Video summary
The video introduces a structured framework called DRIVE for building custom skills with Claude, designed to ensure clarity and reliability in AI interactions. The process begins with "Define," which involves clearly naming the skill, describing its purpose, and specifying exactly when it should trigger. This initial step is crucial because it prevents the AI from activating the skill at inappropriate times; for instance, a presentation creation skill should not automatically run when the user intends to generate a financial report. By meticulously defining the scope and triggers, users establish a solid foundation that aligns the AI's actions with specific human intentions.
Following definition, the framework moves to "Rules," which are non-negotiable guidelines that the skill must never violate, such as mandatory checks for data accuracy in financial statements. The third component, "Instruction," outlines the step-by-step workflow the AI should follow once triggered, mirroring how professionals delegate tasks to colleagues. For example, a reporting task might require the AI to first explore and understand the data, then clean it, establish relationships between tables, write measures, visualize results, and finally publish them. These detailed instructions ensure that the AI executes complex processes in a logical sequence without skipping critical steps.
The fourth element, "Verify," empowers the AI to perform self-checks before presenting any output, ensuring that all previous rules and instructions have been correctly followed. The final stage, "Evolve," emphasizes that skills are not static entities but require continuous refinement over time, much like nurturing a child until they mature. Users must regularly review their skills to fix errors or adjust behaviors based on changing needs, such as altering a workflow route because a specific path is no longer efficient. This iterative process of fine-tuning allows the skill to adapt and improve, ensuring it remains effective and aligned with the user's evolving requirements.
Read the full video transcript
So before we even look at what a skill
is, right? I'm going to give us a
framework for how you build a skill
with Claude.
Right? How you build a skill with
Claude. So what's the framework? The
framework is DRIVE. D R I V E. So what
does D stand for?
What does D stand for? D stands for
what? Define.
Define. So you're trying to say, "Hmm,
Claude, I want to build this. I want to
do that." You define the skill you want
to build. You name it. You describe it.
Right? And when it should what? Trigger.
You don't want your presentation skill
to trigger when you want to create a
report.
You don't want your financial modeling
skill to trigger
when you want to just create
um
a slide deck.
Right? You don't want um
You don't want some kind of You don't
want your skill to trigger when it is
not supposed to trigger, basically. So
from the definition, you describe what
you want to hear. You name it. You
describe it. When it should trigger, you
write those things in the skill, right?
You define your skill. That's the very
first thing that you do.
The next one is the R, the rules. The
non-negotiable guide rules. Right? All
those things that it must never break.
To say,
when you're creating um my my um
financial statements, these are the
rules that you must never break.
These are the rules that you must never
break. These are the checklists. If
these things are not uh you know, if you
check for these three things and they're
not there,
then don't proceed. So you give it like
non-negotiable rules. There's nothing
that would make you get this thing done
if these things are not there. So you
give it guide rules that it must never
break. And that is R. I is instruction.
How you want it to what? To work. The
step-by-step workflow. Take for
instance,
um
I know most of us we we are we are
professionals, right? And of course,
there when when we asked to do a
particular thing, right? Or
um you want to ask your colleague,
right, to get something done for you.
There are instructions, step-by-step, on
how those things should be done, right?
You give it to them. Is that not it?
Yeah. And of course, um some tasks
most of our tasks, they are step-by-step
um guidelines that we do to say, "Okay,
when I get the data, when I Take for
instance, the people that, you know,
that create reports, reporting
analytics, and the likes. When I get my
data, the very first thing is I want to
explore the data to understand the data.
When I understand the data, the next
thing I want to do is probably I want to
clean my data. When I clean my data,
next thing I want to do is create
relationship with um between the tables.
When I create relationship, now I want
to start writing my measures, that's the
DAX. When I write the DAX, then I want
to start um you know, visualizing. When
I'm done visualizing, I want to publish.
When I'm done publishing, I want to So,
those step-by-step guide, right?
Step-by-step instruction, you give it to
you you put it in your skill. So, it's
just when AI triggers that skill, it
will read everything. Okay, this person
likes to This person has asked me to do
this first before I do this before I So,
that is the instruction, how you want it
to work, the workflow, right? You give
it to your AI. And then V.
You you you you verify. This is a
self-check before anything is presented,
right? Your AI can also verify to say,
"Okay, have I done the right thing?
Have I done the right thing?" So, your
AI can also do a self-check, a
self-verification,
right? A self-verification to be sure
that okay, all of these things are what?
Are working fine.
And then lastly,
is what? Is E.
Right? The most important thing I want
every one of us to know is that you
can't sit down
and say, "Okay, I'm going to build this
skill and it will work perfectly while
I'm here."
Right? Because it doesn't work that way.
It doesn't. When you build a skill, it
is possible that when you start using
it, you start noticing, "Okay, some
things are not working fine. Okay, let
me add it to the skill to say, "Okay, I
I forgot to probably add this
instruction to the skill and all of
that."
And most times when you are even
building a skill, it's like you're
building
you you are nurturing a kid, right? It
is not the day you you you you you you
give it to your child that it starts
having that, you know, that, you know,
um maturity in them. You nurture them.
You nurture them until they get it um
perfectly. So,
you refine you can refine your skill to
say, "Okay, this thing I want to
reformat this. I don't want it this
way." It's just how we humans work, all
right? It's just how we work. Sometimes,
um when we we just notice that, "Okay,
I've been doing this thing this way
before. I don't want to do it this way
again." It's like, um when you're going
to work, you're always passing um
Maryland in Lagos. You're always passing
Oshodi but all of a sudden you just feel
like, "Mm, I don't want to pass this
route again. I want to start passing
another route." Yes. On what we do on
our day-to-day task, sometimes it
changes how we work what changes. And
when you notice, "Okay, I'm going to
change this thing." You go back to your
skill, right? You tell AI, "I don't want
you to do this way." So, again, this is
So, that is what refining. You're
refining how your skill is. So, you can
always go back, you know, refine,
fine-tune your skill.