Right now my Fable 5 burn rate is at maximum.
That screenshot is not a flex - it is a strategy. 30 agents running in parallel, 18 minutes, context window at 46.7k out of 1M tokens, 5-hour limit at 14%. That is what a real feedback loop looks like when you stop typing prompts and start building systems.
30 Agents. At the Same Time.
I am not running one conversation and waiting for a response. I am running 30 parallel agents simultaneously - deep-research agents, fetch agents, code agents, and plan agents all chained together and working on different parts of the same build at the same time. Look at the right panel in that screenshot: search agents, fetch agents, scope agents - each one pulling tokens, each one doing a specific job, each one feeding its output into the next phase.
That is not ChatGPT. That is an orchestrated agent loop, and Fable 5 is the framework that makes it work without the whole thing collapsing into noise.
What Fable 5 Actually Does
Fable 5 is my structured prompt framework. Five parts: Frame, Ask, Build, Loop, Execute. Instead of firing one-off prompts and hoping for the best, you build a structured conversation that feeds back into itself. Each output becomes the input for the next phase. The model carries context forward because you designed the loop to hold it.
When I am building code or wiring up an agent, the loop looks like this:
Frame - One precise sentence defining the exact problem. Not “build me an agent” - “build a Node.js endpoint that receives a PayPal IPN webhook, validates the transaction, and returns a signed time-limited download URL for a specific product SKU.”
Ask - Before writing a single line of code, I ask the model to identify every edge case, failure mode, and dependency. This is where most people skip ahead and pay for it in debugging time later.
Build - The model writes the code. Because Frame and Ask were precise, the output is tight. No hallucinated libraries. No missing error handling.
Loop - I run the code, paste the error back in, and the model fixes it in context. No re-explaining. No starting over. The loop carries the full build history.
Execute - It ships. Not “I’ll review this later.” It goes live, gets tested against the real environment, and the result goes into the knowledge base.
Thirty agents running that cycle in parallel. That is the screenshot.
Why I Am Pushing the Burn Rate Right Now
Here is the honest truth: I have access to this level of compute right now, and it is not going to stay this cheap forever. The models are getting better, the context windows are getting bigger, and the pricing is going to reflect that. The strategy is simple - build as much as possible while the cost-to-output ratio is still in my favor.
Every agent build I run right now is doing one of three things:
- Building something that ships - a page, a product, a pipeline that generates revenue
- Creating a reusable skill or framework - something I can hand to Morpheus, Neo, or Tank and they run automatically from that point forward
- Generating knowledge - golden moments, build logs, documented decisions that go into the knowledge base and make every future session smarter
The feedback loop is the key. I am not just burning tokens. I am compounding them. Each session teaches the system something it did not know before. Each build produces an artifact that reduces the cost of the next build.
The Cost Math
At current pricing, a session like that costs me a few dollars. The output - a working payment system, a new page, a documented agent skill - would cost hundreds of dollars in agency time or days of my own time without the framework. The ROI is not even close.
The 5-hour limit resets at 3:39 PM. I will be back at it.
Stay curious, my AI friend. Think like you are seven.
Want to learn the Fable 5 framework? It is on the Fable 5 Prompts page. And if you want to build something together, the Work With Me page is the place to start.
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Stay curious, my AI friend. It's the secret sauce - think like you are seven. - Ryan