Somewhere out there, a founder just typed:
“Write me a blog post about marketing.”
And then wondered why the LLM coughed up 800 words of the most generic oatmeal that looks and tastes like every other generic oatmeal AI generated content.
Listen, Microteam friend, that prompt might’ve worked in 2022, back when we were all just happy that robots could spell. But we’re well past those early days now. LLMs have leveled up, and your prompts should too.
If you’re still typing prompts like it’s a Google search bar, you’re missing out on the difference between “help me brainstorm” and “build me a business engine.”
The Evolution of Prompting
Let’s take a step back.
In 2022, LLMs burst onto the scene, and we prompted like toddlers that figured out making noise would get a response.
Back then, you entered:
“Write a business plan for my startup.”
marveled at the magical output, and prayed it wouldn’t start with “In today’s fast-paced digital world…”
But in 2022, the LLMs would generate very obviously AI generated content. I called it the “Subway sandwich” output. No matter what you ordered, it all tasted about the same. You could smell AI output a mile away.
Then came 2023: the Year of the Prompt Engineers.
Trying to break out of the boilerplate LLM outputs, suddenly, everyone had turned into part-wizard, part-copywriter, part-software developer.The idea was to put more craft into the prompts by “word coding,” inventing complex prompt formulas with names like CRISPE, CO-STAR, TACO, and the crowd favorite, “HELP ME DO MY JOB BECAUSE I’M TIRED.”
We had people swapping “RTF” for “CREATE” like it was the secret Konami code for better results.The internet was full of Do Anything Now (DAN) jailbreaks and 3,000-character “superprompts” that read like occult rituals.
Everyone had a “system prompt” they swore was 10x better than yours, even if it just added “act confident” to the top and “take a deep breath” at the bottom.
Don’t get me wrong, these more elaborate prompts represented a big step up from just typing a free-form train of thought. That was an important era. It taught us how to think with machines, not just talk at them.
A lot of the reason why we had to jump through verbal hoops was because the LLMs just a few years ago were stunted by small context windows (they could only remember or handle a relatively small amount of text), they didn’t have the reasoning models available today that could figure out what you meant by “how many b’s are there in blueberry”, didn’t have memory that could persist across chat sessions, and weren’t able to connect to third-party tools and additional capabilities such as search, deep research, or MCP-based systems.
But it’s 2025 now. And here’s the truth:
People are still typing a few sentences of off-the-cuff prompts because creating the more sophisticated prompts takes more brain power than people are willing to put in these days. LLMs have gotten vastly better with a much bigger context window, built-in reasoning, and ability to connect to search and third-party tools.
LLMs have gotten vastly better but people are still interacting with them as if they haven’t changed. The result is that most people are getting significantly less power from these systems than they otherwise should be.
AI is now everywhere. It’s embedded in Canva, Google Docs, Notion, ClickUp, your email drafts, your design boards, your code editors, your spreadsheets, your Slack threads, your brain (okay, not yet … but give it a quarter). The 2023-era Prompt patterns don’t matter as much when the prompt isn’t even visible anymore.
We’ve moved from prompting manually to prompting passively.You no longer have to tell AI to “act as a designer.” You are the designer, because you’re in a design tool (duh), and it’s just there, anticipating what you need next. Your operational context already provides some of the role / task / format instruction you had to be super specific about before.
Context windows have greatly increased. This means that the more powerful models now know more about your intent and existing information without you having to provide paragraphs of text to describe what you mean. They also make use of memory to keep track of prior conversations and can be provided with prior instructions or project configurations to have access to vital knowledge.
And beyond that?We’re already in the agentic era where prompts don’t just generate content… they trigger action.
A single instruction can now spin up autonomous bots that:
Draft the copy,
Schedule the campaign,
Launch the ads,
Monitor performance,
And send you a Slack update saying, “Hey boss, your click-through rate is up 27%.”
Welcome to the new frontier: the land of infinite leverage and infinite chaos.
So if your prompt style is still stuck in the “Hey please write me a…” era, you’re not just behind. You’re missing the opportunity to orchestrate systems that think, act, and scale for you.
That means you’re not getting leverage over labor, one of the fundamental tenets of Microteam Scalemaxxing.
