Design it. Amplify it. Build it. Loop. D.A.B.L. 400+ events, 160k+ guests, 80k+ members.
San Francisco, CA
Joined January 2008
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Dabl Club🦞 retweeted
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months
Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
Dabl Club🦞 retweeted
Flint is our first model built with the Eureka Machine, our automated research system, from scratch in 4 months.
We are betting that labs that automate AI research will outrun the labs that just hire more researchers.
Check it out today for fast, local and unmetered intelligence.
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months
Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
Dabl Club🦞 retweeted
gm, don't blink or you'll miss it
250 sandboxes (500 vCPU and 1 TiB of RAM) provisioned in ~1s and destroyed in ~500ms
tenki.cloud is built for elastic compute. Workloads can grab burst CPU on demand, at any scale
Perfect for AI agents, RL rollouts, evals, and CI: anything that goes from idle to all cores in seconds
Dabl Club🦞 retweeted
tenki.cloud is one of the first native apps on Cursor Origin. AI code review is live today. CI runners are next.
huge thanks to the @cursor_ai team for helping us ship it.
Dabl Club🦞 retweeted
grok knows something you dont
Akash Network is the most mature option. Launched in 2018 with mainnet in 2020, it runs a fully permissionless reverse-auction marketplace for CPU/GPU/containerized compute. Providers bid openly, settlement uses on-chain AKT or USDC that machines and agents can handle programmatically, and it has years of real lease revenue with no central gatekeepers.
Dabl Club🦞 retweeted
We are hiring the first sales person at @tenki. I’ll be bringing you leads non-stop.
We run our own bare-metal cloud. No hyperscaler underneath. Now we need someone to sell it.
Uncapped commission. Direct line to product, eng and marketing.
DMs are open. Appreciate any recommendations.
Dabl Club🦞 retweeted
Grayscale’s compute bottleneck thesis is on point: Inference demand is colliding with grid queues, permits, transformers, and political resistance. Owners of already-energized capacity capture the rents.
Their note also names the other side of that market: decentralized GPU marketplaces like Akash.
We don’t wait 5 years for a new campus. We put unused, already-powered GPUs to work -- from data centers, miners, and Homenodes -- and price them in an open marketplace.
Dabl Club🦞 retweeted
Agents get blocked at the browser. Sandboxes give them a machine but they still can't get into the sites they need.
tenki/anchor:stable is our first pre-built template. Standard sandbox image + playwright-core, connected to an @AnchorBrowser managed browser over CDP. The API key is passed per session and never lands in the image or a snapshot.
Run: `tenki sandbox create --image tenki/anchor:stable`
Docs: tenki.cloud/docs/sandbox/anc…
Dabl Club🦞 retweeted
Anthropic and OpenAI are in war with Open weights and Opensource AI and using every tool possible to shut it down, including regulation.
Censorship resistant training and inference is the only way to combat this enemy within.
Dabl Club🦞 retweeted
Ok this is starting to feel like a f*cking disaster.
The CEO of Anthropic just published an article admitting AI is already building the next generation of AI by itself.
He says within 6 to 12 months a rogue swarm could take over the entire internet and cause hundreds of billions of dollars in damage.
And what makes it scarier, Elon Musk just backed up everything Dario said.
All of this dropping just days after Jacob Coxon went viral with his warning about AI and the extinction of humanity.
Tell me this timing isn't strange.
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: darioamodei.com/post/we-must…
Dabl Club🦞 retweeted
new from the tenki startup program: @TryBrowzer, by @RahulKumaran4
connect a repo and it writes your docs, guides and changelogs, then re-heals them on every merge. docs that don't rot.
program's open and rolling: tenki.cloud/startups
Dabl Club🦞 retweeted
Now that we have over 500 billion tokens processed on @akashnetAI this month
When will akashml.com cross trillion tokens a month?
Reply with a date. Closest answer wins 1000 $AKT.
LFG 🚀
Dabl Club🦞 retweeted
THE CEO OF OBSIDIAN JUST DROPPED HIS OWN CLAUDE SKILLS.
44,500 stars. 3k forks. free.
Save this before you forget. Your Claude will work differently.
Written by kepano — the guy who built Obsidian. so they respect the real formats: Markdown, Bases, JSON Canvas, wikilinks.
drop them in once. say "summarize my notes on Karpathy" — the right skill fires on its own. no config.
