title: "Beyond the Hype: A Look at That 'Google Best Practices' Prompt Generator" date: "2024-04-27" excerpt: "You see a tool claiming to channel Google's prompt engineering wisdom? I did too. Had to check it out. Here are my candid thoughts on whether it lives up to the hype and if it can genuinely help you write better prompts."
Beyond the Hype: A Look at That 'Google Best Practices' Prompt Generator
Let's be honest, the whole AI prompt writing thing can feel a bit like trying to conjure magic sometimes, can't it? One minute you're getting exactly what you want, the next you're wrestling with the same query for the tenth time, tweaking a word here, adding a phrase there, just trying to get the model to understand what's in your head. We’ve all been there. And naturally, the internet is flooded with "ultimate prompt lists" and "secret formulas." Most of it feels pretty generic after a while.
So when I stumbled across a mention of an agent designed to generate prompts quickly by drawing on, get this, Google engineer best practices? My ears perked up. Skepticism, yes, absolutely – how exactly do you bottle "Google best practices" into a prompt generator? But also, curiosity. Anything that promises to make writing better AI prompts less of a chore, or perhaps shed some light on prompt writing best practices from a supposedly authoritative source, is worth a look in my book. Especially if it means potentially saving time writing prompts and getting closer to generating efficient prompts right out of the gate.
I navigated over to their corner of the web (the one linked, you know the one). The idea is straightforward enough: feed it a basic concept, and it spits out a more refined, supposedly "Google-approved" prompt. The promise is generating high-quality and efficient prompts without the manual grind.
Does it work? Well, that's the million-dollar question, isn't it? My experience was... interesting. It's not a magic bullet, let's get that out of the way. No tool will ever be. But what I did notice was a certain structure, a way of framing the requests it generated, that felt... deliberate. Less like a random mashup of keywords and more like something built with a clearer understanding of how these large language models seem to process instructions.
It nudges the output prompt towards including elements you should be thinking about anyway – specifying format, adding context, perhaps even hinting at negative constraints without explicitly calling them that. It felt less like a simple text expander and more like a subtle guide embedded in the output. For someone who's relatively new to trying to improve AI output with prompts beyond the basic commands, or even for those just looking for different angles on how to write better AI prompts, this could be a genuinely helpful starting point.
Is it channeling the collective wisdom of every brilliant mind at Google? Probably not in a direct, person-to-model kind of way. The term "best practices" itself is a bit nebulous in the wild west of AI prompting right now. But if "best practices" means structuring prompts in a way that tends to yield more predictable, higher-quality results based on empirical observation (which Google surely does a lot of), then maybe there's something to it.
Ultimately, what this agent offers is a shortcut to a more structured approach to prompt engineering. It won't replace your own understanding or the need to iterate, but it might give you a solid, well-formed first draft that's miles better than the vague sentence you might start with. For anyone who finds themselves staring at a blank input field wondering how to write a good prompt that actually works, this tool provides a concrete example to build upon. It's not the final answer, but it could definitely be a productive next step. Worth experimenting with if you're tired of the prompt writing guesswork.