- Caveminds: 7-9 Figure Founder AI Community
- Posts
- Prompt Engineering Mastery: Everything that Founders & Teams Need to Know
Prompt Engineering Mastery: Everything that Founders & Teams Need to Know
Level up your prompt engineering game. No matter if you're using ChatGPT, Bard, Claude an in-house LLM or any AI.
Candyd Mendoza & Benson Sung
October 13, 2023
In today’s Future Friday…
Revolutionize Your Team: Why Employee Reskilling is KEY
The Fine Line Between Blind Prompting and Masterful Prompt Engineering
Why Your Business Needs a Prompt Engineer: Insights from Experts and Strategies to Hiring AI Specialists
Inside the Mind of a Prompt Engineer & Should You Hire One?
The Curation of All The Tools You Need To Be A Master
GPT-4V (ision) got everyone jaw-dropping
Caveminds Podcast Ep. 5 — Are GPT Wrapper Tools Real Businesses?
Read Online and listen to the audio version.
Join 9,000+ founders getting actionable golden nuggets that are tailored to make your business more profitable.
TOPIC OF THE WEEK
DALL·E 3
Beyond Blind Prompting: The Future of AI in Business Reskilling
You’ve probably realized by now that in order to succeed with AI, you must invest in people and training as much as you invest in technology.
Caveminds founder Benson project that AI will completely transform the way companies build organizations and teams by late 2024 or early 2025.
A skyrocketing demand for AI and big data skills, marking a significant shift in reskilling priorities for businesses.
It's shot up to third place in business reskilling priorities in the Future of Jobs Report 2023 – 12 spots higher than core skills.
Work time distribution by industry and potential AI impact
🏆 Golden Nuggets
The AI talent landscape is in flux. Those who start reshaping their teams now, training them to work hand-in-hand with AI, are the ones who'll be leading the pack.
Businesses are putting their money where their mouth is, planning to invest 9% of their reskilling efforts in AI and big data.
Demand for AI and big data specialists has skyrocketed, with companies prioritizing them more in their reskilling initiatives than other skills.
The Problem
DALL·E 3
No one has totally mastered ChatGPT or other LLMs – yet. It’s still a wild west, where most people are just blind prompting.
Blind prompting is a method developer and coding genius Mitchell Hashimoto described as “
Here’s an example of blind prompting in content creation:
Blind Prompt: "Write an article."
Issues: It's too vague. The AI has no context, topic, audience, or purpose to guide the content creation.
Result: A generic, unfocused article that may not be useful or engaging for any specific audience.
Just check the differences starting with the “write an article” prompt once we improve it and specify more of what we aim to achieve.
Quite good, huh? — And this was just a blind prompting improvement! Imagine what you can achieve but methodologically approaching this subject.
ℹ️ Why This Matters Today
A staggering 40% of all working hours across industries could be influenced by large language models like ChatGPT.
Language tasks could see a productivity boost of 65% with the right AI integration.
Without understanding the nuances of prompting, your business might hurt soon.
So when it comes to prompting, it’s gonna be absolutely crucial for your business. But make no mistake:
The good news is there’s a way to craft prompts in a more controlled approach that can lead to more predictable and targeted outputs: Prompt Engineering.
But be warned, prompt engineering is more rigorous and systematic. Hashimoto argues that it should be based on experimental methodologies to ensure that interactions with AI are accurate and productive.
The Process of Prompt Engineering:
DALL·E 3
It starts with identifying a specific problem that needs solving.
A demonstration set is created, containing expected inputs and outputs to test the accuracy of prompts.
The prompts are then rigorously tested and refined to ensure they meet the expected standards of reliability and consistency.
The following are some of the best practices for prompt engineering:
Write clear and specific instructions
Guide language models towards sequential reasoning
Use separators and structural output
Use iterative prompt development
Use least-to-most prompting
Use self-ask prompting
Understand the problem
Incorporate safety measures
Integrate domain-specific knowledge
Enhance the performance of LLMs through the use of customized tools
We’re ready to unpack more: let us know in the comments if you’d like to know more about blind prompting vs. prompt engineering, and we’ll gladly do a deep!
⚒️ Actionable Steps
So, what's the game plan for business leaders?
Begin with dissecting existing job roles
Then deconstruct them into individual tasks
Identify which can be automated, which can be enhanced by AI, and which still need the human touch
Invest in reskilling your team and bringing in prompting specialists if needed
It’s a meticulous process but one that promises unprecedented efficiency and innovation. Here’s an example from Accenture on how to reinvent a customer service job, task by task.
Source: Accenture
CAVEMINDS’ CURATION
Prompt Engineers – Do Companies/ Need Them?
For now, the simple answer is a big, fat YES.
A year ago, the spotlight was firmly on AI-related software engineers. But the focus has shifted, and prompt engineers (yes, it’s a real job) are now the stars of the show.
In fact, 7% of respondents in Accenture's recent survey have added prompt engineers to their teams over the past year.
As generic AI adoption rises, more individuals with little to no coding knowledge are looking for no-fuss, no-code LLM solutions.
