4 Free Models, 1 Winner

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

Source video:
- Title: 4 Free Models, 1 Winner
- URL: https://www.youtube.com/watch?v=gAQasQoPuE8
- Topic: Creative Automation
- My current learning frame: Recreate the experiment: run two free models in separate OpenCode sessions on the identical LLM-refined portfolio brief, then a second round demanding multi-file structure and cited research, and write a short verdict on which small design details separated the winner.
- Why this matters: New playlist item from CodingLab; queued for transcript-backed review, topic mapping, and a practical learning artifact.

Transcript anchors from this exact video:
- 0:42 / Evidence 1: "side, each one building the exact same thing. So, let me make the directory, move into it, and from here I'll run three separate instances of Open Code. One dedicated to each model I want to compare. So,..."
- 3:15 / Evidence 2: "anything it needs to know before it starts building. That way, the prompt that finally goes to the models is as clear and complete as it can be. All right, the prompt is ready, so let's go. All..."
- 4:58 / Evidence 3: "uses it under the hood by default. So, that's model number one locked in. I'll scroll down, paste in the prompt, "Build a website for me based on the following information." And then, just let it go and..."
- 11:17 / Evidence 4: "one that actually works, so I can slot a proper fourth contender into that empty spot. The replacement comes from the Open Code lineup, and Mimo gets brought in here, too. Mimo actually sounded really promising to me."
- 14:20 / Evidence 5: "and design guidelines to the model. If I can feed it that kind of structured design knowledge, then it's not just guessing at what looks good. It's working from actual principles, and the output should feel a lot..."
- 16:39 / Evidence 6: "open-source project. Okay, I realized Oh, this is the open-source project, so The Okay, these are the things that these two found. How on this did I not know all this earlier? This is going to save my..."
- 19:31 / Evidence 7: "available to it, I should get something that feels intentional and distinctive instead of yet another safe, generic-looking page like the ones we've been getting. And in case you don't know what sub-agents are, it's basically like taking..."

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 "4 Free Models, 1 Winner", 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.