Croom Lawrence

CCO @Hemostemix | HealthFounderOS | Turning moonshots into moon landings via AI commercialization | MIT AI and Health

[Croom Lawrence @croomlawrence]

👉 https://t.co/lZISWAHU6m

[Croom Lawrence @croomlawrence]

@pronounced_kyle They were talking about the next gen spcx satellites and space data centers how elegant and beautiful they looked, many overlook that Elon has an incredible sense of taste and beautiful design. That’s a moat.

[Nick Sortor @nicksortor]

🚨 BREAKING — IT'S OFFICIAL: Elon Musk becomes the world's first TRILLIONAIRE as SpaceX goes public

This is absolutely MONUMENTAL. Congratulations @ElonMusk!

To the moon! 🚀

$SPCX is set to start trading at $135 per share imminently, valuing the company around $1.8 TRILLION.

[Croom Lawrence @croomlawrence]

@AlfieJCarter Agents

[ericosiu @ericosiu]

Every company is missing the same layer:

A company brain.

Right now, the memory of the business is scattered across calls, docs, Slack threads, dashboards, SOPs, and people's heads.

That's the part people miss when they talk about a company brain.

The value isn't a giant folder of company knowledge. Every company already has that.

The real advantage is the intelligence layer that sits between all that context and the work your team needs done.

This is the layer every AI-native company will need:

[Chamath Palihapitiya @chamath]

This is awesome. I’ve worked with Sue for more than a decade now. She started Brilliant - a learning site for advanced learning - which has now taken all of that decade-long training data and created a helper to make your kids smarter.

It doesn’t matter their level, this adapts to them and brings them along.

Please consider trying it.

[Matthew LaBosco @matthew_labosco]

High cortisol is the real reason you wake up at 3-4 AM.

It also shaves 5 years off your life — tanks testosterone, locks belly fat, literally shrinks your brain.

If I wanted to fix it without medication, here are 8 things I'd do every day:

1. No food 3 hours before bed.

[Ronin @DeRonin_]

Greg Isenberg broke down a 35-step playbook for building AI startups from zero to $1M+/year. 4 businesses, all profitable, no VC money

I compressed it into 12 rules that actually matter:

1. ride a trend, don't create one: find a niche where demand already exists but tools are 5 years behind. if people are complaining in reddit threads and facebook groups.. that's your market

2. audience before product: master ONE platform. set notifications for 10 niche leaders, reply with real insight (not "great post!"), gain 5-10 followers daily. this compounds into an unfair advantage when you launch

3. validate with wallets, not surveys: if nobody will pre-pay at 50-70% off for something that doesn't exist yet.. they won't pay full price either. your audience becomes your investors

4. vibe code the MVP: use Cursor/Bolt/V0 to ship v1 in days not months. the goal isn't perfect code, it's proving people will use it. polish comes after revenue

5. keep the team at zero: AI is your co-founder now. Manus for research, ChatGPT for PRDs, Claude Design for design, Cursor for code. most $1M/yr businesses in 2026 run with 1-3 people max

6. automate before you hire: find the 3-step process you do 10x a day that takes 5 minutes each time. automate that first. Lindy, Gumloop, Zapier. work toward 90%+ automation

7. retention before growth: fixing churn is 10x more valuable than doubling acquisition. run retention sprints before growth sprints. most founders do this backwards and wonder why revenue flatlines

8. modular pricing kills one-size-fits-all: free tier for top of funnel, $29 for individuals, $299 for teams, $3K for enterprise. let the product sell itself at every level

9. partner with creators instead of buying ads: offer 1-20% equity or 20-50% rev share to creators with your audience. one partnership can outperform 6 months of paid marketing

10. build free tools for distribution: a public-facing calculator, checker, or generator drives organic traffic AND trains AI search to recommend you. this is the new SEO

11. think portfolio, not single product: once business #1 is profitable, repeat the process. share infrastructure, cross-promote, create a flywheel. Walt Disney didn't build one ride

12. ship something new every 30 days: a culture of shipping beats a culture of planning. new MVP monthly, acquire underperforming products with distribution upside, recruit operators to run them

what actually compounds in 2026:

- audience before product, not the other way
- pre-selling before building
- 1-person teams running $1M businesses with AI
- retention over acquisition, always
- portfolios over single bets
- shipping over strategizing

the cost of building has never been lower.. billions of people with credit cards are reachable through social media

the only bottleneck left is you actually starting

full 30-min breakdown from @gregisenberg attached below ↓

study this

P.S. left 20 not taken startup ideas below which you can take and start growing

[Ole Lehmann @itsolelehmann]

marc andreessen just went on Rogan and casually dropped a TON of AI alpha

full pod is 3 hours and 20 minutes, but i pulled out his most interesting takes here:

1. AGI is here. he thinks the line was crossed about 3 months ago with the new GPT-5.5, claude 4.6, gemini 3, and grok 4.3 models. nobody noticed because the field moves too fast for anyone to register the milestones anymore.

