I cut my GPT-4 API bill by 60% without changing my output quality. Here's how.

Most developers are burning money on AI tokens because of one habit: writing prompts like they're talking to a person.

The fix is structural prompting — and it's not complicated.

Here's the framework I use for every prompt I write:

1. Role + Context (10-15 tokens)

Don't say "You are a helpful assistant." Say exactly what you need:

"You are a senior TypeScript developer reviewing code for production readiness."

2. Task + Constraints (20-30 tokens)

Be specific about the output format and scope. Vague input = verbose (expensive) output.

"Review the following function. List only the issues that would cause bugs or security vulnerabilities. Max 5 items."

3. Output Format (10-20 tokens)

Defining the format upfront eliminates filler text:

"Respond as a JSON array of objects: { issue, severity, fix }"

This alone cut my average prompt response from ~800 tokens to ~200 tokens. Same quality. 60% less cost.

The real leverage is when you chain these into reusable templates for your team — so nobody is winging prompts ad hoc and burning budget.

That's what PromptStack is — a library of tested, production-ready prompt packs and AI workflow systems for developers and founders.

If you've been spending more on AI than you want to, check it out.