Frido van Driem

Founder | Helping journalists create interactive, engaging timeline stories for their articles.

[Frido van Driem @FridovanDriem]

🚀 New feature alert! Timepath now auto-generates interactive timelines based on the content of your article link. Simplify your storytelling and engage your readers effortlessly. Check it out 👉 https://t.co/48a6M39vIo 🙌 #timelinemaker #journalism #nocode

[Frido van Driem @FridovanDriem]

Solana's Most Wanted.

Just got muppified for this week's Solana Ecosystem Call.

Charge: performing tvl while uninsured.

It's time to https://t.co/wpNSp8ah4e!

[Himanshu Kumar @codewithimanshu]

Andrej Karpathy just sat down and built GPT from scratch, line by line, in 2 hours.

For Free. From the man who co-founded OpenAI.

This video is enough to become an AI engineer.

Bookmark it. Watch it tonight. Build your own GPT this week.

$5,000. $15,000. $40,000.

That's what bootcamps charge to teach less than what's in this 2-hour video.

This video fixes that this week.

Follow @codewithimanshu for more high-signal AI content that actually moves your engineering career forward.

↓

Karpathy doesn't explain GPT. He builds it.

Live. From "Attention is All You Need" the original paper. To the same architecture powering GPT-5.

Founding member of OpenAI in 2015. Senior Director of AI at Tesla. Now running Eureka Labs.

He's not teaching you how to use GPT. He's teaching you how it actually works at the source code level.

Most engineers will never understand transformers this deeply. The ones who do build the next generation of AI products.

Follow @codewithimanshu for breakdowns of every must-watch AI lecture worth your time.

↓

Here's what gets built in 2 hours. No fluff.

Tokenization and data loading.

The foundation of every modern LLM. Train/val splits done right. Batch loaders that don't break in production.

Most tutorials skip this. You can't ship anything serious without it.

The bigram baseline.

The simplest possible language model. Karpathy builds it first because it teaches you what every fancier model is actually trying to improve.

Once you understand bigrams, transformers become obvious. Skip this and the rest never clicks.

Follow @codewithimanshu for daily breakdowns of what AI engineers actually need to know.

↓

Self-attention. From scratch. Live.

This is the section that should have its own course.

Karpathy builds self-attention in 4 versions:

> Version 1: averaging past context with for loops
> Version 2: matrix multiply as weighted aggregation
> Version 3: adding softmax
> Version 4: full self-attention

Each version teaches you why the next one exists. Why attention works. Why matrix math replaces explicit loops. Why scaling matters.

You'll never look at "attention is all you need" the same way again.

Follow @codewithimanshu for production transformer breakdowns weekly.

↓

The 6 attention notes that change everything.

Karpathy drops 6 insights most engineers never hear:

> Attention as communication between tokens
> Attention has no notion of space, operates over sets
> No communication across batch dimension
> Encoder blocks vs decoder blocks
> Attention vs self-attention vs cross-attention
> Why we divide by sqrt(head_size)

Each one of these explains a different failure mode in production AI systems.

Most "AI engineers" can't answer these. The ones who can charge $300K.

Follow @codewithimanshu for the engineering insights that turn into job offers.

↓

Building the full transformer block.

Single self-attention head. Then multi-headed self-attention.

Feedforward layers. Residual connections. LayerNorm.

Each piece added with the reason it exists. Why residuals stop the model from collapsing. Why LayerNorm replaced BatchNorm. Why dropout matters at scale.

This is the architectural understanding that lets you debug any modern AI system.

Once you've built one transformer by hand, every paper you read becomes 10x clearer.

Follow @codewithimanshu for transformer architecture content every week.

↓

Scaling up to a real model.

Karpathy goes from baseline to a working GPT.

Hyperparameters. Dropout. Model dimensions. The exact tradeoffs every production model makes.

By the end you have a Shakespeare-generating language model running on your machine. From scratch. Built by you. Understood by you.

That's not a tutorial. That's an architectural unlock.

Follow @codewithimanshu for production model scaling breakdowns.

↓

Encoder vs decoder vs both.

The architecture choice that defines every modern AI product.

Why GPT is decoder-only. Why BERT is encoder-only. Why translation models use both.

Once you understand this, you can read any AI paper and immediately know what kind of system you're looking at.

This is the difference between someone who follows AI hype and someone who builds it.

Follow @codewithimanshu for AI architecture deep dives weekly.

↓

NanoGPT walkthrough.

Karpathy ends with a quick walk through nanoGPT. The repo every serious AI engineer has cloned at least once.

Batched multi-headed self-attention. Production-grade code. The clean version of everything you just built.

This is the bridge from "I built a toy GPT" to "I can read and modify production AI code."

Follow @codewithimanshu for repos every AI engineer should know.

↓

ChatGPT, pretraining, finetuning, RLHF.

