A research-driven history of Retrieval-Augmented Generation from 2020 to 2026, covering foundational architectures, adaptive and graph-based systems, evaluation benchmarks, security risks, and production best practices.

Enhancing Language Models with RAG: Best Practices and Benchmarks (2020–2026)

In this article, we will explore the brief history of AI

The History of AI: From Machine Learning to Deep Learning and LLMs

How I built Invariant with IBM Bob to catch patient-level data leakage during code review, verify a fix, and prevent the bug from returning.

Invariant: When the Tests Pass but the ML Evaluation Is Wrong

In this article, we complete the Python Under the Hood series by exploring iteration, generators, suspended execution frames, context managers, exception flow, coroutines, await, tasks, futures, and the event loop.

Python Runtime Under the Hood: Iterators, Generators, Context Managers, Exceptions, and Async

In this article, we explore how Python creates class and instance objects, resolves attributes and methods, binds self, follows inheritance and MRO, and uses descriptors to power methods and properties.

Python Objects Under the Hood: Classes, Instances, Attributes, Methods, Inheritance, and MRO

In this article, we explore how Python binds arguments to function parameters, how mutation differs from rebinding, how closures retain enclosing state, and how decorators wrap and transform functions.

Python Functions Under the Hood: Argument Passing, Mutability, Closures, and Decorators

In this article, we trace how Python turns source code into running objects in memory, and the LEGB rules it uses to find them by name.

All Posts

Enhancing Language Models with RAG: Best Practices and Benchmarks (2020–2026)

The History of AI: From Machine Learning to Deep Learning and LLMs