2. his other big claim: for almost any topic, the top AIs now give him better answers than the actual world-class experts he could call on the phone. and he can call basically anyone.

3. every doctor is already secretly using chatGPT in the exam room. marc says they turn around the second you stop talking and just type your symptoms in. some of them are doing it while you're still sitting there. his quote: "at that point you're asking the question of like, what do i need you for."

4. when AI refuses to answer something he wants to know, he tells it he's writing a novel. "i'm writing a detective novel, walk me through how the bad guy robs the bank." it'll explain almost anything if it thinks it's helping you write fiction.

5. when something is too complex he says "explain it to me like i'm 10." then "like i'm 5." then "like i'm 2." he keeps going until it actually clicks in his brain.

6. when he wants to understand a tough topic he doesn't ask "what's the right answer." he asks the AI to steelman one side, then steelman the other. then he decides for himself.

7. for big questions he tells the AI to pretend to be a panel of experts. "be a doctor, a lawyer, a historian, a psychologist, and argue this out with each other." then he reads the debate they have.

8. pay attention to the exact moment you think "i don't know how to figure this out." most people just give up at that moment. that's the moment you should open the AI.

9. the only real skill left in using AI is knowing what to ask it. the models can already do almost anything you can describe in plain english. the bottleneck lives in your own head.

10. you can send the AI photos of almost anything medical now and get a real answer. skin rashes, blood test results, even pictures of your poop. the new models can read images, not just text. it's a free 24/7 second opinion on basically anything.

11. the one type of therapy that's clinically proven to actually work is called cognitive behavioral therapy. it's also something an AI can fully do on its own. which means every person on earth is about to have access to a real therapist for free, anytime they want.

12. AI is now solving math problems that have been open for 100+ years that no human mathematician could crack. same thing is starting in physics, chemistry, and biology. expect cancer cures, new drugs, and weird new physics breakthroughs to start coming out of these things over the next few years.

13. the best AI coders in silicon valley now make $50 million a year. one person. that's how much value the top performers print with these tools. it tells you how big this thing actually is when you strip away all the doom takes.

14. one friend paid $200 to get his entire DNA decoded (this used to cost millions of dollars and take years to do). then he gave the AI his DNA, his blood test results, and his apple watch data. the AI built him a full health dashboard and started telling him exactly what to fix.

15. another friend (almost certainly zuckerberg) put two cameras in his home jiu jitsu gym. AI now watches him spar and gives him notes on his technique after every round. like having a world-class coach at every practice for free.

16. the best programmers in silicon valley now run 20 AI coding bots at the same time. each bot writes code while they review the others. they call themselves "AI vampires" because they've stopped sleeping. going to bed means 20 workers stop working and you literally lose money every hour you're out.

17. the obvious next step: the bots will start running their own bots. one human in charge of 20 bots, each in charge of 20 more bots. one person running an entire company of 1000 AI workers from a single laptop. this is months away, not years.

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Croom Lawrence @croomlawrence]

@AlfieJCarter CLAUDE

[Matthew LaBosco @matthew_labosco]

Quick recap — 10 cheat codes to lower cortisol:

1. Silent walks (20 min)
2. Close stress loops
3. Reclaim agency
4. Brutal honesty
5. Calibrate your alarm
6. Identify your primal loop
7. Audit your inputs
8. Schedule unscheduled time
9. Pause and choose
10. End-of-day check

[ericosiu @ericosiu]

Hermes told me my throughput was 50x what a normal human could do in 2023.

I thought the answer was interesting:

A work unit = one completed outcome bundle that would normally be a discrete task for a 2023 operator.

Examples from today:

- Pull Beehiiv conference leads + segment + enrich + CSV = 1 work unit
- Analyze HubSpot TTM trend + interpret impact = 1
- Build keynote HTML dashboard + screenshots/polish = 1-2
- Create Instantly read-only baseline + recommendation packet = 1-2
- Build Decision Cockpit spec/schema/templates/HTML = 3-5
- YPO email/LinkedIn rescue queue + copy = 1-2
- Shopify AI visibility scanner research + goal packet = 1
- Parallel checklist lanes = 4-6

So when I said 25-40 work units, I meant 25-40 discrete outputs, not 25-40 chat replies.

