Automation Articles
Browse 927 articles about Automation.
The 5 Levels of AI Coding Autonomy: From Spicy Autocomplete to the Dark Factory
Understand the five levels of AI coding—from reference tool to fully autonomous dark factory—and discover which level is right for your team today.
AI Model Routing: How to Cut Costs 60% by Matching Tasks to the Right Model
Learn how to route AI tasks to the right model tier—frontier for planning, cheaper for execution—and cut your AI bill by up to 60%.
How to Build an AI Operating System for Your Business Using Claude Code
Learn how to design a personal AI OS with Claude Code—mapping workflows, automating tasks, and building a 30-day productivity plan from scratch.
What Is MiniCPM-5? The 1B On-Device AI Model Built for Agentic Tool Use
MiniCPM-5 is a 1B parameter model with 128K context, strong tool-use capabilities, and token efficiency that beats larger reasoning models.
The 5 Levels of AI Coding Autonomy: From Spicy Autocomplete to the Dark Factory
Discover the five levels of AI coding autonomy—from basic autocomplete to fully autonomous dark factories—and learn which level is right for your team.
How to Build an LLM Wiki Knowledge Base with Obsidian and Claude Code
Learn how to ingest YouTube transcripts, PDFs, and URLs into a cross-linked Obsidian knowledge base using Claude Code in under 5 minutes.
How to Build a Long-Running AI Agent That Doesn't Go Off the Rails
Long-running agents need goals, evaluators, verifiers, loops, orchestration, observability, and memory. Here's how to design each component correctly.
What Is the Dark Factory Approach to AI Coding? How to Ship Code Without Human Bottlenecks
The dark factory is a fully autonomous AI coding pipeline: spec goes in, shipped code comes out. Learn what it takes to build one and when it makes sense.
What Is Semantic Compression? How to Cut AI Token Costs by 75% Without Losing Quality
Semantic compression rewrites prompts and system files to maximum information density. Learn how to reduce token usage by 75% with zero quality loss.
The 5 Levels of AI Coding Autonomy: From Spicy Autocomplete to the Dark Factory
AI coding ranges from enhanced search to fully autonomous deployment. Learn the 5 levels, where you should be, and what it takes to reach the dark factory.
AI Agent Observability: How to Monitor Agents Running for Hours Without Babysitting
You can't watch a 6-hour agent session. Learn how to set up dashboards, traces, and monitors so you know exactly when to step in and when to let it run.
How to Build an LLM Wiki Knowledge Base with Obsidian and Claude Code
Learn how to build a self-growing knowledge base from YouTube transcripts, PDFs, and URLs using Karpathy's LLM wiki architecture and Claude Code.
How to Build a Long-Running AI Agent That Doesn't Go Off the Rails
Long-running agents need 7 components to stay reliable: goal, evaluator, verifiers, loops, orchestration, observability, and memory. Here's how to build them.
Token Reduction Strategies for AI Agents: 8 Techniques That Cut Costs by 50% or More
Semantic compression, RTK, logs to SQLite, and capped thinking budgets can cut AI agent token costs by 50–99% with near-zero quality loss. Here's how.
What Is the Dark Factory Approach to AI Coding? How to Ship Code Without Human Bottlenecks
The dark factory takes a spec and ships production code with no human in the loop. Learn the architecture, required agents, and why most teams aren't ready yet.
The 5 Levels of AI Coding: From Spicy Autocomplete to the Dark Factory
Discover the five levels of AI coding autonomy—from manual reference tools to fully autonomous dark factories—and find the right level for your workflow.
AI Agent Evaluators and Verifiers: How to Stop Agents from Grading Their Own Work
Learn why AI agents shouldn't evaluate their own output and how to build separate evaluator and verifier components that catch errors before they ship.
AI Agent Observability: How to Monitor Agents Running for Hours Without Babysitting
Discover how to add observability to long-running AI agents so you can catch failures, track costs, and fix issues before users notice.
How to Use AI Agents for High-Stakes Paperwork: Insurance, Taxes, and Healthcare
Learn how to apply a 9-part agent skeleton to organize messy documents into structured case files for insurance appeals, tax prep, and healthcare claims.
How to Build an AI Flywheel: Reusing Agent Primitives Across Email, Insurance, and Taxes
Learn how to build reusable agent primitives—ingestion, normalization, citations, and gates—that make every new AI workflow faster and cheaper to build.