LLM Foundations

Core mechanics of large language models — training, inference, tokenization, and the mathematics of next-token prediction.

Machine learning maps technical debt hotspots across a codebase, flagging code smells and high-risk files for refactoring
MONA explainer 10 min

What Is AI for Technical Debt and How Machine Learning Detects Code Smells and Hotspots

What Is AI for Technical Debt and How Machine Learning Detects Code Smells and Hotspots ELI5

How AI tools estimate technical debt using proxy signals like code complexity and git change frequency
MONA explainer 10 min

What AI Technical-Debt Tools Actually Measure — and Where the Numbers Break

What AI Technical-Debt Tools Actually Measure — and Where the Numbers Break ELI5

Diagram of an AI-driven CI/CD pipeline scoring commit risk and reordering tests before deployment
MONA explainer 10 min

What Is AI in CI/CD Pipelines and How Automated Code Analysis and Deployment Checks Work

What Is AI in CI/CD Pipelines and How Automated Code Analysis and Deployment Checks Work ELI5

Particle graph of a CI/CD pipeline where an AI node misclassifies a failing test as flaky and lets a regression pass
MONA explainer 11 min

Prerequisites and Technical Limits of AI in CI/CD: DevOps Foundations to Flaky-Test False Positives

Prerequisites and Technical Limits of AI in CI/CD: DevOps Foundations to Flaky-Test False Positives …

Particles forming code that dissolves into a flowing prompt sentence, visualizing the shift from artifact to intent
MONA explainer 10 min

What Is Vibe Coding and How Natural-Language Development Replaces Manual Code Editing

What Is Vibe Coding and How Natural-Language Development Replaces Manual Code Editing ELI5

Curated token layers — prompts, tools, files, history — flowing into an AI coding assistant's context window
MONA explainer 10 min

What Is Context Engineering for Code and How It Shapes AI Coding Assistant Output

What Is Context Engineering for Code and How It Shapes AI Coding Assistant Output ELI5

Concept visualization of an agentic coding loop iterating through plan, write, test, and revise stages.
MONA explainer 12 min

What Is Agentic Coding and How Plan-Write-Test-Iterate Loops Replace Manual Development

What Is Agentic Coding and How Plan-Write-Test-Iterate Loops Replace Manual Development ELI5

Layered constraint diagram showing context window, connected tools, and security gates filtering AI-generated code
MONA explainer 9 min

Prerequisites for Vibe Coding and the Technical Limits That Break the Illusion

Prerequisites for Vibe Coding and the Technical Limits That Break the Illusion ELI5

Three concentric layers around a language model — tool calls, scaffolding, and a verify loop
MONA explainer 11 min

Prerequisites for Agentic Coding: Tool Use, Scaffolding, and the Plan-Execute-Verify Loop

Prerequisites for Agentic Coding: Tool Use, Scaffolding, and the Plan-Execute-Verify Loop ELI5

Layered streams of source code, MCP servers, and memory files converging into a single LLM context window.
MONA explainer 12 min

From Repo Indexing to Memory Files: Prerequisites and Limits of Code Context Engineering

From Repo Indexing to Memory Files: Prerequisites and Limits of Code Context Engineering ELI5

Cascading tokens fading in a context window beside a tool-call retry loop, illustrating coding-agent failure modes
MONA explainer 10 min

Context Window Collapse, Tool-Call Loops, and the Hard Technical Limits of Coding Agents in 2026

Context Window Collapse, Tool-Call Loops, and the Hard Technical Limits of Coding Agents in 2026 …

Diagram of Model Context Protocol limits: optional authentication, tool sprawl token cost, and stateful connection fragility
MONA explainer 11 min

The Technical Limits of MCP: Missing Authentication, Tool Sprawl, and Stateful Connections

The Technical Limits of MCP: Missing Authentication, Tool Sprawl, and Stateful Connections ELI5

Model Context Protocol linking one AI model to external tools, data sources, and APIs through a single standard interface
MONA explainer 9 min

What Is the Model Context Protocol and How It Connects AI Assistants to External Tools

What Is the Model Context Protocol and How It Connects AI Assistants to External Tools ELI5

Diagram of an AI code migration pipeline translating legacy COBOL into Java through deterministic and LLM-agent stages
MONA explainer 10 min

What Is AI Code Migration and How LLM Agents Translate Languages and Modernize Legacy Codebases

What Is AI Code Migration and How LLM Agents Translate Languages and Modernize Legacy Codebases ELI5 …

Diagram of MCP architecture linking a host, clients, and servers exposing tools, resources, and prompts over JSON-RPC
MONA explainer 10 min

MCP Architecture Explained: Hosts, Clients, Servers, and the Tools-Resources-Prompts Primitives