What this does is eliminate the need for a data scientist, one of our founders, Andrew, pointed out.
“Now we don't need someone to do, data engineering. We need prompters and prompters are a lot less money than a data scientist.
So, when you see the no-code solutions, and it's just like building on top, you're creating great prompts for your company.
And that becomes a set of, scripts and procedures and documents that you can house.”
A prompt engineer assesses the task at hand, pinpoints the essential info, and then crafts prompts that steer AI models to deliver accurate and consistent results that can be reproduced.
With their deep understanding of human language and AI systems, prompt engineers ensure that businesses aren’t just using AI but are optimizing it to its fullest potential.
🏆 Golden Nuggets
AI is powerful, but it needs direction. Founders should consider investing in prompt engineering experts to create structured, tested, and refined prompts that elicit reliable and consistent responses from AI.
For how long these roles will be relevant in this fast-moving world, we don’t know.
Some jobs might phase out, some will evolve, and hey, we'll even see other brand-new jobs popping up (e.g., linguistics experts, AI quality controllers, AI editors).
💰 Impact on Your Business
Prompt engineers empower businesses to:
Build better conversational AI systems
Enhance accuracy and relevance
Improve decision-making capabilities
Deliver personalized experiences
Harness the full potential of AI
Inside the Mind of a Prompt Engineer
I spent a few hours with Albert Phelps, the in-house "prompt engineer" at @AccentureUK
He spends his time helping large companies understand and coax AI tools, and training others
He tried to automate my editor with GPT-4...
Did he succeed?
— Conrad Quilty-Harper (@Coneee)
3:46 PM • Jul 5, 2023
Albert Phelps, a prompt engineer at Accenture, believes everyone will wear the hat of a prompt engineer at some point. Scale A.I. prompter Riley Goodside thinks so too.
“A lot of people foresaw that every company is going to have to hire a prompt engineer and you’re going to need them to be the shaman that speaks to the model that interpret what you want to do. That hasn’t panned out. It’s something that in the future, everyone will be doing, but nobody’s going to consider it their job.”
What’s Ahead? (Advice for Prompt Engineers)
Randall Hunt, who delved deep into prompt engineering through structured learning and hands-on experimentation with AI models at Caylent, encourages aspiring prompt engineers to stay updated on the latest research developments on LLMs.
"I think anyone who claims they're an expert in this space should caveat their claim with something like, 'This is a rapidly evolving field and the advice that makes sense today may not be the same as the advice that makes sense in six months. I'd even go so far as to say there are not yet any true experts in this space.”
He also stresses the importance of tokenization in grasping the workings of LLMs.
“As models grow in context, shrink in per-token costs, and improve in throughput, prompt engineering advice will need to adapt."
OUR CHERRY-PICKED TOOL CURATION
PromptInterface.ai - A web-based SaaS interface that offers prompt engineering solutions. It can create personalized assistants for users using GPT-4 prompts. Like Promptly Generated, it also has a prompt editor, tester, and a set of pre-writter prompts.
Promptly Generated - A valuable tool for anyone who is using LLMs. It has a library of pre-written prompts, a prompt generator that can help users to create custom prompts. Plus, it’s got a prompt editor that helps users to refine their prompts and a prompt tester that helps users to test their prompts on LLMs.
Query Vary - A powerful and flexible platform that can help researchers and engineers to efficiently and effectively evaluate large language models. It can also be used to evaluate the performance of LLMs over time, or to compare the performance of different LLMs on the same task.
HoneyHive - Helps developers test and evaluate, monitor and debug their LLM applications. Teams use HoneyHive to confidently go from prototype to production and continuously improve their LLM apps in production
Visit our Cyber Cave and access the most extensive tool database on the internet.
NEEDLE MOVERS
GPT-4V (ision) got everyone jaw-dropping
OpenAI has released a new update for ChatGPT premium users. Usecases are literally limitless. Some of the most notable we’ve seen so far include
Observations only 1 in 5 PMs would do done in just 2 minute
Create a specific workout routine with a photo of your gym equipment.
And even understand humor, complex diagrams and recognize Convolutional Neural Networks
But also, the risk of attacks through prompt injection is now much much higher. So stay safe out there, and take due precautions.
ChatGPT is getting cheaper — (devs gonna love this)
OpenAI is focusing on keeping developers happy and plans to introduce updates to its tools, including memory storage and vision capabilities, to make it cheaper and faster for companies to build AI-powered applications. — The question is, will those cost reductions be reflected in the pricing of their tools? We’ll see!
Replicate has rolled out Llama 2 with built-in support for Grammars, making it a powerful tool for information extraction tasks like getting flight info from an email. This integration ensures you get precisely what you want every time, eliminating the fuss of unpredictable outputs.
And there you have it! Hope you come back for another Future Friday next week. Please leave your comments on your thoughts about today’s piece and what you’d like to see next!
Continue Reading
Don't be shy, give us your thoughts, whether it's a 🔥 or a 💩.
We promise we won't hunt you down. 😉
🌄 CaveTime is Over! 🌄
Thanks for reading, and until next time. Stay primal!
Reply