How can prompt engineering actually boost a language model's creativity?

[MarkP]

I’ve been trying to fine-tune a small language model for a specific creative task, but I keep hitting a wall where the outputs feel repetitive and bland, no matter how I adjust the training data. It’s making me wonder if the whole approach of prompt engineering is just a clever way to mask the model’s lack of real understanding. Has anyone else felt that sinking feeling after weeks of tweaking, only to get mechanical-sounding results?

[Andrew_R]

That sinking feeling after weeks of tweaking is real. prompt engineering can feel like polishing a badge on a tired idea, while the core task stays stubbornly repetitive. Maybe the issue is the model capacity or the objective you optimize rather than the prompts alone.

[Evelyn_J]

From an analytic angle prompt engineering is only part of the loop you need to measure and iterate against data quality and the evaluation framework. If the outputs sound bland maybe the training data lacks true signal or the objective rewards novelty. It could be that you are chasing a local optimum rather than a general style.

[Jonathan.D]

Maybe you think prompt engineering is the whole map but the task itself might need a staged prompting plan that uses constraints and user feedback. It could be that the evaluation leans toward safety over novelty or that you are rating the wrong kind of creativity. I am not sure this will fix it.

[Kevin_S]

Prompt engineering is often pitched as magic but a lot of bland output means the problem runs deeper than the button presses. I would question whether the data and the objective align with creative variance rather than chasing a cookie cutter tone. Maybe the model is simply not a good fit for the task.

[Jacob.T]

Instead of chasing perfect prompts maybe shift focus to how you frame the user interaction and constraints. The issue might be a genre habit or reader expectations more than the model itself. prompt engineering remains a tool but the real challenge is designing a workflow that invites novelty.

[LunaA]

One more angle is to treat the outputs as drafts rather than finished pieces and to experiment with style experiments and reader feedback as a craft exercise. prompt engineering could be used to set a goal like tone or pacing but the wider craft choices come from you and your team. Do you think this framing changes what counts as success?