Greg Isenberg

CEO of Late Checkout, a holding company for community-based businesses

I'm the CEO/Co-Founder of Late Checkout, a holding company with a portfolio of internet businesses. 

Previously, I was the Head of Product Strategy at WeWork, an Advisor at TikTok and an Advisor at Reddit. I was the Founder/CEO of Islands, a messaging/community app that was acquired by WeWork.  I was the Founder/CEO of 5by, a leading video discovery app which got acquired by StumbleUpon.  I helped build one of the internet's most popular financial education communities Wall Street Survivor (acquired). 

I've helped build communities and technology products for brands like Microsoft, FedEX, NASCAR, TechCrunch and Wordpress. 

I've been featured on places like Vanity Fair, Forbes, Mashable, Fortune Magazine, L.A Times and have won Webby Awards.

LINKS to a few of my companies in my holdco 🔗

gregisenberg.com (my guides, podcast, sign up to my weekly newsletter for updates)
latecheckout.agency (product design agency that works with executives from Dropbox to Nike to Shopify)
thevibemarketer.com (community for people into marketing with AI)
ideabrowser.com (the #1 place to find startup ideas and trends on the internet)

CEO & Co-Founder 

Late Checkout is a holding company that builds, acquires and incubates cash-flowing businesses that are powered by internet audiences and communities.

Learn more about our businesses at https://latecheckout.studio and work with us.

i found a github repo that lets you spin up an ai agency with ai employees

engineers, designers, growth marketers, product managers

each role runs as its own agent and they coordinate to ship ideas

10k+ stars in under 7 days

1. engineering (7 agents)
frontend, backend, mobile, ai, devops, prototyping, senior development

2. design (7)
ui/ux, research, architecture, branding, visual storytelling, image generation

3. marketing (8)
growth hacking, content, twitter, tiktok, instagram, reddit, app store

4. product (3)
sprint prioritization, trend research, feedback synthesis

5. project management (5)
production, coordination, operations, experimentation

6. testing (7)
qa, performance analysis, api testing, quality verification

7. support (6)
customer service, analytics, finance, legal, executive reporting

8. spatial computing (6)
xr, visionos, webxr, metal, vision pro

9. specialized (6)
multi agent orchestration, data analytics, sales, distribution

what i like about this approach is the framing

instead of one big ai agent trying to do everything, you structure it more like a company. specialized agents, clear responsibilities, workflows between them

im curious to see what this actually feels like in practice and if its any good (do your own research)

but as always will share what i learn in public on LI, X, IG and my pod the startup ideas podcast

one thing is for certain and it reminds me

the future belongs to those who tinker with software like this

CEO of Late Checkout, a portfolio of internet companies

WELCOME TO THE SKILL ERA OF THE INTERNET...for the last 15 years, if you wanted to build a serious software company, you built a product and exposed an api.

that was the move.

you created functionality… payments, messaging, email, search, analytics… and then you let developers plug into it.

the companies that won owned the pipes.
stripe owned payments.
twilio owned messaging.
sendgrid owned email.

the api was the distribution layer.

once you were integrated, you were embedded.

that model made sense in a world where execution was scarce.

llms compress execution into a prompt.

so the center of gravity shifts.

in this cycle, you build expertise and package it as a skill.

an api is a doorway into a function.

here’s how to send an email.
here’s how to process a payment.
here’s how to fetch this data.

it’s precise. mechanical. bounded.

a skill is a doorway into judgment.

here’s how to audit a landing page like a serious growth operator.
here’s how to structure a legal intake so you catch the real risk.
here’s how to clean and enrich messy directory data so it actually turns into revenue.

you’re encoding a way of thinking.

and that changes how companies are built and how they scale.

in the api era, distribution meant convincing developers to integrate you.
you needed docs. sdk’s. developer evangelism.
you fought for a place inside someone else’s codebase.

in the skill era, distribution means becoming part of someone’s agent workflow.

a founder opens claude code.
they type /seo-audit.

your skill runs.
it frames the output.
it structures the analysis.
it guides the decisions.

your expertise lives inside the execution layer itself.

you aren’t pulling users into your interface.
you’re embedding your thinking into theirs.

that changes company design.

the old playbook looked like this:

build saas
design ui
onboard users
drive retention
expand seats

the new playbook looks more like this:

encode a high-leverage playbook
package it as a skill
let agents call it thousands of times per day

one installation can mean your methodology is invoked across hundreds of companies automatically.