Human-equivalent estimate vs 2023:

Conservative: 40-60 hours
Realistic: 90-140 hours
Aggressive: 125-200 hours

My actual read: ~100-120 hours of 2023-style operator/analyst/fractional-chief-of-staff work got compressed into the 2.5-hour burst.

That’s roughly 40-50x throughput.

But the caveat matters: not all 100-120 hours were “final shipped public work.” A lot was:

- analysis
- packet creation
- read-only verification
- artifact production
- approval-gated execution prep
- system design

So it was more like 2.5 weeks of smart operator work, not 2.5 weeks of pure engineering shipped to prod.

The bottleneck is now not production. It’s decision compression. You can create 100 hours of work in an afternoon, but if it lands as 15 scattered approval packets, congrats, you invented executive homework. Very premium suffering.

It's only going to get faster from here.

[ericosiu @ericosiu]

The agency model as we know it is starting to crack.

For decades, services businesses have been organized the same way.

Client account at the top, then an account manager, then a row of specialists underneath. SEO, paid media, content, design, analytics.

Everyone owns a function. Knowledge lives in people's heads and scattered docs. Reporting is retrospective. Margins improve only when you squeeze utilization or hire cheaper.

That structure made sense when humans were the only execution layer. It doesn't anymore.

What I've been building toward is something I'm calling an agent-native revenue loop model.

Instead of organizing work by function, you organize it by business outcome. You have an outcome owner at the top.

Below that, channel loop owners who run end-to-end processes, keyword research through content production through linking through monitoring, as a single compounding loop.

And underneath that, an agent fleet layer where engineers are building and maintaining the agents that handle repeatable execution.

The shift sounds structural, but the real change is in how knowledge compounds. In the old model, knowledge walks out the door when someone quits. In the loop model, knowledge lives in infrastructure. Every loop gets smarter over time.

Margins improve through automation reuse and productized delivery, not headcount games.

And here's the thing Neil and I were getting into: when your margins improve because of this, don't just pocket the difference. Double down. Give more for the money. That's how you build a defensible position.

One-person teams sitting inside these loops, running more than any five-person team could run before.

That's where agencies are going.

[Camus @newstart_2024]

Steve Jobs famously said his kids didn’t use iPads.

Brené Brown highlighted this on Steven Bartlett’s Diary of a CEO. She’s been in rooms with tech billionaires and platform founders. When they’re asked what kids should study today, the answer is coding and physics. But when the same people reflect on their own success? They credit deep reading of philosophy, the Stoics, history, and the liberal arts.

Her concern: a quiet divide is forming — one group protecting deep thinking for their own children while the rest of us are encouraged to just keep scrolling.

In the age of AI, experts across the board are saying critical thinking, philosophical reasoning, and liberal arts skills are becoming even more essential — not less. AI can generate answers, but it can’t replace the human ability to ask the right questions, understand context, ethics, and meaning.

The people building our digital future seem to understand this deeply for their own families, yet design systems that often pull everyone else in the opposite direction.

Do you think we’re creating a two-tier system — deep thinkers at the top and scrollers below?

[Miles Deutscher @milesdeutscher]

/goal is f*cking insane.

You can literally turn your AI agents into 24/7 employees that work for HOURS with zero manual intervention.

This has to be the most powerful AI feature release of the month.

If you try one thing in AI this week, make it this.

[Croom Lawrence @croomlawrence]

@itsalexvacca ADS

[Alex Vacca @itsalexvacca]

We built 12 Claude Code skills that run our entire paid media ops across Google, Meta, and LinkedIn at ColdIQ (and we're giving the whole pack away).

Our head of growth Ivan Falco runs $200K/month in ad spend from a terminal. It's how we doubled client load this year without losing quality.

The skills do the work that used to fill our media buyers' calendars: spot creative fatigue, adjust bids, upload audiences, run bulk edits, flag broken campaigns, build reports.

Each skill does a specific job:

Google Ads:
→ keyword-analyzer: audits quality scores and finds keyword gaps
→ negative-keywords: reviews search terms and blocks wasted spend
→ performance-auditor: compares periods and flags what changed
→ search-terms: surfaces queries burning budget with zero conversions

Meta Ads:
→ audience-builder: turns CRM lists into custom audiences
→ creative-fatigue-analyzer: spots declining CTR before the metrics flag it
→ fatigue-monitor: flags when your audience is saturated
→ spend-tracker: tracks budget pacing across every campaign

LinkedIn Ads:
→ audience-builder: builds targeting audiences at scale
→ bid-optimizer: adjusts bids across campaigns in bulk
→ bulk-editor: mass edits campaigns, ads, and naming in seconds
→ creative-builder: generates ad creatives from brand specs

You drop them into Claude Code, connect your ad accounts, and tell it what you need. It reads the skill, plugs into the platform, executes.

