The bait, then the rug-pull.
What if your notes app could also write the notes? Stephen G. Pope opens on the bold claim then immediately delivers: Shockwave, his free open-source Obsidian replacement, ships with an AI agent that edits documents inline, loads skills from GitHub repos, manages API secrets, and syncs the whole workspace to GitHub.
Where the time goes.
01 · Intro to Shockwave
Hook and feature promise: free, open-source, AI agent built in, GitHub sync.
02 · Notes, Links & Graph View
Obsidian-parity demo: sidebar notes, internal links, backlinks, and graph view.
03 · Integrated AI Agent Setup
Settings walkthrough: provider, model, API key, system prompt, global/workspace skills, secrets manager.
04 · Using the Agent in the Editor
Select text, prompt agent to list top coding agents in 2026, result inserted inline. Follow-up: 'be more concise' — agent modifies in place.
05 · Downloading & Using Skills
Clone a marketing skills GitHub repo, load content-strategy skill, agent walks through a content strategy interview.
06 · AI Thumbnail Generation
Paste YouTube URL, agent fetches thumbnail, Gemini analyzes it, Key API regenerates with the creator swapped in, result drops into the document.
07 · Building New Skills
Agent reads Scrape Creators API docs and secret, builds a new YouTube report skill, self-corrects two errors, then fetches top 10 Claude Code videos into a document.
08 · GitHub Sync Across Devices
Create a GitHub repo from Shockwave, auto-sync files, live two-way sync demo — edit on GitHub, see change appear in Shockwave instantly.
Visual structure at a glance.
Named ideas worth stealing.
Skill-as-tool pattern
Agent skills are loaded from GitHub repos as structured instruction sets. Any skill installed becomes a callable tool the agent invokes automatically when the task matches.
In-context skill generation
Give the agent API docs plus a secret key, ask it to build a skill. The agent writes the skill code, stores it, and makes it immediately callable — no manual coding required.
Lines you could clip.
"Makes it a lot nicer than having to move to different apps or going to your terminal and running these different things in Claude Code and trying to get it to integrate with these files somewhere else."
"You don't have to pay for any external services."
Things they pointed at.
How they asked for the click.
"If you want to learn how to build out this type of software where you integrate AI agents directly into your own custom software, I walk through how to build this app step by step inside the AI Architects."
Soft sell at the end. Mentions community, a beginner-to-expert AI product engineering course, and daily live replays. Non-aggressive, product-first positioning.
Word for word.
What embedded agents actually fix in a notes workflow.
The problem with combining AI and notes is not the AI — it is the gap between where you think and where the AI lives.
- Context-switching between a notes app, a terminal, and an AI chat window is where most workflows break down; unifying them in one surface eliminates the friction, not the capability.
- Loadable skills let the same AI agent specialize without retraining — a content-strategy skill, a thumbnail-generation skill, and a YouTube-data skill all run through the same model but behave like distinct tools.
- Giving an agent access to API documentation and secrets lets it build its own integrations on demand; the resulting skill is a reusable artifact, not a one-off prompt that disappears after the session.
- Agent self-correction is a meaningful reliability feature: when the YouTube skill failed twice on first run, the agent diagnosed and fixed the error without human input before executing successfully.
- Using GitHub as a sync backend costs nothing and adds version history, branching, and team access as a side effect — no external sync service required.
- Inline editing — where output appears directly at the cursor in the document rather than in a chat panel — changes how you interact with AI output, from paste-and-fix to generate-and-continue.
- Secrets management inside the tool is what makes sharing agent workflows with a team practical; without it, every collaborator has to manually configure their own credentials.






































































