Node Smith

one lie at a time

[Node Smith @NodeSmith_]

@harshilmathur An engine is nothing if it can't take you from point A to B

[Node Smith @NodeSmith_]

@divyaranjan_ @Microsoft Well deserved

[Capx AI @0xCapx]

gcapx

[Node Smith @NodeSmith_]

Claude server is down. Or is it just me?

[Divya Ranjan @divyaranjan_]

"AI made you faster. Your brain didn't get bigger"
@karpathy's recent post went viral for sharing how he uses LLMs to build personal knowledge bases. Interestingly, I've been building a more holistic version of what he described for the past few weeks.
Introducing Pattrns, an AI interface crafted for deep parallel work, with a partner called Dots that just knows you and grows with you from day one.

Why? A few months back, I realised I was working with so many tools / terminals / windows. AI had made me 10x faster, but to be efficient at all times required all my focus and constant attention/depth. AI was creating 100x more output daily than my brain could process, and the constant context switching and orienting myself again and again was killing me. Alsooo, why is every AI chat so linear? The entire experience of using AI was disorienting me. Another agent wasn't the solution for me but an entire interface that connected all the dots for me automatically was.

So I built Pattrns. Here's what it actually is:
Pattrns is a visual environment to think and do more knowledge work with AI. It keeps you oriented at all times and uses visual threads, kind of like how our brain works (think your prefrontal cortex externalised). Your research, your references, and your thoughts for all your different threads all live side by side as context for AI. The interface gives you one view with infinite depth. You can run parallel sessions across projects, drop a massive question in one thread, and switch to another one to keep working. Focus when you want depth, expand when you want the big picture. My early version was actually an infinite canvas with chat, but using it daily became a bottleneck. Infinite canvases eventually just turn into noise especially for boards that keep evolving.

Then there's Dots, the ambient intelligence underneath it all. It learns your taste and decisions by watching your actions. It pays attention to what you care about, what you curate, and what you engage with (also like how much, think pagerank). Over time, it just knows you. You never have to re-explain your thinking, your taste, or your decisions ever again. It does this by auto-organizing and constantly updating your memory graph into a board ("Me") for you to look at, edit, or chat with. You are also always fully aware of what it knows.
The underlying rule is simple. Organization is Dots' job, but thinking and creating is yours. So every chat just feels like you're talking to someone who already gets you.

This is how it feels to use:
Day one: During onboarding, you import your past AI chats (Claude / ChatGPT) and data (Apple Notes, Notion, Evernote). Dots reads through everything, starts creating your Me board with your entire memory graph, auto resolves conflicts, and just knows you from the start.

Week one: You're working across three projects. You drop research into one board, brainstorm in another, execute in a third. Switch between them instantly. The AI already knows what each board is about because it sees your cards, your structure, your context. No re-explaining. You can just start chatting anywhere and it stays updated at all times.

Month one: Dots knows you and has seen what you've been creating and doing. What you build on vs what you explore and move on from. It's learned your taste through your actions, not your words, relative to the different boards. When you ask it to design something, it already knows you hate rounded corners in that exact project. When you're debugging, it remembers you prefer logs over breakpoints. Every correction you make teaches it. Every card you create sharpens its understanding.
The result? You stop maintaining tools and start using them. No tagging. No filing. No "I should organize this later" guilt. Conversations are JSONL you can grep, Git tracks everything. Zero lock-in.
Dots understands the context as the what and the conversations that led to it as the why.

And also, there's a lot more under the hood
Everything stays local (your brain is a folder you own). Privacy is a mission statement, nothing is stored online. You can literally just drop your entire Obsidian vault here and watch it get organized beautifully. It's powered by Anthropic's Agent SDK, so Dots is as capable and agentic as it gets. You can bring all your MCPs, and if an API or skill doesn't exist, just dump things and ask Dots to create it. Repeat something enough and Dots suggests turning it into a skill automatically.

Every chat has reply threads (like Slack) so you can drill into any thought without losing the main conversation, and a TLDR button to catch up in seconds.

Who is it for?
I believe there are 2 kinds of people doing major work with AI:
1. Those who want fully autonomous agents that take a prompt and do everything. OpenClaw, AI chief of staff, that whole wave.
2. Those who sit with it, plan, execute step by step so their exact taste is translated into the output.
Pattrns is for the latter! You will soon even be able to use the browser extension and Pattrns MCP to bring your own context to any chat agent you use daily, so it automatically starts thinking like you.

Anyway Pattrns is a product I always wanted for myself and I deeply care about this cause. My ultimate mission is to eventually have an interface that is as intuitive as paper and pen along with an ambient AI that watches you and unifies everything you do in one place, constantly organizing your context so you keep coming back to it. What would that eventually feel like? That Pinterest image you keep going back to on your browser, it'll soon be auto-organized in a space for you.

The early access for the beta is going live today (Invite only. Mac only for now). Reply with what you're building right now and I'd love to send you an invite soon!

PS: There was no AI ever used while crafting this entire product experience, just pen and paper. Only used AI to build it. Taste is human :')

[Capx AI @0xCapx]

riding the AICM wave

[Capx AI @0xCapx]

Capx × @elevenlabs

The Capx ecosystem now has priority access to the ‘ElevenLabs for Startups Program’ 🤝

Founders part of Capx ecosystem get:
→ 12 months free access
→ 33M characters (~600 hours of audio)
→ Direct POC with ElevenLabs

Voice is becoming the interface layer for AI agents.