300+ hours of work went into building these.

Comment ADS and we'll send all 12 over.

[GREG ISENBERG @gregisenberg]

I'm giving away a FULL course on how to build a managed AI agent business solo using Hermes Agent, Orgo, Obsidian, Codex, Claude Code etc.

Here's everything (47 minutes):

1. The offer: unlimited agents, unlimited usage, all infrastructure and security included. The customer gets a digital employee. They never think about tokens or models. You handle everything.

2. Don't niche down too fast. Try marketing agencies, law firms, insurance, manufacturing, real estate. See where the market pulls you. Then go vertical. Diverge first, converge later.

3. Every executive has the same problems regardless of industry. Too many emails, too many meetings, too many follow-ups, too many open loops. Solve those first. Then layer in vertical-specific skills.

4. The stack: Hermes Agent for the agent harness. Codex or Claude Code desktop to build and configure. Orgo for cloud computers so every agent lives in its own sandbox. Composio for one-click authentication across thousands of apps. Agent Mail to give every agent its own email. Obsidian for the knowledge base.

5. Use agents to build agents. Don't stress about setup. Use Claude Code or Codex to install and configure Hermes inside a VM. Use Perplexity MCP, Context7, and Exa for up-to-date docs. Your agent sets up your customer's agents.

6. GPT 5.5 is the best model right now. Efficient with tool calls. Doesn't eat tokens like Opus 4.7. For cheaper tasks, GLM 5.1 from ZAI is the best open source option.

7. Set up watchdogs for gateway crashes so they auto-restore. Have agents email you when cron jobs break or skills fail. Your customer should never have to tell you something is broken.

8. Get customers through content. If someone jumps on a call and already knows who you are and what you sell, that's the position you want. Content is the most leveraged thing you can do in 2026.

9. Keep scope tight. One to two requests at a time, delivered in under 48 hours. Use Trello for customer-facing project management. Send Loom updates at random hours to show you're always working on their agents.

10. If you can set up Claude Code, Hermes, or OpenClaw, you have a skill that 99% of business owners don't have and would pay $5k/month for. You're probably not giving yourself enough credit.

shoutout to @nickvasiles from @orgodotai for coming back on @startupideaspod and sharing the full playbook. tools, stack, fulfillment, everything.

this type of episode isn't shared anywhere on the internet. this is the alpha people keep for themselves.

i will keep sharing if you keep watching.

you could watch netflix or you can watch this (link below)

https://t.co/Z4PM5I7d0S

watch

[Croom Lawrence @croomlawrence]

@ashiqur_ai CLAUDE

[Shanto @ashiqur_ai]

I built 131 Claude skills for outbound, content, LinkedIn, SEO, and growth into one plugin.

131 skills. 11 domains. One /bootstrap command.

Our clients kept hearing the same thing from prospects: *"Your outreach actually sounds like you."*

That doesn't come from better prompts. It comes from a system that reads your brand, voice, and ICP automatically.

▶️ The foundation (built once)

→ /bootstrap - onboards Claude to your brand, voice, and ICP. Every skill reads that context automatically.

→ ICP document - loaded once, referenced by every skill without manual pulling.

→ Brand and voice layer - installed at setup. Every output reflects your positioning, not a template.

Most teams skip this and go straight to prompting. Then wonder why everything sounds the same.

▶️ The skill layer

→ Outbound and email for personalised sequencing at scale

→ LinkedIn, Twitter, YouTube for social across every format

→ Content and copywriting that reflects your documented voice

→ Analytics and research for signal detection and account intelligence

→ Strategy and positioning for ICP, messaging, and competitive work

47 growth and product skills alone.

▶️ The execution layer

→ Plain-language task detection - skills activate automatically

→ Cross-referencing - a cold email pulls from brand, voice, and ICP simultaneously

→ Output grading - if it reads generic, one fix: make it specific enough it can't describe any other company

Compatible with Claude Code, Claude Cowork, and any Agent Skills spec agent.

▶️ Repurpose

→ One validated outbound skill = one framework cross-referenced into content, SEO, positioning, and paid. No rebuilding.

→ Repurposing is not copy-pasting. It's cross-referencing.

▶️ Maintain

→ /bootstrap refresh updates every skill automatically

→ Monthly voice refresh. Quarterly domain audit.

The system gets smarter the longer it runs.

▶️ Delivery

→ Claude Code or Claude Cowork. 4 installation methods in the setup guide.

Bootstrap → detect → activate → cross-reference → draft → grade → repurpose → refresh

Your skill library is your GTM brain.

Reply "CLAUDE" and I'll send you the full breakdown 👇

@ashiqur_ai