Why This Matters
Microteams run on leverage, not labor. Prompting isn’t just about asking questions anymore. It’s about designing systems, frameworks, and results.
You don’t just talk to AI now. You train it. You contextualize it. You scale it. AI is part of your team, not some Google search replacement.
And if you’re still copy-pasting generic requests, you’re leaving exponential efficiency and scale on the table.
Every major LLM now publishes prompt playbooks
If you’re still winging it, you’re officially behind. The big model providers are pushing first-party prompt guides with concrete techniques (role/persona setup, structure/sections, examples, constraints, evaluation loops, JSON schemas, etc.). A few high-value starting points:
Google (Gemini) — Prompt design strategies for Gemini API, plus Google Workspace/Gemini PDF guide.
Microsoft (CoPilot and Azure OpenAI) — Practical prompt engineering techniques and system-message design guidance for production apps.
Cohere — Prompt engineering basics and docs for Command models (useful even if you’re model-agnostic).
Mistral — Prompting capabilities & system/user prompt guidance in the official docs.
TL;DR: The playbook is public now. No need to stash a prompt library or copy those DAN prompts anymore.
Moving Beyond the Basic Prompt: use Scalebrate’s free Prompt Optimizer Custom GPT
First, let’s save you from the “I don’t know how to write a really good prompt” problem.
We built a free Prompt Optimizer Custom GPT that takes your outdated prompts and supercharges them for 2025-level performance. The Custom GPT is free, hosted on ChatGPT, but the output prompts are usable on any LLM.
It follows the latest best practices for ChatGPT, Claude, Gemini, and Perplexity to make sure your requests are structured, scoped, and scaled to deliver smarter results.
It’s like Grammarly for prompts but instead of fixing your commas, it fixes your thinking.
And yes, the logo is a wizard hat because it can turn any Muggle into a GPT Wizard, or at least a basic entry level Hogwarts student.
Past you: “write a press release.”Future you: paste that into the Prompt Optimizer GPT, and get a revised prompt that provides fully structured objectives, role, audience, format, examples, constraints, and success checks generated for you in one pass and optimized for the latest LLM best practices. No need to remember any of the prompt patterns, copy from a library, or incant any magic…. Other than Wingardium Leviosa for your prompts of course.
Example: Basic vs Optimized
The 2022 Prompt:
“Write a social media post about my startup launch.”
The 2025 Optimized Prompt (via Prompt Optimizer):
“Act like a professional startup marketing strategist and social media manager. You specialize in creating high-impact, viral social media launch posts that blend storytelling, brand positioning, and emotional engagement.
Your objective: Write a powerful, inspiring, and shareable social media post announcing the launch of my startup. The goal is to build anticipation, attract early users or investors, and clearly communicate our mission, vision, and what makes us unique.
Follow these steps:
1. **Brand Essence:** Begin by introducing the startup name, industry, and core mission in a way that immediately captures attention.
2. **Storytelling Hook:** Share a brief origin story or the “why” behind the company — what problem inspired the creation of this startup.
3. **Value Proposition:** Explain what the product or service does and how it makes people’s lives better, easier, or more efficient.
4. **Emotional & Social Connection:** Use aspirational and motivational language that aligns with the audience’s ambitions or pain points.
5. **Call to Action:** End with a clear invitation — to visit the website, join a waitlist, try the beta, or follow the journey.
6. **Tone & Style:** Keep the tone inspiring, confident, and human. Avoid corporate jargon. Include emojis or hashtags strategically if appropriate for LinkedIn, X (Twitter), or Instagram.
7. **Output:** Write 2 variations — one concise and catchy (for X/Twitter) and one longer and story-driven (for LinkedIn or Instagram).
Take a deep breath and work on this problem step-by-step.”
The difference?One sounds like someone who just discovered GPT wrote it.The other sounds like you actually want to get value from the LLM.
Let’s Go, We’re Already Half-way Through the 2020’s.
Prompting isn’t a “hack” anymore, it’s a skill.And like any skill of value, it compounds the more we use it and the better we get.
Stop treating AI like a vending machine.Start treating it like your smartest teammate.
Because you don’t have time to prompt like it’s 2022.
👉Try the free Prompt Optimizer GPTand start prompting like a Microteam founder who actually gets it.