Run the Framework End-to-End

In this exercise you run the AI Workflow Framework end-to-end yourself, live in class. Starting from a pre-built Workflow Requirements, you invoke /design, /build, /test, and /run on a Competitive Intelligence workflow — shipping a competitor-research skill and competitor-brief agent that produce a structured brief on a real competitor. In a follow-up session, you’ll evolve that workflow into a self-improving system.

Lesson: Ship a Workflow Using the AI Workflow Framework

Run the framework end-to-end yourself in Cowork (or Claude Code — same slash commands). Starting from a pre-built Workflow Requirements, you invoke /design, /build, /test, and /run — generating a competitor-research skill and competitor-brief agent from your approved spec, then running the workflow on a real competitor. Watch a structured context file get produced on the first run.

Hands-on assignment

Starting point: a pre-built Workflow Requirements (download below). Ending point: a shipped skill + agent producing a brief on a real competitor.

1. /design — Turn the requirements into an approved Design Spec (plan mode, collaborative). See the Design step docs.
2. /build — Generate the competitor-research skill and competitor-brief agent from your spec. See the Build step docs.
3. /test — Validate the building blocks before trusting them with real input. See the Test step docs.
4. /run — Invoke the workflow on a real competitor; watch knowledge/competitors/{name}.md emerge. See the Run step docs.

Download the Workflow Requirements

The Step 2 (Deconstruct) artifact is pre-built so we can spend class time running the rest of the framework on it.

Download the Competitive Intelligence — Workflow Requirements (.md)

Set up your workspace before class

Do these three steps in the folder where you run Cowork or Claude Code:

1. Create the workflow folder. Inside your workspace, create a folder named outputs, and inside it a folder named competitive-intelligence-brief.
2. Save the download as requirements.md inside that folder, so the full path is outputs/competitive-intelligence-brief/requirements.md. (Rename the downloaded file — the framework skills look for requirements.md.)
3. Create the manifest. In the same folder, create a file named workflow.yaml and paste in exactly this:

workflow: competitive-intelligence-brief
display_name: Competitive Intelligence Brief
description: Research a competitor's recent moves and produce a structured brief plus an updated knowledge file
definition_type: Step-Decomposed
status: under-development
trigger: Manual on demand, or scheduled per competitor
owner: Workflow operator
current_step: 2
last_updated: 2026-07-06
artifacts:
  requirements: outputs/competitive-intelligence-brief/requirements.md

The manifest is the small file every framework step reads first — it tells /design where your Workflow Requirements live and that Step 2 is already done. When class starts, you’ll run /design and it will pick up right where the pre-built requirements leave off.

What you’ll walk away with

• A competitor-research skill and a competitor-brief agent installed in your workspace, ready to invoke any time
• A populated knowledge/competitors/{name}.md file on a real competitor — the seed for the self-improvement work later in the course
• First-hand reps on every framework step as a chainable slash command (/analyze, /deconstruct, /design, /build, /test, /run, /improve)

Lesson: Recognize When a Workflow Needs to Improve

A brief, conceptual preview of Step 7 of the framework — Improve — anchored to the workflow you just ran. Identify the three signals that tell you a running workflow needs to evolve: hypotheses that never confirm, edge cases where the schema breaks, and drift as your priorities evolve. Improve is the step that never ends — and in the follow-up session, you’ll actually do the iteration.

Lesson: Evolve Your Workflow Into a Self-Improving System

Take the workflow you just shipped and evolve it into a system that gets sharper every time it runs. Apply Karpathy’s “LLM Wiki” pattern to its structured context file — structure it with Rules / Facts / Hypotheses sections, implement an ingest / query / lint learning loop, and schedule the workflow to run daily without you. By session end, your workflow’s outputs feed a self-improving knowledge base of competitor intelligence — Step 7 (Improve) in action.