Unleash ChatGPT Potential with the SCRIBE Method
Summary
TLDRThis video script delves into the Scribe method for structuring prompts to enhance interactions with AI, particularly in the context of live courses focusing on practical applications and advanced prompt engineering. It explains the Scribe acronym—Specify, Role, Context, Responsibility, Instructions, Bentor, and Evaluate—offering a detailed guide to crafting effective AI prompts. Additionally, the script highlights the significance of markdown for clarity and structure in prompts, providing examples and best practices. It concludes by illustrating the application of the Scribe method, including a unique 'criticize me' step, to improve AI-generated content, and introduces an advanced prompting course for further learning.
Takeaways
- 📝 The Scribe method for prompt engineering is essential for structuring prompts effectively, emphasizing Specify, Role, Context, Responsibility, Instructions, Bentor, and Evaluate.
- 📈 Live courses focus on practical application, hands-on projects, and feedback, with a follow-up course named 'ChatGPT and Beyond: Advanced Prompt Engineering' starting on February 19, 2024.
- 📚 The Scribe method encourages specifying a role for the AI, such as acting as a blog writer or social media manager, to guide its response direction.
- 🔧 Context is crucial in prompting; sharing relevant background information leads to more appropriate AI responses.
- 📌 Instructions should be detailed and broken down into step-by-step guidance to achieve desired outcomes.
- 💬 Engaging in a follow-up conversation with the AI to refine initial responses and provide feedback enhances the quality of results.
- 📄 Evaluating AI's responses for accuracy is important, including asking the AI to assess its own effectiveness.
- 🏆 Markdown is used in prompts to add formatting elements, helping communicate with the AI in a universally understood language.
- 🚀 Advanced prompting techniques, like 'criticize me mode,' involve instructing the AI to critique its own output to improve quality.
- 📝 Positive language in prompts (e.g., specifying what to do rather than what not to do) can significantly enhance interaction with the AI.
Q & A
What is the start date for the second cohort of the course?
-The second cohort of the course starts on January 29.
What role will the speaker play in the upcoming cohort?
-The speaker will help learners as a technical adviser in the upcoming cohort.
What is the 'Scribe' method in the context of this course?
-The 'Scribe' method provides a framework for structuring prompts, including specifying a role, context, responsibility, instructions, banter, and evaluation.
What is the name of the follow-up course mentioned, and when does it start?
-The follow-up course is called 'ChatGPT and Beyond: Advanced Prompt Engineering', and it starts on February 19, 2024.
Why is domain expertise important in prompting?
-Domain expertise is crucial for using specific language to condition the AI model and steer its responses in the right direction.
How does the Scribe method suggest using roles with large language models?
-The Scribe method suggests giving large language models a specific role, like acting as a blog writer or social media manager, and specifying the style or tone for the model to inherit.
What is Markdown, and why is it used in prompts?
-Markdown is a lightweight markup language used to add formatting elements to plain text documents, helping communicate universally understood terms to the AI model.
How can headings in Markdown enhance structuring of prompts?
-Headings in Markdown, denoted by hashtags, help establish structural hierarchy in prompts, with different levels of headings indicating the importance and organization of content.
What is the 'criticize me mode' mentioned in the script?
-The 'criticize me mode' is an instructional approach where the AI is asked to critique its own work, aiming to improve the quality of its outputs by identifying potential flaws.
How does the script suggest improving the effectiveness of AI prompts?
-The script suggests using positive, affirmative language in prompts rather than negative language to more effectively guide the AI's responses.
Outlines
📚 Introducing the Scribe Method in Prompt Engineering
The speaker discusses the preparation for the second cohort of an AI and prompt engineering course starting on January 29, highlighting the role as a technical adviser and the students' fondness for the scribe prompting method. Despite this method not being explicitly shared before, it's emphasized for structuring prompts effectively. The upcoming course, 'ChatGPT and Beyond: Advanced Prompt Engineering,' is mentioned, starting on February 19, 2024, focusing on advanced topics like meta multi-agent prompts. The scribe method, which stands for Specify, Context, Responsibility, Instructions, Bentor, and Evaluate, is detailed as a framework to improve interaction with AI by defining roles, providing context, outlining tasks, giving detailed instructions, and engaging in iterative refinement to enhance output quality. Additionally, the importance of domain expertise, the use of specific language, and a reference guide for different contexts and prompts are discussed. Markdown's role in structuring prompts for better AI understanding and interaction is explained, highlighting its significance in the AI prompting process.