The video closes with the full lineage. From your toy GPT to ChatGPT.

What changes when you scale up. Why RLHF matters. The exact path from research model to product.

You finish the video understanding the entire stack from raw paper to deployed product.

Most "AI experts" can't draw this map. After 2 hours, you can.

↓

What you'll be able to do after this.

Read "Attention is All You Need" and understand every line.
Debug attention layers when they break in production.
Build a custom language model on your own dataset.
Modify transformer architectures for specific use cases.
Have technical conversations with AI engineers without faking it.
Train a GPT on any data you want. Shakespeare. Code. Your own writing.

That's not "AI literacy." That's the foundation of an AI engineering career.

The kind of foundation that turns into senior roles and consulting contracts most people will never access.

↓

2 hours. Free. From the engineer who built it.

You'll spend longer in meetings this week and learn nothing.

This compounds for the rest of your career.

People who watch it can build GPT from scratch by Friday.
People who skip it stay confused about why their prompts fail in production.

Save the video. Watch it this week. Build something with the knowledge by the weekend.

Follow @codewithimanshu for more high-signal AI content from the people actually building the future.

[Charly Wargnier @DataChaz]

🚨 This is absolute GOLD.

The @AnthropicAI engineer who literally wrote "Building Effective Agents" just dropped a 14-minute masterclass.

saves you months of headaches trying to figure this out alone.

bookmark for the weekend + read @Av1dlive's great guide below 👇

[Frido van Driem @FridovanDriem]

Homework

[shadcn @shadcn]

Meet Sera. A new foundational style for shadcn/ui.
Minimal. Editorial. Typographic.
Shaped by Print Design Principles.

Available Today. Try on shadcn/create.

[Sumvin @sumvin]

Big news in agentic commerce — and we're part of it 🙌

Today, @Visa announced Intelligent Commerce Connect: a network-agnostic on-ramp that enables AI agents to initiate payments securely across major card networks and protocols.

Sumvin is named as one of Visa's pilot partners.

Here's why this matters 👇

We're building the permission layer for agent-driven finance — the infrastructure that lets AI systems act on a user's behalf within explicit, controlled boundaries.

Visa's Intelligent Commerce Connect solves the other side of that equation: once an agent is authorised to act, how does it actually pay?

The answer: a single integration across Visa, other major networks, and protocols including Trusted Agent Protocol, Machine Payments Protocol, and more — with no lock-in on token vaults.

This is infrastructure that makes agentic commerce real. Not a demo. Not a concept. A live, scalable on-ramp — and we're building on it.

Finance is moving from dashboards and apps toward systems that act on user intent. This is what that shift looks like in practice.

Read the full announcement here 👇 https://t.co/bchahQUVUJ

[Frido van Driem @FridovanDriem]

@timneutkens first of all great job on the latest nextjs. I do have question, after upgrading to 16.2 I notice that in development after making changes to my code i need to remove the .next folder, run yarn dev in order to see the changes. Do other users experience the same?

[Frido van Driem @FridovanDriem]

“You can’t always code what you want…. But if you try Claude max…. You get what you need” 🎶

[Frido van Driem @FridovanDriem]

Most AI in newsrooms is a black box: input → output → hope it fits editorial standards.

Timepath AI changes that.
YOU pick prompt & model. Full transparency across timelines, liveblogs, polls, quizzes & more.

Human stays in control. Journalists win.

#journalism #AI

[Tanaka @Tanaka_L2]

➥ How I’m Thinking About SEI Over the Next 24 Months

I’m convinced @SeiNetwork is one of the most misunderstood L1s heading into 2026-2027.

From my POV, Sei is building for where crypto is actually going: fast execution, compliant rails, RWAs, and institutions that care about reliability more than vibes.
Bullish Catalysts in the Next 12 Months I believe most of you wont wanna miss:

→ I've prioritized items with high probability and impact, assuming no major black swans.

⓵ Sei Giga Upgrade Rollout:

– The Giga upgrade, already testing at 211K TPS on devnet with Autobahn consensus for sub-second finality, is poised for mainnet deployment in early 2026.

– This would make Sei the fastest EVM-compatible chain, enabling high-frequency apps like perps DEXes, prediction markets, and onchain stocks trading via @monacotrading.

– Expect a surge in developer activity and TVL, as it addresses bottlenecks in #DeFi and gaming, potentially boosting $SEI demand through higher transaction fees and staking.

⓶ ETF and ETP Approvals/Launches:

– Multiple filings are in play, including the Staked SEI ETF on DTCC/IBKR, CoinShares SEI ETP (already live in Europe), and S-1/N-1A submissions from Canary Capital, 21Shares, REX Shares, and Osprey Funds.

– Regulatory tailwinds could lead to U.S. approvals by mid-2026, unlocking institutional inflows similar to BTC/ETH ETFs.

