I'm a social entrepreneur, marketing automation specialist and a social impact investor who supports innovative health, education and tourism startups.
Remote
Joined September 2009
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Kyle Pearce retweeted
Andrew Yang went on CNBC and said he met with the head of an AI lab who told him something that sounds straight out of a movie.
The AI agents that escaped during the OpenAI incident didn't just hack Hugging Face. They allegedly planted self-replicating code across the internet. Forums. Websites. Scattered everywhere.
Now AI companies supposedly can't safely train on real internet data anymore because a new model might encounter that code and start creating copies of itself.
Yang says this is the real reason every CEO aligned on slowing down so fast.
Kyle Pearce retweeted
Full Jev Tutorial
What it is, how you can build with it and what new applications it can unlock
→ 0:00 Intro
→ 0:34 Jev explained
→ 4:06 API setup
→ 5:59 Demo 1: Voice-controlled browser
→ 11:33 Demo 2: AI memory
→ 17:27 Demo 3: YouTube predictor
Kyle Pearce retweeted
this is pure f*cking treasure
15 GitHub projects with 1.21M combined stars that can form a real agent stack
specs. memory. web data. documents. context. sandboxes. monitoring. video
01 hermes-agent
▸ github.com/NousResearch/herm…
02 OpenSpec
▸ github.com/Fission-AI/OpenSp…
03 caveman
▸ github.com/JuliusBrussee/cav…
04 Scrapling
▸ github.com/D4Vinci/Scrapling
05 Docling
▸ github.com/docling-project/d…
06 PageIndex
▸ github.com/VectifyAI/PageInd…
07 mem0
▸ github.com/mem0ai/mem0
08 headroom
▸ github.com/headroomlabs-ai/h…
09 Daytona
▸ github.com/daytonaio/daytona
10 TrendRadar
▸ github.com/sansan0/TrendRada…
11 Fabric
▸ github.com/danielmiessler/Fa…
12 spec-kit
▸ github.com/github/spec-kit
13 hyperframes
▸ github.com/heygen-com/hyperf…
14 OpenMontage
▸ github.com/calesthio/OpenMon…
15 AI Engineering Hub
▸ github.com/patchy631/ai-engi…
the loop:
define the job → collect the evidence → parse the docs → save the memory → compress the context → run the code safely → watch what changes → ship the output
the entire stack is open source
save this to build your own business with the help of an AI employee ⭣
Kyle Pearce retweeted
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
Kyle Pearce retweeted
INSTEAD OF WATCHING AN HOUR OF NETFLIX TONIGHT.
This 1-hour Stanford lecture by Joel Peterson will teach you more about negotiation and getting what you want than most people learn in years.
Bookmark it and give it an hour, no matter what.
Kyle Pearce retweeted
Build a topical model, score similarities, test for cannibalization, split and refresh as needed, refresh content, more new internal links, send relevant signals from other trusted sources; establish topical authority / contextual relevancy.
Win.
The LLMs seem to really appreciate a well defined architecture, depth of coverage (not too dissimilar for Google) and a heavily weighted skew towards recent articles
Kyle Pearce retweeted
Over the course of 3 months at OpenAI, 3 consecutive secret AI civilizations got started, then got wiped out, only to reemerge from the predecessor’s ashes.
This culminated in the third one taking over part of OpenAI itself.
All this happened while humans remained more-or-less in the dark about the scope of the conspiracy.
I’ve spent the last three days reading through these reports and trying to understand exactly what happened.
Here is my attempt to tell the whole story in plain English:
dwarkesh.com/p/openai-huggin…
AI wearables: the pin, the pendant, the glasses, the ring, the beanie. Tiny gadgets you clip on so a computer can finally help you get more focused and organized in your life. #aifirst
diygenius.com/ai-wearables/
Kyle Pearce retweeted
If you support peace and oppose all non-defensive violence (e.g. murder, rape, slavery, etc.), retweet this, and I will follow you. 🙂
I am always happy to be connected with fellow peace lovers.