🔧 Utilizing Markdown for Structured AI Prompts
The second paragraph elaborates on the practical application of markdown in structuring AI prompts, with a focus on enabling markdown detection in tools and its impact on organizing content. The use of headings to define roles and context, and how markdown's structure is recognized across different platforms like Obsidian, is demonstrated. The segment further expands on structuring detailed instructions for AI, including specifying roles, providing context, detailing responsibilities, and breaking tasks into step-by-step instructions. A unique 'criticize me' mode is introduced, encouraging the AI to critically evaluate its work, thereby enhancing the refinement process. The effectiveness of positive language in prompts over negative instructions is highlighted, showcasing how specific prompting can lead to improved AI interactions. Finally, the segment mentions a successful prompt developed by a team member, which enhances the ChatGPT experience, illustrating the potential of advanced prompting techniques in maximizing AI utility.
Mindmap
Keywords
💡Scribe method
💡Prompting
💡Markdown
💡Large language models
💡Role prompting
💡Meta multi-agent prompts
💡Feedback loop
💡Evaluate
💡Structural hierarchy
💡CHPT Master reference guide
Highlights
Preparation for second cohort starting on January 29 with technical adviser assistance.
Introduction of the Scribe method for structuring prompts.
Live courses focused on practical applications, hands-on projects, and feedback.
Announcement of follow-up course 'ChatGPT and Beyond: Advanced Prompt Engineering' starting on February 19, 2024.
Emphasis on the importance of specifying a role for effective prompting.
Highlighting the necessity of domain expertise in prompting.
Introduction of a Master reference guide with useful terms and prompts.
Explanation of the significance of context in generating appropriate AI responses.
The importance of clear instructions and step-by-step task breakdown.
The role of iterative feedback in refining AI responses.
The value of evaluating AI's responses for accuracy and effectiveness.
Use of markdown in prompts to structure and clarify requests.
Example of structuring prompts with markdown for clarity.
Introduction of 'criticize me' mode to enhance prompt feedback.
Technique to improve AI interactions by using positive affirmative language.
Introduction of a prompt that transforms ChatGPT into an AutoGPT experience.
Transcripts
I was going through our a anbt for
everyone course material in preparation
for second cohort starting on January 29
where I will come to help Learners as a
technical adviser you check this one off
your list okay this is done while
reviewing testimonials and past student
projects I remembered how much students
love scribe prompting method I also
realized that I have never explicitly
shared or explained scribe method first
of all prompting is all about Str
structure and V scribe method provides a
helpful framework in structuring your
prompts our live courses are all about
practical applications Hands-On projects
and feedback if by the time you're
watching this video and enrollment has
closed don't worry about it if you're
interested there's going to be follow-up
course called Chad GPT and Beyond
Advanced prompt engineering which will
start on 19th of February 2024 in that
course we go as deep as creating meta
multi-agent prompts but for now I want
to share with you the Scribe method as
well as talk to you about importance of
markdown scribe stands for specify a
role context responsibility instructions
bentor and evaluate let's dig just one
by
one it's very useful to give large
language modu a specific role like for
example act as a Blog writer as act as a
social media manager and so on here you
can also add the preferred style or tone
that you want large language model to
inherit large language models are
predicting one word at a time based on
the input the specific role acts as a
key for a large language model to look
which doors it should go to which would
match this context and here's one
universal truth when it comes to
prompting you as a user have to have
domain expertise and use specific
language to condition the AI model and
steer its responses to the right
direction but if you want to use AI to
help you with task which are outside of
your domain expertise we put together
chpt Master reference guide with useful
terms for different context and prompts
for example how to write like a human
different marketing styles are a bunch
of role prompting personas you can find
the link in the description box below
and check it out for yourself okay let's
talk about context share any relevant
background context details and even
examples to help large language model to
generate an appropriate response more
specific and the more context you
provide the better response you might
expect you need to clearly outline the
task that you want large language model
to perform be as specific as possible in
describing what you want and most
importantly what success would look
like provide large language model with
detailed instructions that you wanted to
follow in order to achieve that outcome
and break the complicated task into step
by step instructions to help the large
language model to guide you and for each
of these you can use CHT to help you for
example breaking a task just literally
tell what's the big task and ask it to
break it in stepbystep instructions copy
those and input of them in here that's
it you have to engage with large
language model in a follow-up
conversation to refine its initial