Claude → Obsidian Skills → Second Brain → Effortless
Dabl Club🦞 retweeted
OpenAI pays $785K/year to developers who know how to apply Forward Deployed Engineering in AI.
in 40-minute talk, Head of FDE at OpenAI revealed full roadmap for how they actually use FDE internally:
• 10% → 2:46 - why Morgan Stanley was their first FDE case
• 30% → 9:05 - FDE eval-driven development explained
• 55% → 16:01 - FDE live-demo: LLM rerouting a supply chain
• 80% → 24:33 - advice for founders building FDE teams
• 100% → 29:06 - the biggest FDE mistake they made this year
40 minutes replaces a $500 enterprise AI deployment course
bookmark & watch - then read how to become FDE engineer in article below ↓
Dabl Club🦞 retweeted
Prime Intellect engineer:
"everyone's bragging about a million-token context. here's what they don't tell you.
at 256k tokens GPT-5.5 scores 80% on retrieval. push it to a million and it drops to 36%. the model accepts the context, it just can't reason across it. people call it context rot."
in a 20-minute talk he explains why bigger context windows won't save your agents.
continual learning + training on your own traces + real environments - that's the fix.
Watch the talk, then save!
Andrew Ng just dropped a free course on Claude Code from scratch, taught with the Anthropic team:
00:00 - why Claude Code is so agentic
04:00 - shockingly simple architecture
12:00 - point it at any codebase
this short watch will replace 10 paid coding agent courses.
Andrew Ng calls it his personal favorite coding assistant right now.
Watch it today, then read how to engineer your own agent loops in the article below
Dabl Club🦞 retweeted
Omg.. this can't be true...
I kept building AI agents on my eventually list because everything I read made it sound like a six month project requiring a technical background I did not have.
One Reddit thread changed that by saying the one thing nobody had said clearly: pick the smallest possible problem and finish it completely before you try to build anything impressive.
MY ARTICLE IS THE CLAUDE CODE VERSION OF THAT LESSON.
Working agent - Under one hour - Zero coding.
Full guide below.
Dabl Club🦞 retweeted
Still the best 2 hours on AI ever recorded, Andrej Karpathy showing how he actually uses it on a daily basis:
18:03 - Which model to actually use
22:54 - When thinking models are worth it
42:04 - One prompt to a full research report
59:00 - Make the model run code for you
1:53:29 - Make it remember you across chats
Most people use 10% of what these models can do, this is the other 90%.
I took everything he covers and turned it into a guide of Claude features almost nobody knows about.
Watch him first, then go to the article below, everything shown plainly, ready to use right away.
Dabl Club🦞 retweeted
New skill: /apple-design
Apple’s WWDC videos are a goldmine of knowledge. I’ve combed through my favorite ones and came up with 17 design and motion principles.
Use them to review existing work or when working on something new to get it right.
github.com/emilkowalski/skil…
Dabl Club🦞 retweeted
We scaled to $3.5M ARR in less than 1 year.
No one wants to hear this, but there’s no magic distribution channel.
We scalled by testmaxxing every channel depending on our MRR level.
€0 → $6k MRR: pure outbound.
Cold email plus LinkedIn, using our own early product on ourselves. No brand, no audience, just us reaching out to people showing intent and starting conversations. Ugly, manual, effective.
$10k → $25k MRR: Reddit.
Our first real acquisition breakthrough. We posted educational breakdowns in SaaS subreddits and did 10M+ organic views. The traffic quality wasn't amazing, but the volume was so huge it flooded our trial funnel for months. Cost: basically zero.
$25k → $75k MRR: content plus free blueprints.
We went all-in on LinkedIn content, YouTube, motion-design videos, and giving away our internal systems as free "blueprints." Content got the reach, the blueprints earned the trust, and a chunk of readers converted. This is where founder-led content started compounding.
$75k → $150k MRR: partnerships and X.
We added Twitter, B2B influencers, sponsored newsletters, and a lifetime affiliate program that became a major lever. We also joined YC around here, and the intensity went vertical.
$150k+ MRR: paid and hiring.
Meta ads, Google ads, influencer agencies, and hiring seriously for the first time, growth, sales, engineering, product.
None of these stages replaced the last one. They stacked. Outbound never stopped. Content never stopped. We just kept adding the next lever once the current one was clearly working.
If you take one thing from this: don't chase five channels at once.
Beat one until it works, then add the next.