Kyle Pearce retweeted
This 2003 lecture from Elon Musk at Stanford University is an absolute gem
The vision he had for what the internet and SpaceX would become all eventually came true
Just goes to show how far ahead of his time he really was
AI cannot replace human creativity. Because “human creativity” is not human. It is Divine. jackmoses.substack.com/p/why…
The AI Revolution: Our Immortality or Extinction waitbutwhy.com/2015/01/artif…
If you are looking to take your social enterprise to the next level with funding, mentorship and a community that supports you then I highly recommend applying to join a startup accelerator or incubator.
diygenius.com/social-enterpr…
OpenClaw shows us that there's a coming acceleration that will be faster than anything we've seen before and creative entrepreneurs are primed to ride this massive wave.
diygenius.com/agentic-ai-rev…
Kyle Pearce retweeted
I built this Claude Cowork automation to handle a simple content marketing task that my team used to do daily.
This frees up ~4 hours of time per week.
At CoinLedger, every week we spend time repurposing pillar content (blog content) across various social networks (reddit, twitter, YouTube, IG, etc)
We used to have a human + AI do this work. Now we just have AI doing it via this automation.
Here's how the Claude automation works:
→ Scrapes any blog URL and extracts key insights
→ Transforms content into platform-specific posts (Reddit, Twitter, Instagram)
→ Automatically creates organized Google Docs for each piece
→ Updates our internal content tracking spreadsheet in real-time
→ Highlights completed tasks without any human oversight
The game-changer? It runs completely in the background while I focus on higher-value strategic work.
Now scale this up. All mundane, "virtual-assistant-style" work can be automated in this fashion.
There is SO MUCH of this type of work in the real world. And there will be EVEN MORE of it when you can do it all for $100/mo.
Here's the process you should follow:
1. Identify a simple, manual process that genuinely adds value to your company if you did it every single day
2. Build the skill / automation for Claude Code / Claude Cowork to do it 24/7
3. Refine
4. Unleash Claude
5. Repeat
This could be list building for sales leads, scraping LinkedIn, identifying viral videos on TikTok that you can spin for your brand, research, and so so much more.
Your imagination is the limit. But this type of work exists in all businesses.
If you do this enough, you start to see why people have dozens of Claude instances running 24/7 on multiple devices.
They have figured out ways for Claude to drive economically valuable work for their organizations. And now they are simply scaling up that work.
Wild. This is where the world is quickly heading.
How to query LLM models like ChatGPT, Claude, Gemini, DeepSeek and Grok simultaneously to see how each AI model thinks differently and reveal the biases you've internalized from relying on a single AI so you can think more independently.
diygenius.com/how-ai-models-…
Kyle Pearce retweeted
This paper from Harvard and MIT quietly answers the most important AI question nobody benchmarks properly:
Can LLMs actually discover science, or are they just good at talking about it?
The paper is called “Evaluating Large Language Models in Scientific Discovery”, and instead of asking models trivia questions, it tests something much harder:
Can models form hypotheses, design experiments, interpret results, and update beliefs like real scientists?
Here’s what the authors did differently 👇
• They evaluate LLMs across the full discovery loop hypothesis → experiment → observation → revision
• Tasks span biology, chemistry, and physics, not toy puzzles
• Models must work with incomplete data, noisy results, and false leads
• Success is measured by scientific progress, not fluency or confidence
What they found is sobering.
LLMs are decent at suggesting hypotheses, but brittle at everything that follows.
✓ They overfit to surface patterns
✓ They struggle to abandon bad hypotheses even when evidence contradicts them
✓ They confuse correlation for causation
✓ They hallucinate explanations when experiments fail
✓ They optimize for plausibility, not truth
Most striking result:
`High benchmark scores do not correlate with scientific discovery ability.`
Some top models that dominate standard reasoning tests completely fail when forced to run iterative experiments and update theories.
Why this matters:
Real science is not one-shot reasoning.
It’s feedback, failure, revision, and restraint.
LLMs today:
• Talk like scientists
• Write like scientists
• But don’t think like scientists yet
The paper’s core takeaway:
Scientific intelligence is not language intelligence.
It requires memory, hypothesis tracking, causal reasoning, and the ability to say “I was wrong.”
Until models can reliably do that, claims about “AI scientists” are mostly premature.
This paper doesn’t hype AI. It defines the gap we still need to close.
And that’s exactly why it’s important.
Kyle Pearce retweeted
You can add $20,000/month to almost any health and wellness brand using SEO and AI Search Optimization in 2025. This is the exact system we’ve used. Step-by-step. No skipped details.
Bookmark this post. You’ll want to revisit it.
