What PromptBase is
PromptBase is a marketplace for buying and selling prompts. The model works like a stock photo library: prompt engineers create optimised prompts for specific tools (Midjourney, DALL-E, ChatGPT, Stable Diffusion) and sell them at prices typically ranging from $2 to $10. Buyers browse by category, purchase prompts, and use them as-is or as a starting template. The value proposition is curation and community testing — the prompts on PromptBase have been used and refined, and the best ones consistently produce good outputs for their target tool. For image generation in particular, where prompt engineering is a craft skill, buying a tested Midjourney prompt can save significant trial and error.
What PromptIt does differently
PromptIt solves a different problem: it doesn't sell you someone else's prompt — it builds a structured prompt from your idea, personalised to your saved profile and the specific task you're trying to accomplish. The workflow: you type a short, rough description of what you want ('write a cold email to get a meeting with a potential investor'). PromptIt takes that raw input plus your saved context (your profession, your project, your tone preferences, your audience) and generates a fully structured ROLE/CONTEXT/TASK/CONSTRAINTS/FORMAT prompt. The output is a prompt built around your specific situation — not a generic template someone else wrote for a different use case.
The core philosophical difference
PromptBase is static; PromptIt is dynamic. A PromptBase prompt was written once for a general use case. It works well if your needs exactly match the scenario the prompt author had in mind. If they don't — your industry, your audience, your specific constraints, your tone — you need to modify it anyway. PromptIt generates a fresh prompt for your specific situation every time. You don't need to understand prompt engineering to use it — you just describe what you want in plain language, and PromptIt handles the structure. The result is a prompt that reflects your actual context: your project, your audience, your goals.
When PromptBase is the right choice
PromptBase is most valuable for image generation tools like Midjourney and Stable Diffusion, where prompt quality has enormous impact on output quality and where the craft of writing image prompts is genuinely specialised. Community-tested Midjourney prompts for specific aesthetics (architectural visualisation, character design, product photography) are often worth buying if you need consistent results without spending hours on prompt iteration. For niche ChatGPT use cases where you want a tried-and-tested prompt for a specific application — a particular business analysis framework, a very specific writing style — PromptBase can surface quality options that might take you time to develop independently.
When PromptIt is the right choice
PromptIt is the right choice when the prompt needs to be about your situation, not a generic scenario. If you are drafting a business document, writing a marketing piece, analysing data, coding a feature, or researching a topic, the prompt that works best is one that knows who you are, what you're building, who your audience is, and what constraints you're operating under. No PromptBase listing can capture that context — it doesn't know you. PromptIt does, because you've saved your profile once and it uses that context every time. The practical result: you type a sentence and get a prompt that would have taken a skilled prompt engineer five minutes to write manually.
The complementary view
These tools are not competing for the same use case. A professional using AI daily might use PromptBase to buy a specialised Midjourney prompt pack for a design project and use PromptIt every day for text-based AI tasks. The two tools target different workflows: PromptBase: specialised, visual-generation, community-sourced, one-time purchase model. PromptIt: personalised, text-generation, continuously generated from your own ideas, subscription model. Choose based on what problem you're solving, not on which tool sounds better in the abstract.