OpenAI Codex Now Works from Anywhere (Dispatch Killer?)

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

Source video:
- Title: OpenAI Codex Now Works from Anywhere (Dispatch Killer?)
- URL: https://www.youtube.com/watch?v=9N1ky5Y_fPc
- Topic: Codex + Claude Workflows
- My current learning frame: Pair your own phone and desktop Codex, then from your phone start a session in a specific project folder and have it edit one real file, confirming the change mirrors on desktop and triggers a completion notification.
- Why this matters: New playlist item from Paul J Lipsky; queued for transcript-backed review, topic mapping, and a practical learning artifact.

Transcript anchors from this exact video:
- 0:00 / Evidence 1: "OpenAI has just enabled mobile access to Codex through the ChatGPT app, and it has honestly blown me away. It is so much better than I thought it would be. So, let me show you the setup process..."
- 2:27 / Evidence 2: "really cool. Okay, so you can see over here on the left all the projects on the desktop version and inside the Codex app, you can see the same projects. This is really cool. Okay, so let's actually..."
- 4:07 / Evidence 3: "to connect up with the mobile version of Codex?" That never came up. I had the screen open on my phone telling me, you know, trying to link up with Codex desktop app, but it wasn't doing anything."
- 5:43 / Evidence 4: "has full computer use enabled. So, it would be able to open up apps and click around and control them even if it's an app that doesn't have a native integration with Codex. And of course, it has..."
- 7:16 / Evidence 5: "creating a school community for AI enthusiasts, people who are looking to build AI agents out like Codex or Claude Co-work, and not necessary or not really coders or people who are developers, but just regular knowledge workers..."

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 routing matrix for when to use Codex, Claude, browser checks, or manual review.
5. Include:
   - a plain-English definition of the core idea
   - a diagram or structured model using this sequence: Inspect -> Plan -> Edit -> Verify -> Review -> Route
   - 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 "OpenAI Codex Now Works from Anywhere (Dispatch Killer?)", not a generic Codex + Claude Workflows 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.