AI Strategy
What Using Fable 5 Taught Me About Return on Token Investment
The short version
- Strategy is everything with AI. Not the tool, not the prompt. Fable 5 is vision-led, so it works backward from an end point, and naming that end point is the real work.
- Spend cheap tokens first. Lock the vision on the leaner models (Haiku 4.5, Sonnet 5, Opus 4.8), then run Fable 5 clean on a full tank.
- The metric that matters isn't usage, it's aim. Return on Token Investment: the people who win with AI aim it best, they don't use it most.
I spent 75% of my time with Claude's Fable 5 not using it. That was the plan, and here's why.
Strategy is everything with AI. Not the tool, not the prompt. The strategy. Fable 5 isn't tactics-led, it's vision-led. It works backward from an end point, the way real transformation does.
And here's the thing. "Start with the goal" sounds easy, everyone says it. But if you don't know your end point, you're sunk, and if you wing it, you're just going fast to nowhere.
The hard truth is that naming the real vision is the hardest part, and it's only going to matter more as AI adoption deepens. Everyone can write a prompt. Few can define the roadmap that the prompt is meant to serve.
Through my strategy framework, I locked the endpoint before I ever opened Fable 5. I ran it first on the leaner models, Haiku 4.5, Sonnet 5, and Opus 4.8, each chosen for its strengths and its token rate. Cheap tokens up front bought a clear vision and a full tank to run Fable 5 clean.
From there, it ran like an assembly line. I set the goals and boundaries, Opus 4.8 shaped each prompt from the Fable 5 documentation, and Fable 5 was built inside the right project with updated working memory. I reviewed every output and passed my feedback back to Opus for the next pass. Around and around it went.
In 8 hours
Every one of these exists because the strategy came first.
- A live MCP connector running a subscription (a small SaaS)
- A financial model
- A full brand and website
- A legal foundation
- A marketing engine
- An operations app
They exist because the strategy came first.
The metric worth stealing
ROTI, Return on Time Invested, comes from lean and agile. I'm changing one word: Return on Token Investment.
Since writing this I built the calculator version of it, so you can stop estimating. Price your own prompt in the ROMTI simulator: your real prompt, your model, and the costs that never appear on the pricing page.
The people who win with AI won't be the ones who use it most. They'll be the ones who aim it best.
Strategy is everything with AI. The tool doesn't transform anything. A vision does.
That's the work I do, and I'd love to help you find your own R.O.T.I. 📈 Now it's your turn: what did you build with your Fable 5 sample, and what did it teach you?
Questions people ask about this
Straight answers, in case you skimmed.
What is Return on Token Investment?
It's a spin on ROTI, Return on Time Invested, a metric borrowed from lean and agile. Changing one word to Return on Token Investment reframes the goal: the win isn't using AI the most, it's aiming it best, so every token you spend serves a vision you've already defined.
Why run cheaper Claude models before Fable 5?
Because strategy should be locked before you spend on the heaviest model. Running Haiku 4.5, Sonnet 5, and Opus 4.8 first, each chosen for its strengths and token rate, buys a clear vision cheaply and leaves a full tank to run Fable 5 clean.
Does strategy really matter more than the tool with AI?
Yes. Everyone can write a prompt, but few can define the roadmap the prompt is meant to serve. The tool doesn't transform anything. A vision does, and naming that real vision is the hardest and most valuable part.
Sources & Notes
- ROTI (Return on Time Invested) is a feedback metric from lean and agile practice, most often used to rate whether a meeting or retrospective was worth the time spent. "Return on Token Investment" is my adaptation of it.