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It takes me 2 hours. I am not joking. Usually, I don't have it "planned" before I started to...

Meme Monday! Today's cover image comes from the last thread. DEV is an inclusive space! Humor in...

When I first started learning HTML, I thought it would be the easiest part of web development. The basic tags seemed straightforward, and creating a simple page didn't take long. But as I kept learning, I realized that HTML is more than just putting elements on a page. Understanding semantic HTML , proper document structure, forms, accessibility, and knowing which element to use in different situations takes practice. For example, it can be tempting to use for almost everything, but learning when to use elements like <section>, <article> , <nav> , or <header> makes a big difference in writing meaningful markup. I'm curious about other developers' experiences: What HTML concept confused you the most when you were starting out, and what helped it finally click? I'd love to hear different perspectives, especially from people who have been working with HTML for a while.

The Battery-Free Smart Card Revolution: A Hands-On Review of NFC Energy-Harvesting MCU PCBs In professional networking, first impressions are everything. But in a landscape crowded with QR codes and cheap plastic tap-to-share cards, how does a high-tier developer, cybersecurity expert, or tech founder stand out? Enter the NFC Energy-Harvesting MCU PCB Business Card . It’s not just a card; it's a fully functional, battery-free embedded system packed inside a 1.6mm-thick piece of FR-4 fiberglass. In this review, we’ll dive deep into the tech behind passive RF power harvesting, explore the hardware stack making this possible, and evaluate whether building (or selling) these high-tech novelties is worth your time. What is an NFC Energy-Harvesting MCU PCB? At its core, this device is a printed circuit board (PCB) styled to the dimensions of a standard business card. However, unlike passive NFC tags that simply store a URL, this card integrates an onboard Microcontroller Unit (MCU)—such as the ultra-cheap WCH CH552 or Microchip ATTiny85 —and an array of LEDs or an e-paper display. The real engineering marvel? It has no battery. +-------------------------------------------------------------+ | [ NFC Coil Antenna ] -> (Harvests 13.56 MHz RF Field) | | | | | v | | [ Schottky Rectifier Bridge ] | | | | | v | | [ Voltage Regulator ] | | | | | v | | [ Ultra-Low Power MCU ] | | / \ | | v v | | [ Status LEDs ] [ Dynamic NFC payload ] | +-------------------------------------------------------------+ When tapped against an NFC-enabled smartphone, the phone's transmitter emits a magnetic field at 13.56 MHz . The trace antenna etched directly into the outer edges of the PCB acts as an inductor, harvesting this RF energy and converting it into AC electricity. This current is rectified to DC, regulated to a stable 3.3V, and powers up the MCU to execute its onboard program instantly. The Tech Stack: Under the Hood To truly appreciate these cards, we have to look at the components that m

If you’ve ever tried to open an Apple Health export.xml file in VS Code, you’ve probably watched your RAM melt into a puddle of sadness. 🫠 Apple’s HealthKit data is a treasure trove of biological insights, but at the scale of 5GB+ of "dirty" XML, it’s a Data Engineering nightmare. In this tutorial, we are building a high-concurrency Apple Health ETL Engine . We’ll be leveraging Rust for blazing-fast parsing, Apache Arrow for memory-efficient data transport, and ClickHouse for lightning-fast analytical queries. Whether you are building a personal bio-hacking dashboard or a population health platform, this architecture is designed to handle "Big Data" on "Small Hardware." The Problem: Why XML is Killing Your Pipeline Apple Health exports everything as a single, massive XML file. A typical 3-year history contains millions of <Record> tags with inconsistent attributes. Standard DOM parsers (like Python’s ElementTree ) will crash your system because they try to load the entire tree into memory. To solve this, we need a Streaming ETL approach. The Architecture 🏗️ Our pipeline follows a "Performance-First" philosophy: we parse in a low-level language, pass data through a zero-copy memory format, and sink it into a columnar database. graph TD A[Apple Health export.xml] -->|Streaming I/O| B(Rust XML Parser) B -->|Schema Mapping| C{Apache Arrow Batches} C -->|Zero-copy| D[Python/Polars Wrapper] D -->|Bulk Insert| E[(ClickHouse OLAP)] E -->|SQL/Grafana| F[Health Insights] style B fill:#f96,stroke:#333,stroke-width:2px style E fill:#00f,stroke:#fff,stroke-width:2px Prerequisites 🛠️ Before we dive in, ensure you have the following installed: Rust (Latest stable) Python 3.10+ ClickHouse (Local or Cloud) Tech Stack : quick-xml , arrow-rs , polars , clickhouse-connect . Step 1: The High-Speed Rust Parser 🦀 We use the quick-xml crate because it provides a "pull-based" API. This allows us to read the file byte-by-byte without ever loading more than a few KB into memory. // src/parser

