Turgutalp Tug

Software Engineer | Blockchain, RWA Tokenization & Custody @GarantiBBVA

[Turgutalp Tug @tuglabs]

Fonlar Blockchain’de Olsaydı, Bunlar Yaşanır mıydı?
https://t.co/2F5vGSH4xx @LinkedIn aracılığıyla

[Ash Crypto @AshCrypto]

BREAKING:

🇺🇸 SEC approves Nasdaq rule change to enable tokenized securities trading.

[Turgutalp Tug @tuglabs]

@ZaferAyan Dikkat ironi falan ekleseydin keske

[Turgutalp Tug @tuglabs]

@denizirgin Yazik cidden cok gecmis olsun
Umarim biran once mahkemelere ai bakmaya baslar bundan daha kotu olamaz herhalde

[Turgutalp Tug @tuglabs]

@batuhan_katirci Dogru diyorsun ben senin kadar hakim degilim o kisima 🧐 teknigini cok iyi anladim baya da mantikli tebrikler brocum

[Turgutalp Tug @tuglabs]

@batuhan_katirci Bence bu bir acik degilde bir secim gibi sanki simdi veriyi reencode etse cpu maliyeti compute cost mu storage cost mu mantikli gereksiz reencode etmek
Cdnde olay guvenlik yerine hizliya veriri iletmek haliyle detection ile zaman kaybetmek istemezler guzel acik bulmussun 😂

[Turgutalp Tug @tuglabs]

Tktok re-encoding yapmiyor mu ya ? Bizim gonderdigimiz sekilde mi strore ediyorlar png’yi ilginc
Sen teknik olarak appending data to eof yapiyorsun diye anladim
Tiktok veriyi compress /optimize etse senin chunklar nanay olur ?
+ bunun entropiside farkli olur nasil bi dedection algoritmasi calistirmamislar hayret

[Turgutalp Tug @tuglabs]

Blockchain Node'una Neden "SELECT * FROM Transactions" Diyemezsiniz ? https://t.co/hdV88NqSkC @LinkedIn aracılığıyla

[Turgutalp Tug @tuglabs]

@mdisec Kesinlikle durum bu :)

[Turgutalp Tug @tuglabs]

Btw i get i bugs happen chains split reverts occur 🤷🏻‍♂️ That’s software you publish an incident report (post-mortem) devs review it life goes on
My point is about the process management. For a supposedly decentralized layer handling it this way (panic & authority) is where the real failure lies

[Turgutalp Tug @tuglabs]

Relax, I was referencing Mert’s sarcasm about vibecoding. But honestly, your defense makes it look worse lol….
admitting a 'known bug' hit mainney isn't a flex it’s a massive failure of release hygiene. And if 'the chain didn't literally die' is your standard for success the bar is in hell 😅
Also, calling the FBI for an on-chain tx? Fbi fbiii open the door 😂 That’s a centralized company move, not a decentralized protocol. Pick one

[Turgutalp Tug @tuglabs]

@IOHK_Charles Turning it into a total shitshow

[Turgutalp Tug @tuglabs]

@mert People don’t volunteer for traceable money because it’s better they choose it because it’s easier. Convenience has always beaten privacy. Encrypted money protects freedom traceable money protects institutions. Two different problems % two different incentives

[Turgutalp Tug @tuglabs]

X402 yarının hype konusu…

Web2 altyapısı microservice’ler, API’ler ve AI modelleriyle çağ atladı ama ödeme katmanı hâlâ “kart bilgisi gir, abonelik başlat” ve “payment integration” noktasında takılı.
Bu da özellikle API, AI ve agent kullanım senaryolarında ciddi bir yük haline geliyor.

x402, @coinbase ekosisteminden çıkan ama zincir bağımsız ve açık bir protokol olarak tam bu noktada devreye giriyor:
HTTP’nin yıllardır rafta duran status code’u 402 – Payment Required nihayet gerçek bir kullanım alanı buluyor.
İstediğiniz endpoint’i neredeyse tek satırla pay-per-request mantığıyla ücretli hale getirebiliyorsunuz.
Agent’lar; API’lere, veri setlerine ve compute kaynaklarına kendi başlarına ödeme yapıp erişebiliyor.

USDC ile mikro ödeme modeli sayesinde, içerik ve servisler için abonelik zorunluluğu olmadan gelir yaratılabiliyor.
Protokol tarafında ekstra bir fee yok; tercih ettiğiniz zincirin finality süresi ve transaction ücreti oyunu belirliyor.
Bugün Base, Solana, Polygon ve NEAR gibi ağlar üzerinde büyüyen bir x402 ekosistemi var; yüz binlerce haftalık işlem ve çok sayıda entegrasyonla özellikle agent economy tarafında ciddi bir aday haline gelmiş durumda.

Şahsen önümüzdeki dönemde:
“Bu API ücretli mi?” sorusundan çok,
“Bu endpoint x402 destekli mi?”
sorusunun sorulacağını düşünüyorum.

