Catalog · topic

AI & LLM

Build with Claude the way we do. Prompt design, agent coordination, quality evaluation and the working habits that keep an AI model on task.

This is our discipline for working with Claude, written down: inputs that are designed instead of guessed, agents that are measured instead of taken on faith, and a memory layer that survives between sessions. It is the same method behind our own systems.

17 skills · 1 agents

Who this shelf is for
  • Developer whose agents work in demos and break in production
  • Team building on Claude with no way to measure output quality
  • Builder who needs the AI to remember context after the session ends
Where to start

Brain ships as its own product, so start here with Context Driven Development to fix what you feed the model, then add Agent Eval Suite Langsmith to measure what changes.

Skills 17

AI & LLM Skill

Claude Agent Template Library

A categorized canon of 100+ Claude Code subagent templates with a strict frontmatter standard, enforcing Mission Brief, Agent Chain and bypass-permissions discipline.

$15
Inspect →
AI & LLM Skill

LLM Evaluation

Implement comprehensive evaluation strategies for LLM applications using automated metrics…

$15
Inspect →
AI & LLM Skill

ML Pipeline Workflow

Build end-to-end MLOps pipelines from data preparation through model training, validation, and…

$15
Inspect →
AI & LLM Skill

Model Selection Router

Lock every AI call to the most capable Opus model (no downgrade) and route cost savings through prompt caching, batch APIs and context engineering instead of cutting quality.

$15
Inspect →
AI & LLM Skill

Prompt Architect

AI image and video prompt builder that guides users from a rough vision to a copy-paste ready…

$15
Inspect →

Agents 1

Questions · still in the air

Catch what's on your mind.

the air is clear. nothing between you and the forge.
catch a spark: the forge will answer

  1. I am new to Claude Code, is this the right shelf to start?

    It is the shelf about working with Claude itself. Claude Agent Template Library and Context Driven Development teach the structures; if you want a packaged starting point instead, the Brain ships the whole system pre-wired.

  2. What is context engineering and why does it matter?

    An LLM is only as good as what it holds in view. These skills encode how we keep Claude on task across long work: what loads when, what stays out, how memory and rules persist, the difference between a demo and a system.

  3. Can I measure whether my agents are actually good?

    Yes: Agent Eval Suite Langsmith builds evaluation runs for your agents: test cases, scoring, regression checks. You stop judging agents by vibe and start judging them by results.