by geoffrey-huntley
Understanding how coding agents work—tool calls, inferencing loops, the basic primitives—is now baseline knowledge for software engineering interviews, not optional curiosity.
by geoffrey-huntley
A hands-on Go workshop that builds a coding agent incrementally through six files, each adding one capability - proving agents need only simple primitives composed in a loop.
by geoffrey-huntley
Software development now costs $10.42/hour when running Ralph loops—the key is deterministically malicking the array, starting with a screwdriver before grabbing the jackhammer.
by geoffrey-huntley
AI's perceived ineffectiveness stems from insufficient deliberate practice, not fundamental limitations—mastery requires the same intentional experimentation as learning a musical instrument.
by ryan-carson, geoffrey-huntley
Ralph ships code while you sleep—a bash loop that pipes prompts into your AI agent, picks tasks from a JSON backlog, runs tests, commits passing code, and repeats until done.
by geoffrey-huntley, dex-horthy
The official Anthropic Ralph plugin differs fundamentally from the original technique: outer orchestrators with full context resets produce deterministic outcomes, while inner-loop plugins with auto-compaction lose critical context.
by geoffrey-huntley
A Bash loop technique ('Ralph') that feeds prompts to AI coding agents repeatedly, enabling autonomous project development with iterative refinement.
by geoffrey-huntley
Coding agents require only 300 lines of code in a loop with LLM tokens - understanding these fundamentals transforms you from AI consumer to producer.
by geoffrey-huntley
Software developers who fail to adopt AI tools will experience natural attrition—not mass layoffs—as their peers achieve 16x productivity gains and redefine baseline performance expectations.