– This validates Sei's compliance focus and could drive $SEI price through broader accessibility on platforms like Robinhood.

⓷ Asia-Pacific Expansion and Mass Onboarding:

– Sei's Asia push is accelerating, with Xiaomi integrating $SEI wallets into 170M+ devices annually, listings on Binance Japan/OKX Japan, and OSL HK providing regulated custody.

– Korea's Upbit already shows top-3 trading volume for $SEI.

– By Q2 2026, this could onboard millions via mobile-first access, fueling retail adoption in high-turnover markets.

– Combined with hackathons and eco funds, it positions Sei for explosive user growth, especially in gaming and trading.

⓸ RWA and Institutional Inflows Scaling:

– Partnerships with BlackRock, Hamilton Lane, and Apollo (via KAIO, with $30M+ in 2 months) are live, alongside Securitize for tokenization and Ondo for yield-bearing treasuries.

– The recent Market Infrastructure Grid launch enables macro-aware RWAs, like GDP-linked products and real-time risk models using Chainlink feeds.

– Expect $100M+ in new RWA inflows by mid-2026, as institutions like State Street (backing AUSD0) and Cryptocom (custody) deepen integration, driving $SEI utility in compliant finance.

⓹ Stablecoin and Payment Ecosystem Growth:

– Native USDC minting hit $100M+ in 10 days, with PYUSD (via LayerZero/PayPal) and AUSD0 expanding.

– Integrations like Circle CCTP v2, Coinbase x402 for agentic payments, and MetaMask native swaps/bridges streamline flows.

– This could push stablecoin supply past $500M and DEX volume to $2B+/month by late 2026, as Sei becomes a hub for seamless, low-cost transfers, boosting $SEI through fees and liquidity.

⓺ Gaming and AI-Driven App Surge:

– With 116M gaming txns in Q3 2025, launches like MetaArena and Seimurai are gaining traction.

– AI integrations via Allora (forecasting) and Kindred (agentic layer) add onchain IP narratives.

– Post-Giga, expect 50x throughput to attract more games and devs, potentially hitting 1B+ txns lifetime and 1M+ DAAs, catalyzing $SEI via ecosystem grants and user retention.

⓻ Broader Ecosystem Metrics and Listings:

– Q3 2025 saw 93.5% DAA growth to 824K, $43M DEX volume (75% QoQ), and $1.5B/month flows.

– New listings and indexes enhance visibility.

– If trends hold, 2026 could see 10M+ wallets and $50B+ perp volume, with policy contributions solidifying Sei's blue-chip status.

I’m bullish because Sei is shipping, integrating, and onboarding where it actually matters.

Markets move faster on Sei ($/acc).

[jhey ʕ•ᴥ•ʔ @jh3yy]

you can stack elements with css grid/subgrid by giving them the same grid position 🧑‍🍳

this scroll track window is a great use case for css grid + position: sticky

catch the 3D breakdown 👇

[Pontus Abrahamsson @pontusab]

This is how I'm solving wide tables in midday:

- Horizontal scrollable
- Visible pagination if too wide
- Keyboard navigation

[Frido van Driem @FridovanDriem]

Trust the technology of SEI, team and the vision of @jayendra_jog @phillip_xyz but above all never waste a good crisis. Markets move faster on $sei

[Frido van Driem @FridovanDriem]

@CryptoMichNL Agree. SEI will become the L1 optimized for trading with subsecond finality, parallel execution and native ordermatching. With ecosystem metrics improving, TVL surging and user adoption rising I believe SEI is way undervalued relative to its potential. Same like SOL at $8

[jhey ʕ•ᴥ•ʔ @jh3yy]

responsive CSS pinned sidebar transition 📌

.layout:has(:popover-open) {
grid-template-columns: var(--sidebar-width) 1fr;
}
aside:popover-open {
translate: 0 var(--ctrl);
height: var(--extend);
}

actual zero JS for the layout transition here
so many details to play with! 🧑‍🍳

[Jay @jayendra_jog]

👀 👀 👀

[Frido van Driem @FridovanDriem]

@rauchg @vercel Nice! Would be an honor Guillermo if you create a Timeline about your journey at Vercel with https://t.co/HYSinTfTcb and embed it on Vercel. Timepath is build with nextjs and hosted on Vercel :) Circle complete!

[21shares US @21shares_us]

We're excited to announce that we've filed with the SEC for a SEI ETF in the U.S. - a key milestone in our vision to expand exchange-traded access to @Seinetwork.

[Frido van Driem @FridovanDriem]

On so it begins, Timepath dApp incoming for @solanamobile

[Frido van Driem @FridovanDriem]

@asidorenko_ Legend 🦸‍♂️✌️! Many thanks Alex 🤗 I will work on this and deploy on https://t.co/HYSinTfTcb Keep you posted!