I recently dug out my CDs and started reripping them all. I've found a few forgotten gems in there, but few hit harder for me than the beautifully concise Professor Murder Rides the Subway EP. There was a period of time in the mid-aughts in NYC where it seemed like every indie band wanted you […]

Searches for it fell 71% this year. Here’s what people are searching for instead. Every list of dying businesses says the same thing. AI is coming for the boring work. Bookkeepers, translators, copywriters, support reps. Learn to prompt or get replaced. I run a database that pulls business ideas from Reddit complaints and App Store reviews, then checks real search-volume data behind each one. 1,416 scored threads. 192 published ideas. 941 companies with revenue verified straight from Stripe. When I sorted those 192 ideas by year-over-year search growth, the bottom of the list was not what I expected. At a glance Searches for “ai writing tool” fell 71% year over year. “ai agent” fell 46%. “ai detector” fell 19%. Meanwhile “fleet management software” rose 50%, “route planner” rose 50%, and “invoice reminder software for contractors” rose 45%. Of 941 Stripe-verified companies, the 37 in Services average $22,457 MRR. The 129 mobile apps average $4,387. The dying category is not boring work. It is the tool layer built on top of a model anyone can call. Demand did not disappear. It moved to the industries nobody wants to write a Medium post about. Where these numbers come from Search volume and year-over-year growth come from DataForSEO, the same keyword source most SEO tools resell. Revenue comes from TrustMRR, which reads a company’s actual Stripe account rather than asking the founder what they make. That second part matters for this piece. Most “here is what’s growing” articles quote founders. Founders round up. Stripe does not. The categories that are shrinking Keyword: cloud storage Monthly searches: 60,500 Year over year: -99% Keyword: tax preparation software Monthly searches: 6,600 Year over year: -75% Keyword: ai writing tool Monthly searches: 8,100 Year over year: -71% Keyword: church management software Monthly searches: 4,400 Year over year: -57% Keyword: ai agent Monthly searches: 18,100 Year over year: -46% Keyword: 3d printing software Monthly searches: 9,

The Liux Big microcar is made in Spain. The startup thinks it can compete in a crowded market with its tiny electric car built around sustainability.

When a new cryptographic algorithm appears, a tension shows up: classical algorithms such as X25519 or Ed25519 have resisted attacks for years, but are vulnerable to a future quantum computer; post-quantum ones such as ML-KEM or ML-DSA resist quantum attacks, but are newer and less tested. Hybrid encryption resolves the tension: use both at once . The idea in one sentence Combine a classical and a post-quantum algorithm so that the system only breaks if both fail simultaneously . A classical attacker would have to break the post-quantum algorithm; a quantum attacker would have to break the classical one and the post-quantum one. You gain security against the future without betting everything on a young algorithm. Two places to apply it Key exchange (encrypting for a recipient). You combine: X25519 — classical key exchange, fast and heavily tested. ML-KEM-1024 — NIST's post-quantum key encapsulation mechanism, at its highest level. The two resulting keys are mixed with a context-bound derivation function (HKDF), so that neither one alone is enough. Digital signatures (authenticity). You combine: Ed25519 — classical signature. ML-DSA-87 — NIST post-quantum signature. The message is accepted only if both signatures verify — an AND combiner. One principle that never breaks There is a golden rule in cryptography, Kerckhoffs's principle : a system must be secure even if the attacker knows its entire design; security lives in the key , not in hiding the format. A good hybrid system uses public, audited primitives — XChaCha20-Poly1305 to encrypt, Argon2id to derive keys from passwords, HKDF to separate domains — and never invents its own cryptography . How Quipu applies it Quipu is a free library implementing exactly this approach for data at rest : hybrid X25519 + ML-KEM-1024 encryption, hybrid Ed25519 + ML-DSA-87 signatures, and only verified primitives underneath. It targets NIST security level 5 (CNSA 2.0) and is open source, so anyone can review how it works. An honest

After Donald Trump’s executive order demanding the name change, Google is the first major online maps provider to flip the switch.

Originally published on xroot.dev . On-chain, a regulated fund token and a honeypot scam are the same shape. Both are Token-2022 mints. Both keep an active freeze authority. Both set DefaultAccountState to Frozen , so every new holder's account starts locked. One of them is a European money-market fund following its regulator's rules; the other is a trap built to let you buy and never sell. Every token scanner I tested reads them identically: red flags, high risk, score zero. The reason this now matters is sRFC-37, the Token ACL standard — the Solana Foundation's official mechanism for permissioned tokens. It has been live on mainnet since March 2026, real institutional money already uses it, and the entire real-world-asset wave forming on Solana is going to ship in this exact shape. This post covers how it works end to end — and the structural check that separates a compliant token from a trap, verified against the chain rather than anyone's metadata. Why Permissioned Tokens Exist at All A tokenized treasury fund, a regulated stablecoin, a security token — their issuers are not allowed to let anyone hold them. KYC requirements, sanctions screening, court orders, investor-accreditation rules: the issuer must be able to control who holds the asset and stop specific wallets, or the asset cannot legally exist on a public chain. Solana had two ways to build that before, and both hurt: Transfer hooks run issuer code on every transfer — but every DEX, wallet and protocol touching the token must implement the hook interface, so composability dies at exactly the venues that create liquidity. Manual freeze-and-thaw keeps standard transfers — but every new holder starts frozen and waits for the issuer to co-sign a thaw. Onboarding becomes a support ticket, and the issuer signs forever. Token ACL is the third path: keep the freeze mechanism — the one lever the token program already enforces everywhere — but make thawing self-service against a published rulebook. The Mechanics:

