You
can
build
a
working
custom
AI
assistant
without
touching
a
terminal
or
knowing
what
an
API
is.
OpenAI’s
GPTs
and
Anthropic’s
Claude
Projects
handle
the
infrastructure.
You
handle
the
instructions.
The
catch:
most
guides
assume
you
want
a
chatbot.
That’s
not
the
point.
The
point
is
building
a
specialized
system
that
handles
a
specific
workflow—research
synthesis,
customer
support
triage,
content
quality
control—and
actually
remembers
its
instructions
across
conversations.
What
You’re
Actually
Building
A
custom
GPT
or
Claude
Project
is
not
a
new
model.
It’s
a
wrapper
around
an
existing
model
with
three
components:
system
instructions,
a
knowledge
base
(optional
files),
and
custom
actions
(optional,
but
powerful).
Think
of
it
as
a
saved
conversation
template
that
never
forgets
how
to
do
one
specific
job.
The
difference
between
the
two:
- GPT:
Lives
in
OpenAI’s
ecosystem.
Can
pull
from
the
web,
run
code,
use
external
integrations.
Limited
to
~200
files
for
knowledge
base. - Claude
Project:
Lives
in
Claude.ai
or
your
workspace.
Optimized
for
document
analysis
and
research.
No
web
search
built-in,
but
faster
at
long-form
reasoning.
Pick
based
on
your
workflow.
Need
to
fetch
data
from
the
internet?
GPT.
Processing
50-page
research
documents?
Claude
Project.
Setting
Up
a
GPT
in
Five
Steps
Go
to
openai.com/gpts
and
click
Create.
Step
1:
Write
your
system
instructions
This
is
the
entire
system
prompt
the
GPT
runs
on
every
conversation.
Be
specific
about
tone,
constraints,
and
output
format.
You
are
a
research
paper
analyzer
for
startup
founders.
Your
job:
extract
the
core
insight
from
research
papers,
then
explain
why
it
matters
for
early-stage
companies.
Format
every
response
as:
1.
Core
Finding
(1
sentence)
2.
Why
It
Matters
(2–3
sentences,
founder-focused)
3.
How
to
Use
It
(1
specific
action)
Never
output
tables
or
academic
language.
Always
assume
the
reader
has
15
minutes
max.Notice
the
specificity.
Not