MCP Architecture Explained: Hosts, Clients, Servers, and the Tools-Resources-Prompts Primitives ELI5 …

Deterministic AST-based code migration versus probabilistic LLM transformation and the silent test regressions between them
MONA explainer 10 min

AI Code Migration: AST Parsing, Test Coverage, and the Problem of Silent Regressions

AI Code Migration: AST Parsing, Test Coverage, and the Problem of Silent Regressions ELI5

Source code parsed into a syntax tree with retrieval chunks feeding an LLM that emits documentation.
MONA explainer 11 min

Prerequisites for AI Documentation Generation: From AST Parsing to Repo-Scale Context Windows and Hallucination Limits

Prerequisites for AI Documentation Generation: From AST Parsing to Repo-Scale Context Windows and …

Syntax tree being rewritten by an autonomous coding agent across linked files
MONA explainer 11 min

What Is AI-Assisted Refactoring and How Agentic Tools Restructure Code Without Breaking It

What Is AI-Assisted Refactoring and How Agentic Tools Restructure Code Without Breaking It ELI5

Source code lines flowing into structured layers of docstrings, API references, and architecture diagrams
MONA explainer 9 min

What Is AI Documentation Generation? How LLMs Turn Code Into Docstrings and Architecture Docs

What Is AI Documentation Generation? How LLMs Turn Code Into Docstrings and Architecture Docs ELI5

Diagram of AST structure, test coverage layers, and hallucination guardrails for AI-assisted code refactoring workflows
MONA explainer 11 min

Prerequisites for AI-Assisted Refactoring: From AST Awareness to Test Coverage and Behavior Preservation

Prerequisites for AI-Assisted Refactoring: From AST Awareness to Test Coverage and Behavior …

Stack trace tokens dissolving into a probability cloud at the boundary of an AI model's context window
MONA explainer 10 min

Prerequisites for AI-Assisted Debugging: Stack Traces, Context Windows, and Why Models Still Hallucinate Fixes

Prerequisites for AI-Assisted Debugging: Stack Traces, Context Windows, and Why Models Still …

Particles forming a stack trace with an arrow tracing back to the originating source code line
MONA explainer 12 min

What Is AI-Assisted Debugging and How LLMs Analyze Stack Traces to Find Bugs

ELI5

LLM transforming a code function into structured unit test candidates filtered by coverage signals
MONA explainer 12 min

What Is AI Test Generation and How LLMs Write Unit and Integration Tests from Code

What Is AI Test Generation and How LLMs Write Unit and Integration Tests from Code ELI5

Split panel contrasting a tall coverage bar with a short mutation-kill bar against the same code under test
MONA explainer 12 min

From Coverage Metrics to Mutation Testing: What You Need to Know Before Using AI Test Generators

ELI5

AI agent reviewing pull request changes with highlighted bug patterns and dependencies between files.
MONA explainer 14 min

What Is AI Code Review and How LLM-Powered PR Reviewers Catch Bugs Before Humans

What Is AI Code Review and How LLM-Powered PR Reviewers Catch Bugs Before Humans ELI5

Diagram of inline AI code completion stack — tokenizer, context window, fill-in-the-middle training, speculative decoding.
MONA explainer 11 min

From Context Windows to Speculative Decoding: Prerequisites and Technical Limits of Inline Code Completion

From Context Windows to Speculative Decoding: Prerequisites and Technical Limits of Inline Code …

Probability distribution emerging from a code cursor, showing how an LLM ranks candidate tokens for inline completion
MONA explainer 14 min

What Is AI Code Completion and How LLM-Powered Inline Suggestions Predict the Next Token

What Is AI Code Completion and How LLM-Powered Inline Suggestions Predict the Next Token ELI5

Layered diagram showing retrieval, static analysis, and language model triage as three stages of AI code review
MONA explainer 11 min

Prerequisites for AI Code Review: RAG, Static Analysis, and the Hard Limits of LLM Bug Detection

Prerequisites for AI Code Review: RAG, Static Analysis, and the Hard Limits of LLM Bug Detection …

A screenshot-driven agent loop: capture, locate UI elements visually, emit coordinates, click, and repeat on a desktop
MONA explainer 12 min

What Are Browser and Computer Use Agents and How Screenshot-Grounded AI Controls Your Desktop

What Are Browser and Computer Use Agents and How Screenshot-Grounded AI Controls Your Desktop ELI5

Control loop diagram where an agent decides whether to retrieve, judges chunk relevance, and reroutes failed queries.
MONA explainer 10 min

What Are Retrieval-Augmented Agents and How They Combine Agentic Reasoning with Dynamic Retrieval

What Are Retrieval-Augmented Agents and How They Combine Agentic Reasoning with Dynamic Retrieval …