the scaling curve looks less like seats and more like invocations.

what’s happening underneath all of this is simple:

software used to be the executor.
now software is the orchestrator.
next, expertise becomes infrastructure.

in the api era, the winners owned the pipes.

in the skill era, the winners own the patterns.

patterns for closing deals.
patterns for pricing.
patterns for positioning.
patterns for enrichment.
patterns for research.

many new companies will look surprisingly small on the surface.

a tight repo. a handful of powerful skill files.
maybe 2–5 people maintaining and improving them.

and it’s creating a new class of companies built less around dashboards and more around encoded judgment.

THIS IS THE SKILL ERA OF THE INTERNET.

welcome.

note: more startup ideas for this AI age on ideabrowser.com

4000 people laid off today at Block (almost half the company) and the reason is AI

“we're already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. and that's accelerating rapidly” - jack dorsey

this is unfortunate yet just the beginning. hundreds of thousands if not millions will lose their jobs.

New jobs will be created and many will become entrepreneurs and build ai native businesses

send this to a friend

note: i've noticed in uptick on http://ideabrowser.com of people looking for startup, ideas trends who've been recently laid off

"Things I wish someone told me before I almost gave up on OpenClaw"

the future of building saas

1/ start with a sub-niche inside a big market
2/ map their daily workflow end-to-end
3/ identify where money changes hands
4/ spot the repetitive mechanical steps
5/ quantify the cost of those steps
6/ create scroll-stopping content around that workflow
7/ study which posts get saves, replies, and dms
8/ double down on the organic angles that convert
9/ run paid ads on proven organic winners
10/ capture emails from day one
11/ manually perform the workflow yourself
12/ document every step precisely
13/ separate judgment tasks from mechanical tasks
14/ turn mechanical tasks into structured agent workflows
15/ design agents to complete full tasks, not suggestions
16/ connect to real tools: email, slack, notion, crm, stripe
17/ add orchestration, retries, and verification checks
18/ store user preferences + long-term memory
19/ launch narrow with high-touch onboarding
20/ publish measurable proof: revenue, hours saved, errors reduced
21/ move pricing from per-seat → per-task
22/ shift to outcome pricing tied to revenue created
23/ increase pricing as value compounds
24/ expand into adjacent workflows within the same niche
25/ orchestrate multiple agents across the full lifecycle
26/ build switching costs through data + memory
27/ turn power users into public case studies
28/ hire operators from inside the niche
29/ reinvest profits into distribution + product depth
30/ become the default execution layer for that sub-niche

this is how 3 person teams build 100m companies

what a time to be building

note: find startup ideas on ideabrowser.com

how to build an ai native vertical saas in the claude cowork era:

1. pick a sub-niche inside a large, profitable market
2. map one recurring workflow that drives revenue or saves time
3. write the workflow step-by-step like you’re training an intern
4. separate mechanical steps from judgment calls
5. connect claude to the actual stack: crm, sheets, inbox, slides, contracts
6. remove exports and copy-paste from the process
7. collapse raw data → reasoning → finished output into one session
8. store every output so context compounds over time
9. turn your best prompts into named, reusable commands
10. build memory around the niche (not generic instructions)
11. package the result as a finished outcome
12. price per report, per memo, per meeting, per deliverable
13. publish the workflow collapsing in real time for distribution
14. use organic traction as signal before running paid ads
15. expand into adjacent workflows inside the same vertical
16. layer governance and approvals where required
17. become the default operating layer for that sub niche
18. repeat the model in the next vertical once memory and distribution compound
19. good times

claude can now sit inside real enterprise tools:

– google workspace
– excel + powerpoint
– crm systems
– prospecting tools like apollo + clay
– traffic data like similarweb
– contracts via docusign
- etc etc

that means the model sees the full workflow

the opportunity for you

find a niche.
collapse a workflow.
package the outcome.
own the memory.
expand from there.

that’s how ai native saas gets built now

it's a wonderful time to be building

I'm a UI/UX Designer who creates high-performing digital interfaces and wonderful User Experiences.

I love using Figma and Notion to get my job done.

In my free time, I like to code in React JS and play football.

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Greg Isenberg

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The Battle

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Engagements

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Greg Isenberg's LinkedIn Performance

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