This Free Tool Runs 5 AI Coding Agents at Once

You are helping me turn one specific YouTube video into real, durable learning.

Source video:
- Title: This Free Tool Runs 5 AI Coding Agents at Once
- URL: https://www.youtube.com/watch?v=rhHjSrsv8as
- Topic: Creative Automation
- My current learning frame: Connect one of your repos to a multi-agent orchestrator, kick off three worktrees at once (a security review, a feature research task, and a bug fix from real feedback), and practice pushing all three to completion by responding only to input checkpoints.
- Why this matters: New playlist item from Sean Kochel; queued for transcript-backed review, topic mapping, and a practical learning artifact.

Transcript anchors from this exact video:
- 0:00 / Evidence 1: "One of the big pains for me with vibe coding is trying to keep track of everything that's being built or worked on. So, for example, I'm typically working on like three to five different agents. They're out..."
- 1:57 / Evidence 2: "like learn and review outputs like to the best of your ability. But then you inevitably reach this point where you are now starting to run multiple sessions at the same time. And when you get to this..."
- 4:06 / Evidence 3: "sometimes multiple agents that are out building different pieces of that. And then things like security reviews is like another really solid example. So again, this list isn't even really that exhaustive. And in this context, we would..."
- 6:01 / Evidence 4: "continue the build of this like agent refactor that I am doing. And so, it went off and it's doing this entire thing. So, it's calling sub-agents as it needs to, any of like the work that is..."
- 8:52 / Evidence 5: "and everything that's needed for the security review. And so, it's a really nice way to like manage all of these again. In this context, I have like four different sub agents moving at the same time. And..."
- 10:48 / Evidence 6: "running at the same exact time and they're starting to build tooling for us to do that in like a more effective way. The reason I like this is that it works natively with our actual like Claude..."

Your task:
1. Use the transcript anchors above as the primary source packet. If you add outside context, label it clearly as outside context and keep it secondary.
2. Create a source-check table with columns: timestamp, claim, what the demo proves, confidence, and what still needs verification.
3. Extract the actual teachable claims from the video. Do not invent claims that are not supported by the title, lesson frame, or transcript anchors.
4. Build a reusable learning artifact: A creative workflow board with critique criteria and review checkpoints.
5. Include:
   - a plain-English definition of the core idea
   - a diagram or structured model using this sequence: Brief -> Source -> Generation -> Selection -> Edit -> Taste Review
   - 3 concrete examples that apply the video idea to real agentic work
   - 2 failure modes the video helps prevent
   - a checklist I can use the next time I run Codex or Claude
   - one practical exercise with a clear done signal
6. Add a "learning transfer" section: what changes in my workflow tomorrow if I actually learned this?
7. Add a "source check" section that cites which transcript anchor supports each major takeaway.

Quality bar:
- Make this specific to "This Free Tool Runs 5 AI Coding Agents at Once", not a generic Creative Automation essay.
- Prefer operational examples, failure modes, and reusable artifacts over broad definitions.
- Call out uncertainty instead of smoothing over weak evidence.
- If evidence is weak, say what transcript segment or timestamp needs review instead of guessing.
- Finish with a concise artifact I could paste into my learning app.