In this 2026 update, the presenter demonstrates five advanced prompt-engineering tactics—recursive brainstorming, web→JSON extraction, iterative feedback loops, model judging, and LM retrieval—using practical examples and a free playground to test and visualize results. The video links four foundational prompt pillars (role, task, context, rules) to automation techniques that improve idea discovery, structured data use, and retrieval accuracy.
– Recursive Brainstorm: Automate multi-level idea trees, visualize nodes, score ideas, and export JSON for deeper, unexpected sub-ideas.
– Web→JSON: Instruct models to search the web and return structured JSON for use in carousels, dashboards, and product comparisons.
– Feedback Loop & LM Judge: Iterate critiques to refine outputs and use a separate judge model to select, synthesize, or compare multiple model responses.
– LM Retrieval & Prompting Tips: Use semantic routing to navigate structured content without vectors; practical tips include starting with criticism, mixing concepts, documentation injection, and learning-by-building.
Quotes:
The better you prompt AI, the better results you get.
Imagine a magic coin that can be both heads and tails at the same time while it’s spinning.
Before you respond, critically analyze my idea — be brutally honest.
Statistics
| Upload date: | 2026-01-09 |
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| Likes: | 317 |
| Comments: | 33 |
| Statistics updated: | 2026-01-11 |
Specification: This Is What Actually Works in 2026!
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