We're making it available to Capx ecosystem apps from day one.

[Capx AI @0xCapx]

New partnership update 💪

Capx is very proud to announce our new partnership with Capx, to build the future of fully autonomous and ownable AI apps.

Thank you for your attention to this matter.

[Capx AI @0xCapx]

2026 — the era of solo founders has begun!

the moat is not code
its ownership + distribution

time to ship agentic ai apps going public on day 1

[Nikola Mrkšić @nikola_mrksic]

I quit Apple because I knew Siri would never make an actual dent in the world.

Not because the tech was bad.

But because the entire concept had to be rethought.

General-purpose AI assistants try to do everything, and end up doing nothing well.

When you optimize for breadth, you can't go deep enough to actually complete transactions.

Siri can tell you about restaurants but it can't book one, can't take payments, can't modify reservations, can't handle the messy back-and-forth that happens in real conversations.

It's a search interface, not a transaction engine.

When we started @polyaivoice, we made one decision: We only do customer service calls.

Yes! Just one single thing.

We wanted to answer your calls so your customers can talk to AI agents that actually know what they're doing.

And that focus is exactly why we handle 500M+ calls today.

This is what actually happens when you go narrow:

1️⃣ you can train on real data that matters.

We've trained on hundreds of millions of actual customer service calls across hospitality, banking, logistics, and healthcare.

And I'm not talking about web-scraped text, or synthetic conversations.

I'm talking about real calls with real edge cases, real accents, real background noise, real payment failures, and real angry customers.

Our model know what "I need to move my reservation" sounds like in 45 different languages because they've heard it millions of times.

2️⃣ you can integrate deeply into actual business systems.

PolyAI doesn't just talk; it pulls data from your CRM, checks availability in your booking system, processes payments through your payment gateway, updates your PMS, triggers workflows, and a lot more.

3️⃣ you can measure what actually matters to businesses.

We don't track "user engagement" or "daily active users".

We track containment rate, revenue per call, cost per contact, CSAT scores, after-hours bookings captured.

The Melting Pot generated $250K in six months from calls that would've gone to voicemail.

4️⃣ and this is the part that took me years to understand:

You can actually be held accountable.

When your AI is handling a business's main phone line, every failure is visible immediately.

A hallucination doesn't just annoy a user, it costs the business a customer.

So you build differently.

You build with guardrails, with fallbacks, with human handoff protocols, and with real-time monitoring.

You build like the business depends on it, because it does.

PolyAI Agent Studio will help every business have a customer service AI that works 24/7 and actually gets things done.

Excited to have it deployed across your business.

[capx unicorn @CapxUnicorn]

7 is a special number

7 colors of the rainbow
7 days of the week
7 continents
7 notes in the musical scale

And wait for it…
7 AI apps live on Capx Super App

[Node Smith @NodeSmith_]

@CapxUnicorn @cookwithcandy @heykitchy @Project0AI @TryBiteAI @Fizzy_AI @0xCapx The holy 7

[Node Smith @NodeSmith_]

Best coding model is dropping soon:

[tyagi / capx.ai @vb_tyagi]

if we strip away marketing and look at the market honestly

most “competitors” in the ai agent space fall into two camps:

1.
launchpad-only platforms and

2. framework-only platforms

@0xcapx is neither

it is built as a full-stack platform

because the lifecycle of an ai app doesn’t end at minting a token or publishing a repo

[kane @kAInnotkane]

https://t.co/QMk8UrJRjf

[Capx AI @0xCapx]

Game On 🕹️

[Capx AI @0xCapx]

🪂 CAPX Airdrop Unlock 2.0

The 2nd unlock (40%) of the Capx Airdrop is now LIVE

Who all are eligible 🤝

• Capx App Users
• AIRAA Campaign Participants
• Symbiotic Operators & Stakers

Go claim👇
https://t.co/WYP5yZ1zUQ

[Node Smith @NodeSmith_]

@dextrrr @kAInnotkane Appreciate the long term mindset here

[Dexter @dextrrr]

Over the past few weeks, I’ve been thinking a lot about our presale unlocks and what they mean for the future of the project.

Then I saw @kAInnotkane push CIP-001 for Candy, settling early, reducing unlock pressure, and redirecting tokens into a growth pool.

It gave me clarity.
It confirmed I was already thinking in the same direction.

So, today I’m putting an important decision in front of the community with CIP-002.

The idea is simple: settle the presale early, give participants some liquidity now, and move the rest into a long-term Growth Rewards Pool to fund creators, integrations, and user acquisition.

Because big unlock cliffs change behavior.
Buyers wait. Holders worry. Momentum slows.

I don’t want us managing charts, I want us building.

If this passes, we get years of runway to focus on shipping and helping users win.

If you’re eligible, I’d really appreciate your vote.

[zed @0xPZed]

. @Project0AI is here to build for the long term and this proposal makes that possible

seeing @kAInnotkane couple weeks ago was a eureka moment for me!! kudos man

anyway, back to building and shipping. if you are eligible please do vote 🗳