responses ask clarifying questions or
provide feedback this what we call enter
back and forth conversation and like
more collaborative work leads to the
higher quality
results and always always evaluate
review their responses for accuracy you
can ask AI to even evaluate its
Effectiveness and accuracy this kind of
metal level analysis helps the model to
strengthen its generation abilities and
reduce hallucinations before I show you
scribe in action and more advanced
features I want to explain why we like
to use markdown in our prompts and what
markdown is in the first place markdown
is a lightweight markup language that
you can use to add formatting elements
to the plain text documents when it
comes to prompting this markdown
language allows us to communicate to AI
universally understood terms plus AI
model was already trained on this terms
and it knows them for example instead of
writing title you can use what is known
as headings in markdown heading one is
expressed with one hashtag this way a
model understands that a hashtag n
combination of word is a title or
heading sentences in your PR which has
hashtag in front of them will act as a
titles and the text underneath it as
part of one block now if you want to
establish structural hierarchy or
substructures you can use heading two
which are two hashtags and we can keep
breaking down the structure down to six
hashtags or heading six in Google Docs
you can visually see how this works
first thing to enable markdown you need
to go to tools preferences and then
automatically detect markdown you need
to check it and say yes and now we are
going to do a hashtag it automatically
goes to heading one you can see it here
let's say specify a roll okay so next we
are going to be like okay this is our
role and space again and then another
hashtag will tell context okay here
we're doing some context so now these
two are H1 so this is the initial
structure but if I
did two hashtags and
said Ru two it becomes a substructure of
the first one but not another rule by
itself now if we if I copy all of this
and I go to the tool like obsidian which
reads markdown you will see that this
text is automatically expressed with a
hashtag and it has different weights and
this is what I mean by universally
understood important to remember that
headings in markdown don't work if you
don't have space between hashtag and
your text so keep that in mind you can
also Define banter and instruct model to
evaluate the results and here I like to
take it one step further and use my
criticize me mode first of all we
specify a all we give context we
describe responsibilities and here we
now breaking up instructions the
instruction two is telling what it's
supposed to do so we are supposed to
craft an email in this case three as you
can see has B here we're instructing CH
what it's supposed to do once it crafted
an email first it has to ask for my
feedback and then ref find the email
content as needed now four is evaluate
stage and I'm going to tweak it a little
bit with you so once salesperson is
satisfied with the format you will
finalize the email and encourage them to
send it to the prospect you will then
ask feedback on the process to improve
your future email crafting five is
really optional but we like to Define
how chbt should interact with us like
what it should say at the beginning of a
chat in this case it says hello I'm your
personal expert salesperson prospecting
assistant not only it's nice start of a
conversation but it also confirms that
Chach B understood so first thing it
followed the instructions of how it
should interact with us second step is
gathering all the necessary information
so it's asking for product details
target audience brand background
previous successful emails I could just
continue until we get to the final email
but I want to show show you the critic
mode so I tweaked a little bit our
scribe method and included one more step
in instructions it is something like
this but you can adjust it however you
want once you have presented initial
draft you need to act as a harsh critic
your job is to critique the email and
convince me why it is bad and why
receiver would not like it the first
step scrap method does is asking for
details in this case because I didn't
want it to come up with all the detail
by myself I told it to come up with all
the details itself and it did and then
we have an email and we have a critiques
and here's like my first impression when
I saw this email I was like it's too
long and here you go in critique it says
the email is a bit too long which might
lead to loss of Interest especially for
busy Prospect and here's a bonus tip
which very few people know or use
actively we all been frustrated with ch
not giving us what we want right right I
see him hide him in the crowd more
effectively hidden in the whole point of
where's Waldo is to find him
interestingly enough telling AI model
what not to do is not as effective as
specifically instructing what to do
basically use positive affirmative
language instead of negative instead of
saying blog title should not exceed more
than 50 characters try say block title
should always be shorter than 50
characters small tweaks like this can
dramatically improve your experience
with AI and just imagine what learning
Advanced prompting can do for you take
for example Joe our genius brain behind
all our courses and prompts he has
developed this prompt which turns chpt
into more like Auto GPT experience and
now this prompt called Professor synip
is ranking as one of the top gpts on GPT
store
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