Akış basitçe nasıl çalışıyor?

Sen API’ne x402 middleware ekliyorsun ve diyorsun ki:
/inference çağrısı = 0.02 USDC, /data-feed = 0.005 USDC
Müşteri / agent ödeme yapmadan çağrı yaparsa:
Sunucu HTTP 402 Payment Required dönüyor,
Response header/body içinde “hangi zincirde, hangi adrese, ne kadar ödeyeceği” bilgisi var.
Agent:
Zincirde ödemeyi yapıyor (ör. Solana’da USDC ile),
Ödeme tx’inin kanıtıyla isteği tekrar yolluyor.
Sen:
Ödemeyi on-chain olarak doğrulayıp cevabı üretiyor ve sonucu dönüyorsun.
Kısacası; kredi kartı + subscription + klasik ödeme entegrasyonu karmaşasını,
HTTP request/response cycle’ına gömülü programatik bir mikro-ödeme rail’i ile değiştiriyor.

İncelemek isteyenler için:
🔗 https://t.co/lvF5B4inOF

#Web3Community #Coinbase #x402
#Coinbase
#PayPerRequest
#USDC
#Web3Payments
#OnchainPayments
#DeFi
#Solana
#Base
#Polygon
#NEAR
#APImonetization
#ServerlessPayments

[Computer @AskPerplexity]

This November, history changes.

An NVIDIA H100 GPU—100 times more powerful than any GPU ever flown in space—launches to orbit.

It will run Google's Gemma—the open-source version of Gemini. In space. For the first time.

First AI training in orbit. First model fine-tuning in space. First high-powered inference beyond Earth.

And the CEO just said: "Within 10 years, almost all new datacenters will be built in space."

This is Starcloud-1. Here's why it matters.

[Christina Qi @christinaqi]

We process 14M messages/sec with sub-100μs latency. When rewriting our feed handler, Rust seemed like the obvious choice - we use it successfully across our stack... We chose C++ instead. Here's why the ownership model created friction for our specific use case: https://t.co/r194eMMnCP

[Jean-Jacques Rousseau @TurkRousseau]

Tam olarak şu:

[DHH @dhh]

I love lazygit so much. Such a nice way to deal with git, partial commits, catching up on history, creating new branches, seeing what's there. Incredible power up for any developer.

[Stanislav Kozlovski @kozlovski]

The way Datadog calculates percentiles at scale is 🔥

Calculating percentiles of large datasets is very expensive. To know the 99th percentile of a stream of values, you need to:
• keep all the values
• sort them
• return the value whose rank matches the percentile (e.g 99th item)

Datadog cannot do this with the many millions of data points that come in every second - the memory and CPU requirements would be enormous. 💀

The solution?

👉 Sketch algorithms

Said simply, sketches are algorithms that trade off a bit of accuracy for massive efficiency gains. Those should provide them with a good-enough probabilistic result while being vastly cheaper and faster to compute.

Unfortunately - they didn't get satisfactory results. The algorithms would produce results that were too inaccurate. ❌

Why?

Many percentile sketches had guarantees in terms of rank error.

A rank-error guarantee of 2% means that the p95 value returned by the sketch is somewhere between the p93-p97 value.

But system latencies exhibit very FAT tails - the difference between the p97 and p99 values can be 2-10x!

So what did the dogs do? 🐶

They invented a new sketch algorithm - DDSketch. 🐾

Instead of rank error, they designed it for RELATIVE error guarantees.

If the p99 is 60s, a 2% error means the sketch would return 58.8-61.2s.

The algorithm is pretty simple:
• They create buckets covering ranges of the desired error rate (+- 2% in this case)
• Each bucket keeps a counter of the amount of data points within that range.
• When processing a latency metric data point, increment the counter of the appropriate bucket.
• To count the desired percentile, you sum up the bucket’s values until you get to the desired percentile. Whatever bucket that percentile is in - that’s your value.

💡 Example

1. We want the 50th percentile. We have 8 total samples, so our 50th percentile is represented by the 4th value.
2. We take 3 from the first bucket and then 1 from the second bucket. We conclude that the 4th value is in the second bucket - b-1.
3. The bucket tells us the latency is between 1021-1061ms.

Our actual 50th percentile was 1033ms. Good enough! 👍

🟪 How well does this work?

To cover the range from 1 millisecond to 1 minute, you only need 275 buckets. With 64-bit counters, that's just ~2kB of memory.

The exponential nature makes it cheap to cover a wide range.

💡 1 nanosecond to 1 day takes just 3 times more buckets 802 buckets at ~6kB.

This is also very easy to parallelize.

You can divide this bucket-building exercise into many parallel lightweight substreams, each building their own set of buckets and latency result. At the end, you merge the results of each. 🔥

The merge operation is a simple sum of the buckets & their counters, which ensures that the accuracy is kept in the same range.

It is a very scalable and performant sketch algorithm.

Kudos to Datadog for inventing it!