u/ImaginationUnique684

Quick frame I've been using for AI-assisted work that actually scales.

When the task is new → prompt. You're discovering what the work looks like. The model is your sparring partner.

When the task repeats → make it a skill. Package the context, scripts, criteria, fallback path. You stop explaining everything from scratch.

When the skill is stable → move the deterministic parts to gates. Formatter for code. Linter for forbidden phrases. Schema for output shape. The model can still draft; the gate decides whether it passes.

When the gates are stable → reduce the LLM's responsibility. Often down to 20% of the workflow. The system handles the rest.

The point isn't "use AI less" — it's that the model should handle the part where ambiguity is genuinely useful, not the part that's already measurable.

Self-check I run on any workflow that feels janky:

• What do I keep explaining to the model? → that's a skill
• What does the model keep judging by itself? → that's a gate
• If I removed the LLM, which parts of the workflow would still be clear? → those are real process

The first stage of AI work is prompting. The last stage is removing the model from most of the workflow.

That sounds backwards. It isn't.

Prompting is great when the work is still ambiguous. You're discovering what good looks like. You try a prompt, read the output, adjust, run it again. That's a good use of AI.

But once the workflow keeps coming back, and you're still explaining it to the model every time, you're not building capability. You're repeating yourself with a better interface.

The maturity curve I keep coming back to:

Prompt → Skill → Gate → System

• Prompt: discover what the task looks like
• Skill: package the repeatable parts (context, files, tone, scripts, criteria)
• Gate: move stable checks out of the model (formatter, linter, tests, schema, checklist)
• System: reduce the LLM's responsibility to where ambiguity actually remains

For code, this is uncontroversial: we don't ask the model whether the code passes — the gate decides. For content, people keep more of the workflow inside the prompt because it "feels less deterministic." Same principle applies. "Make it good" is a vibe. A gate is a standard.

Posted the full piece here: https://renezander.com/blog/your-ai-workflow-needs-less-ai/

Curious where the rest of you draw the line - which part of your AI workflow has stopped being a prompt?