Stop Overpaying for AI: My Real Workhorse plus Specialists Stack

Описание: This video breaks down how I currently split tasks across multiple AI models to get speed, safety, and quality without overspending.

GLM 4.7 is my primary workhorse because it delivers the best performance to cost ratio. It handles the majority of everyday development tasks reliably and consistently.

Opus 4.5 is used only when deep back end logic is required. It performs extremely well, but it is not used by default due to cost considerations.
GPT-5.2 Codex is reserved for security audits and debugging. This is where Codex models shine, especially for reasoning, security validation, and exploit level analysis.

Gemini 3 Pro is used selectively for front end work when the other models do not fully execute the task as expected.

The key takeaway is to avoid locking yourself into a single provider or tool. Models evolve quickly, pricing changes, and flexibility matters.

Chapter Outline (YouTube Chapters)
00:00 – Introduction and AI model stack overview
02:18 – Preferred CLI tools: Factory AI Droid and Claude Code
04:15 – Beginner recommendations: Open Code and Kilo Code
06:02 – Critique of Google Anti Gravity
08:50 – Pricing analysis and Z.ai coding plans
11:00 – Benchmark suite score overview
12:15 – Test 1: Sonic platformer functionality
14:50 – Test 2: macOS Big Sur desktop simulation
17:55 – Test 3: Orbital solar system simulation
19:50 – Reasoning and logic task performance
21:18 – Conclusion and final recommendations

Tools Mentioned in This Video:

Claude Code
Factory AI Droid
Open Code
Kilo Code
Google Anti Gravity

Additional playbooks and the full benchmark suite are available on my website under the Resources section: https://mediadatafusion.com/resources

Affiliate and Resources
GLM Coding Plans (best value for cost to performance)
https://z.ai/subscribe?ic=6ZGVEFSWGY

Explore Free Tools by Kit Utility
https://kitutility.com

Connect With Me:

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  / jeremy-grove-mediadatafusion  

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