Insights
Artificial Intelligence
Practical writing on applied and agentic AI, LLMs, RAG, and machine learning for finance and regulated industries.
Observability and Governance in RAG: Building Trustworthy AI for Insurance and Banking
A practical guide to understanding observability, governance, RAG validation, judge models, and safety guardrails—explained in simple terms for building compliant AI systems in insurance, banking, and regulated industries.
Read · 10 min
Compliant AI Orchestration in Insurance: From API Calls to Structured Claim Decisions
A practical guide to building a stateful, agent-driven insurance workflow that orchestrates eligibility checks, contract validation, shared state management, human oversight, and data-grounded claim summaries.
Read · 8 min
Architecting an Agentic Claims Assistant: A Simple, Grounded Explanation of Autonomous Insurance Triage
A step-by-step, plain-language walkthrough of how to design a stateful, tool-using AI claims assistant using LangGraph — covering orchestration, shared state, multi-step reasoning, human-in-the-loop controls, and structured resolution outputs.
Read · 12 min
Building True AI Agents: Understanding the Core Architecture
A clear, layer-by-layer explanation of how modern AI agents are constructed — from probabilistic token prediction to structured tool use, strong typing, and observable orchestration loops.
Read · 10 min
Understanding and Implementing Simple Linear Regression from Scratch
A grounded, intuitive introduction to simple linear regression using real-world farming analogies and first-principles reasoning.
Read · 10 min
What Is an AI Agent? A Simple Guide for New Learners
A clear, story-style introduction to AI agents, how they use Generative AI and large language models, and why they feel more like smart helpers than simple chatbots.
Read · 6 min
Level Up Your AI Chats: Six Prompt Moves That Wake Your Words Up
Six small prompt shifts turn AI from a dull answer machine into a sharp thinking partner you can use all day, from budgets to bedtime stories.
Read · 8 mins
How LLMs Choose the Next Token: A Practical Guide to Logits, Decoding, and Sampling
An intuition-first guide to how large language models turn raw logits into next-token choices, using real-world analogies to explain temperature, top-k, and top-p.
Read · 12 min
RAG with Tabular Data: From Schemas to Answers
How to design and operate Retrieval-Augmented Generation systems over relational and financial tabular data.
Read · 12 min
How LLMs Choose the Next Token: A Practical Guide to Decoding and Sampling
An intuition-first explanation of how large language models select the next token, demystifying temperature, top-k, and top-p through real-world analogies.
Read · 12 min
The Lifecycle of an LLM
From raw text to real-time answers: how large language models actually work.
Read · 8 min