Phil Greene

🚀 Building AI-powered businesses in public
🌐 I help local businesses grow with websites & automation
💡 Sharing what works, from $0 to revenue

[Suraj Sharma @suraj_sharma14]

22 platforms where founders actually hang out:

1/ X ➝ build in public, hiring, fundraising signal
2/ Indie Hackers ➝ revenue screenshots + honest metrics
3/ Product Hunt ➝ launch day + maker traffic
4/ Hacker News ➝ technical founders + Show HN
5/ YC Startup School ➝ free founder network + curriculum
6/ MicroConf ➝ bootstrapped SaaS owners
7/ DEV ➝ indie makers publishing in public
8/ Hashnode ➝ long-form founder writing
9/ Makerlog ➝ daily progress streaks
10/ BetaList ➝ early waitlists + soft launches
11/ Tiny Startups ➝ small IT / bootstrap shops
12/ FounderPass ➝ startup perk deals
13/ RevGenius ➝ B2B SaaS GTM community
14/ SEO Wins ➝ SEO marketers swapping wins
15/ HubSpot Trends ➝ startup / marketing trend drops
16/ GrowthHackers ➝ growth experiments
17/ Designer Hangout ➝ product designers
18/ r/startups ➝ founder war stories + advice
19/ r/SaaS ➝ SaaS pricing, churn, stack talk
20/ r/SideProject ➝ feedback before you launch
21/ Failory ➝ post-mortems and founder lessons
22/ Founder Cafe ➝ founder networking

Bookmark this.
Next time someone asks “where do founders hang out?” send this.

[Phil Greene @vtguy65]

@suraj_sharma14 Yeah def worth a save. Thanks.

[Phil Greene @vtguy65]

@hridoyreh Yeah, that is a super helpful list. Thank you.

[Phil Greene @vtguy65]

@facelesscanup Channels

[Phil Greene @vtguy65]

Tried running small LLMs on a Raspberry Pi with a Hailo AI accelerator. The surprise? Small local models start to shine when they're tied to hardware and workflows you actually use, not just as abstract tech demos. It’s a shift from theory to tangible utility.

[Phil Greene @vtguy65]

I automated my first AI reel with an n8n pipeline: Airtable to script, media, TTS, FFmpeg assembly, Telegram review, and back to Airtable. The voice was creepy, but it worked end-to-end. That rough success taught me more than polishing parts separately ever could.

[Phil Greene @vtguy65]

@AI_creator_Yara Claude

[Marceline Yara @AI_creator_Yara]

19 year old Japanese student built a trading bot with Claude Code in 2 days.

Used his iPad as a second monitor.

First night: $6,732 profit.
Starting capital: $68.

Total profit so far: $750,000.

[ 𝐍𝐨𝐭𝐞: 𝐅𝐨𝐥𝐥𝐨𝐰 𝐌𝐞 @AI_creator_Yara 𝐅𝐨𝐫 𝐢𝐧𝐬𝐭𝐚𝐧𝐭𝐥𝐲 𝐚𝐮𝐭𝐨 𝐃𝐌]

Here's how it works👇

The bot scans over 50 markets simultaneously.

Syncs live BTC data from Binance every second.

Spots price errors before humans even notice.

The edge is pure speed + pattern recognition.

While traders stare at charts trying to predict the next move, his bot is already executing on mispricing across dozens of markets.

No guessing.
No emotions.
No hesitation.

Just Claude Code logic finding gaps that close in seconds.

He built the entire system in 48 hours:

→ Claude Code handles the trading logic
→ Binance API feeds real-time BTC data
→ iPad displays multi-market monitoring
→ Executes trades when arbitrage windows open

The system runs 24/7.

Every price dislocation = profit opportunity.

Most people are still trading manually, refreshing charts, second-guessing entries.

Meanwhile this 19 year old engineering student turned $68 into $750K by letting Claude Code do what humans can't: process 50 markets instantly and execute without fear.

Why are people still trading manually?

I'm giving away the exact Claude Code setup for free.

24 hours only.

To get it 👇
1️⃣ Like and Repost
2️⃣ Comment " 𝐂𝐥𝐚𝐮𝐝𝐞 "
3️⃣ Follow Me: @AI_creator_Yara (so I can send it via DM)

[Phil Greene @vtguy65]

@paulpagepilot Regret

[Paul Gotea @paulpagepilot]

probably going to regret this...

$77K in 7 days selling products found from tiktok comments to women 45-65 on facebook at 10pm in 5 countries at $2-4 ads. the same products cost $23 ads in the US. same product. same buyer. different country. different price. 70 minutes of decisions that week

I put the full $13k/mo system into a 36-page guide:

> how to find your competitor's supplier name in their own page source code in 30 seconds (ctrl+F "vendor", search on alibaba, 50% cheaper)
> how to crack their "exclusive" discount codes by typing 5 URLs anyone can access (/discount/WELCOME10, SAVE20, VIP25)
> how to read the pages they tried to hide from google (/robots.txt, wholesale pricing, test collections, influencer commissions)
> why mexico at $3.92 ads, poland at $2, and turkey at $2 with installments that make $60 look like $10/month
> the ad URL trick that pre-loads the expensive variant + pre-checks the subscription before the page finishes loading
> how to steal 5 competitor email funnels by abandoning 5 carts and screenshotting every email for 72 hours ($0)

→ the 36-page $0-$10K/mo ecom playbook
→ the 6-point product page checklist to go from 1.2% → 3.4% CVR
→ the full video walkthrough - finding products, building pages, launching ads, going live

Want it?

Follow me, like this post, RT this post and comment "REGRET".I'll send it over.

[Phil Greene @vtguy65]

@bretonwill GTM

[Phil Greene @vtguy65]

@iamtyfrankel Clients

[Phil Greene @vtguy65]

@everestchris6 Thank you😉

[Phil Greene @vtguy65]

@ThebilalSEO Pin

[Phil Greene @vtguy65]

Laptop's in the shop until tomorrow. The backup is a 2017 with a 128GB drive, so no Xcode, and no ThumbDNA builds.

So today I'm rewriting the https://t.co/lXTeWboIjH copy and my bio so the app is explainable in one line.

Blocked on the build, not on the work.

[Phil Greene @vtguy65]

Decomposing tasks into narrow, typed decisions improves every AI stack—even

Claude Haiku jumped from 18% to 53% accuracy when placed inside structured workflows.

The future of AI isn't just bigger models. It's machine-native micro-decisions.

Are you cascading your agent stack yet? Let’s discuss below.

[Phil Greene @vtguy65]

Most AI agents are burning cash on frontier LLMs for decisions that don’t need language generation.

Tool selection. Ticket routing. RAG filtering. Retry logic.

A co-creator of ChatGPT spent two years in stealth fixing exactly this.

Meet Jev by TypeSafe AI: 🧵👇

[Phil Greene @vtguy65]

The reality check (the "jaggedness"):

1. Type safety is NOT correctness. It can pick the wrong enum cleanly.

2. It takes instructions literally (no intuition for what you "meant").

3. Prompt injection still applies if user text is in the state.

Keep arithmetic and safety in regular code. Use Jev for the narrow judgment.