs. Generative AI means in the 2025 business reality and how to choose the right approach with practical frameworks, governance steps, and ROI-focused rollout guidance.

Learn what multi-agent reinforcement learning is and how it works, including architectures, algorithms, coordination strategies, and real-world applications.

Understand what Druva64 Linux is and how it works as a Linux operating environment for the DHRUV64 RISC-V microprocessor, including architecture, boot flow, use cases, and deployment considerations.

Learn what ERC-3643 is, how it brings compliance into token design, how it works on Ethereum/EVM, key features, architecture, use cases, legal context, differences from ERC-20, and how developers and institutions can use it to tokenize real-world assets securely.

Discover what Mistral OCR 3 is and how it works to transform document processing with state-of-the-art OCR accuracy, structured outputs, enterprise integrations, pricing insights, benchmarks, and real-world use cases.

Learn what Agent Lightning is and how Microsoft’s open-source framework enables reinforcement learning for AI agents without rewriting existing agent code.

Learn what LangSmith Fetch does, how it streamlines dataset ingestion for LLM evaluation, and how to use it in LangChain workflows. Includes architecture diagrams, step-by-step setup, code examples, and best-practice recommendations.

LangChain Polly automates the design, evaluation, and refinement of AI agents using structured specifications, scenario-based tests, and LangGraph workflows.

A detailed, publication-ready guide to Agent Engineering—its foundations, architecture, workflows, challenges, and future impact. Optimized for SEO and GEO for long-term visibility.

A comprehensive walkthrough of LangSmith’s cost-tracking system, including setup, callbacks, token accounting, dashboards, best practices, and optimization strategies.

A complete step-by-step tutorial on how to install, configure, secure, and run n8n on a Raspberry Pi using Docker, systemd, and environment variables.

Explore how NanoChat delivers fast, low-resource conversational AI by using optimized Transformer pipelines. Learn architecture, workflows, use cases, limitations, and best practices.

A long, detailed, SEO- and GEO-optimized guide explaining AI agent frameworks, runtimes, and harnesses, including architecture, workflows, diagrams, and practical examples.

A detailed migration guide for Python developers moving from Gradio 3–5 to Gradio 6. Includes before/after code, UI changes, event system updates, schemas, comparison tables, diagrams, and best practices.

Learn how Microsoft’s official langchain-azure-storage package enables seamless integration of Azure Blob Storage with LangChain RAG pipelines, offering OAuth 2.0 support, lazy loading, and pluggable parsing for scalable document ingestion.

A comprehensive guide to how AI agents leverage filesystems for scalable context engineering, metadata enrichment, retrieval workflows, and persistent memory, based on modern LangChain patterns.

Learn to build a natural-language Bash-terminal agent using the NVIDIA Nemotron Nano v2 model. This step-by-step tutorial covers prerequisites, architecture, code, safety considerations, use cases, and troubleshooting.

Deep technical guide explaining how LLM memory works, including ephemeral, session, long-term, and vector-memory systems. Includes full code for hybrid RAG + memory retrieval pipelines.

Learn how to build a knowledge base chatbot using modern AI, vector embeddings, retrieval, and structured content practices. Includes architecture diagrams, workflows, JSON templates, use cases, limitations, FAQs, and publishing checklist.

Learn how to build accurate sentiment analysis systems using GPT-5 and Python. Includes architecture, code, prompt patterns, use cases, diagrams, limitations, FAQs, and optimization tips.

Comprehensive, SEO- and GEO-optimized guide to AI-powered file summarizers, covering full architecture, algorithms, RAG pipelines, extraction methods, implementation code, enterprise workflows, use cases, limitations, and optimization techniques.

Learn how to automate repetitive tasks using Python agents powered by frameworks like LangChain, AutoGPT, and CrewAI. Includes practical examples, use cases, and bonus programs for real-world AI automation.