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In partnership with
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In This Edition:
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Agentic AI: The Next $B
Wave
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Will AI Replace Your Sales
Interns?
-
Idea → MVP in 7 Days with
AI
-
Paul Graham: Why ‘Obvious’
Ideas Fail
-
VCs’ New AI Startup
Checklist
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Agentic AI: Why
VCs Say It’s the
Next
Multi-Billion-Dollar
Wave
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Investors are
shifting focus
from
general-purpose AI
to agentic
systems—autonomous AI
that doesn’t just
answer but acts on behalf
of users.
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Why VCs believe
it’s a
multi-billion-dollar
opportunity:
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Autonomous
execution
→ AI
handling
tasks
end-to-end,
not just
providing
outputs
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⚡ Productivity
leap
→ Replacing
entire
workflows
across
sales,
support, and
ops
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Scalable
demand
→ Every
sector, from
healthcare
to finance,
benefits
from
agents
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Early
signals
→ Startups
in this
space
already
drawing
oversized
seed
rounds
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Strategic
moat
→ Teams that
master
orchestration
will own
defensible
markets
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The shift is
clear: agentic AI
is not hype—it’s
the next
competitive layer
where startups can
carve
billion-dollar
niches.
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Curious
which
startups are
leading this
charge and
why
investors
are doubling
down?
Explore the
full
breakdown
here.
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Will AI Replace
Your Sales
Interns? A
Startup Case
Study
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A growing number
of startups are
testing whether AI
can handle the
tasks
traditionally
assigned to sales
interns. The
findings reveal a
shift in how teams
think about
early-stage sales
support.
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What the case
study
uncovered:
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Lead
sourcing
→ AI tools
processed
10x more
leads in
less
time
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✉️ Outreach
→
Personalized
emails
generated
higher open
and reply
rates
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Time
savings
→ Routine
research and
data entry
reduced by
80%
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Cost
efficiency
→
Operational
expenses
dropped
significantly
compared to
intern
programs
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⚠️ Limitations
→ AI
struggled
with nuanced
conversations
and
unstructured
data
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The insight is
clear: AI may not
fully replace
interns yet, but
it is reshaping
how sales leaders
allocate tasks and
budget.
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Explore the
full case
study to see
where AI
adds the
most
value—and
where humans
remain
irreplaceable.
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From Idea to
MVP in 7 Days:
Startups Using
Pythagora &
GPT-Pilot
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Startups are no
longer waiting
months to test an
idea. With tools
like Pythagora
and GPT-Pilot, founders are
compressing the
journey from
concept to minimum
viable product
into a single
week.
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⚡ Key advantages
these teams
reported:
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Rapid
prototyping
→ Functional
apps built
without
heavy
engineering
teams
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⏱ Time-to-market
→ Weeks of
development
reduced to
days
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Cost
savings
→ Lower
upfront
spend on
design,
testing, and
engineering
resources
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Faster
iteration
→ Immediate
user
feedback
drives
product-market
fit
experiments
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Founder
focus
→ More time
spent on
customers,
less on
debugging
code
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This shift shows
how automation and
AI-first workflows
are redefining the
startup
playbook.
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Curious how
these tools
work in
practice—and
which
startups are
already
scaling with
them?
Explore the
full
breakdown
here.
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The Gold standard
for AI news
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AI will eliminate
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Founder Hot
Take: Paul
Graham on ‘Why
Obvious Ideas
Rarely Work’
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Paul Graham
highlights a
paradox in
entrepreneurship:
the most obvious
startup ideas are
rarely the ones
that
succeed.
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Key points from
his insight:
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Obvious ≠
original
→ If it’s
clear to
everyone,
competitors
are already
building
it.
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⚡ Non-obvious
wins
→
Breakthroughs
often hide
behind
mistaken
assumptions
or ignored
niches.
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Founder
advantage
→ Insight
comes from
spotting
what others
overlook,
not chasing
trends.
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Market
truth
→ Many
billion-dollar
companies
started as
“weird” or
“niche”
ideas.
-
Investor
perspective
→ VCs often
back
contrarian
founders who
see value in
overlooked
spaces.
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The lesson is
clear: innovation
thrives in the
shadows of doubt,
not in the
spotlight of
consensus.
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Before
the
Startup
with
Paul
Graham
(How
to
Start
a
Startup
2014:
Lecture
3)
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Explore the
full context
of Paul
Graham’s
take—and why
it matters
for founders
searching
for their
next big
idea.
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Startups
Buzz
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Why the Best
Startup Skill
Might Be Saying
No
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Saying yes to
everything drains
focus. The
founders who win
big are the ones
who say
no—relentlessly—to
protect their time
and energy.
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Learn why
‘No’ is the
ultimate
growth
skill
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What Airbnb’s
Brian Chesky
Learned From
Burnout
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Airbnb’s
co-founder hit
burnout during
hypergrowth—and
came back stronger
by reshaping how
he worked. His
lessons can help
founders avoid
costly burnout
while
scaling.
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See the 7
lessons every
founder should
know
|
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50 Pre-Seed
Funds Every
Founder Should
Know
|
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Papermark
compiles a list of
the most active
pre-seed investors
— a handy resource
for marketers to
identify sectors
where new product
launches will
emerge.
View the full
pre-seed
list
|
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20,000-Word
Personal Finance
Guide for
Founders
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Built for startup
founders, this deep-dive
Notion guide
covers
everything—equity
structures, cap
table setup,
fundraising,
taxes, team hiring
&
compensation, plus
selling
secondaries and
planning your
exit. Every
section is
actionable and
founder-tested so
you can build wealth
while building
your company.
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Click to
unlock the
complete
founder-focused
personal
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playbook
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|
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VC Insights: The
New Due
Diligence
Checklist for AI
Startups
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Venture capital
firms are updating
how they evaluate
AI startups.
Beyond product
demos and market
size, investors
now scrutinize
deeper factors
that determine
long-term
defensibility.
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What’s on the
new
checklist:
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Model
dependence
→ Reliance
on
third-party
LLMs vs
proprietary
IP
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Data
moat
→ Access to
unique,
high-quality
datasets
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⚡ Unit
economics
→ Realistic
cost
structures
for scaling
AI
workloads
-
Team
depth
→ Balance of
technical
expertise
and
go-to-market
strength
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Adoption
proof
→ Early
customer
traction and
measurable
ROI
-
Regulatory
readiness
→ Compliance
with
evolving AI
governance
standards
-
Competitive
edge
→ Clear
differentiation
in crowded
sub-sectors
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The message is
clear: AI startups
must prove
resilience, not
just technical
brilliance.
|
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Explore the
full
breakdown of
how
investors
are vetting
AI founders
in 2025—and
what
startups can
do to stand
out.
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