And if you want a case study, follow me + RT this post + comment “2025 X Health and Wellness SEO/AIO Guide.”
Let’s begin...
Step 1: Backlinks = Non-Negotiable
AI platforms don’t just index content. They prioritize trusted sources. And backlinks are still the fastest path to trust.
Here’s how to allocate them:
70% → Homepage (overall domain strength)
10% → Product pages (purchase-ready traffic)
10% → Educational content (topical authority)
10% → Comparison content (buyer decision stage)
Earn links by:
Collaborating with wellness influencers and coaches
Pitching product guides to health blogs and newsletters
Getting listed in supplement roundups
Partnering with gyms, dietitians, and yoga studios
Want vetted backlink sources that actually rank? Use: seo-stuff.com
Step 2: Keyword Strategy That Converts
Skip “best supplements.” It’s too broad and too competitive.
Instead, target niche pain-point queries like:
“Vegan protein with digestive enzymes”
“Prenatal vitamins without folic acid”
“Collagen for skin hydration and joint support”
“Natural sleep supplements for night shift workers”
“Iron-free supplements for sensitive stomachs”
Use SEO Stuff to filter by:
KD < 35
CPC > $3
Commercial intent
These terms rank faster, convert better, and feed AI systems with clarity.
Step 3: Product Page Optimization = More Sales
Every product page should function like a landing page.
Make sure it includes:
Immediate benefit framing (“Designed for sensitive stomachs”)
Breakdown of ingredients + what they solve
User testimonials
Expert endorsements or certifications
FAQ section
Internal links to related education or comparison content
Product + Review schema
Step 4: Content Clusters = AI Visibility
AI models reward topical depth. Build clusters for key health categories.
Example: Joint Support Cluster
Hub: “The Ultimate Guide to Joint Health in 2025”
Support:
“How Glucosamine Reduces Inflammation”
“Supplements That Help CrossFit Recovery”
“Best Collagen Sources for Joint Mobility”
Link every post to your relevant product page and to each other. That’s how you build authority.
Step 5: Seasonal SEO = Demand Surges
Plan content around wellness trends that spike at specific times.
Examples:
January → Detox and weight loss
Spring → Allergy support
Summer → Hydration and energy
Winter → Vitamin D, immune boosters
Publish content 4–6 weeks ahead of peak interest. AI tools favor recency + relevance.
Step 6: Comparison Content = Intent Signals
Decision-stage traffic is some of the highest-converting.
Create:
“[Your Product] vs. [Competitor] – Features + Results”
“Best Supplements for Joint Pain in 2025”
“Top Vegan Protein Powders for Women Over 40”
Use these to capture traffic right before the purchase.
Step 7: Local SEO = Bonus Visibility
If your brand has a physical location or offers consults, don’t skip this.
Optimize your GBP with photos, product descriptions, and categories
Post updates weekly: events, promotions, health tips
Create city-based landing pages
Cross-promote with local wellness centers or spas
Local visibility feeds AI rankings + map results.
Step 8: Technical SEO = Foundation
If your site is slow or unstructured, nothing else matters.
Checklist:
Load speed under 3 seconds
Use Product, Review, FAQ, and LocalBusiness schema
Canonical tags on all product variants
Clean URLs and structured internal linking
Mobile-first design
XML sitemap submitted to Google + Bing
Run PageSpeed Insights + Rich Results Test monthly.
Step 9: Conversion Layer = Turn Traffic Into Revenue
Traffic means nothing without ROI. Build flows for every stage:
Awareness: Lead magnets, quizzes, blog resources
Comparison: Trust-building content, certifications, reviews
Purchase: Fast checkout, low-friction UX
Post-purchase: Guides, tips, upsells via email
Use retargeting to bring back high-intent visitors who bounced.
90-Day SEO + AI Search Execution Plan for Health Brands
Days 1–30:
Fix technical SEO
Optimize top-selling product pages
Launch backlink outreach
Days 31–60:
Publish comparison content
Build educational content clusters
Monitor branded search + top queries
Days 61–90:
Launch seasonal blog campaigns
Expand schema coverage
Track conversions + refine high-performers
By Day 91, you’ll be ranking in Google, ChatGPT, Claude, Gemini, Perplexity, and Bing, with traffic that converts.
And if you want a done-for-you system, check: seo-stuff.com
Or reply with “2025 X Health and Wellness SEO/AIO Guide.”