GitHub热门项目 | A syntax-highlighting pager for git, diff, grep, rg --json, and blame output | Stars: 31,997 | 64 stars today | 语言: Rust

GitHub热门项目 | Apache Iggy: Hyper-Efficient Message Streaming at Laser Speed | Stars: 4,608 | 16 stars today | 语言: Rust

GitHub热门项目 | Open Source Spotify client library | Stars: 6,993 | 7 stars today | 语言: Rust

Every value in my little embedded key-value store gets encrypted, then its ciphertext gets encoded as a string of A/C/G/T characters before it ever touches the filesystem. Open the file in a text editor and you'll see actual DNA-looking text - not because it's a gimmick, but because that's genuinely the storage format. This is mdc-lite , a ~348KB embeddable encrypted key-value store I built in Rust for places a server can't reach - a watch face, a phone app, a background service. It's part of a larger repo, ModelDB , that also includes MDC, a Python conversational data engine (query AI models, databases, images, and documents in plain English, no SQL) with its own DNA-inspired archival storage tier. The actual storage format Every put() call does this, in order: Pack [key_len][key_bytes][value_bytes] into one plaintext buffer. Encrypt the whole thing with XChaCha20-Poly1305 (a 256-bit key you supply - the crate never generates or stores key material itself; real key custody belongs to the platform's secure hardware, iOS Secure Enclave or Android Keystore). DNA-encode the resulting [nonce][ciphertext][tag] blob: 2 bits per base, 00→A 01→C 10→G 11→T . Every byte maps to exactly 4 bases, so there's no padding ambiguity on decode. Write the ACGT text to disk, atomically (temp file + rename). Filenames are keyed BLAKE3 hashes of the logical key, not the key name itself, so a directory listing alone leaks nothing - no key names, no values, no way to tell how many distinct keys exist versus how many files are on disk. rust pub fn put(&self, key: &str, value: &[u8]) -> Result<(), LiteStoreError> { let mut plaintext = Vec::new(); plaintext.extend_from_slice(&(key.len() as u16).to_le_bytes()); plaintext.extend_from_slice(key.as_bytes()); plaintext.extend_from_slice(value); let nonce = XChaCha20Poly1305::generate_nonce(&mut OsRng); let ciphertext = self.cipher().encrypt(&nonce, plaintext.as_ref())?; let mut record = nonce.to_vec(); record.extend_from_slice(&ciphertext); let ac

After sixty-seven published posts here, the comments have become one of the best parts of the work....

The next DEV Weekend Challenge launches next week, and we have some ideas up our sleeves, but we...

An agent that changes something runs in the order decide, act, report. Verification, where there is any, reads what already happened. That's a fine shape for a log. As a control it's empty: by the time the check fails, the effect is already on disk, and what's left is describing the damage, attempting a repair nobody verified, or restoring from a backup whose age nobody measured. For the last few months I've been building the other order, not for one tool but for the whole path a change takes. A proposed change gets a canonical identity. Its inverse is constructed, checked, and stored before anything is applied. A gate rules on it and returns one of three verdicts. The outcome, refusals included, becomes a signed record that a third party can re-check offline with no trust in me. There's a longer draft paper behind this, deposited at doi.org/10.5281/zenodo.22168558 . It's a draft, not peer reviewed, and not a specification. This post is the part that fits in a coffee break. What I'd have to be wrong about Putting this first, because a claim that only becomes checkable after you already agree with it isn't checkable. Inverse availability. The escrow design assumes a useful fraction of write-capable tools expose something you can build an inverse from. A first census of public MCP tools put that at about 13.8% of the tools that write anything at all (census v2 stage 1, public MCP servers only, not production deployments). If the real number in production is at or under that, this is mostly a refusal machine, and "reversibility as a property" degrades into "refusal as a property", which is a much smaller and much less interesting thing to have built. That's the most dangerous fact in the project and it's mine, not a critic's. Offline re-verification. If a signed receipt can't be re-checked with networking off and no trust in the issuer, meaning signature, log inclusion and identifier consistency, then the provenance layer is a log and not a proof. This one is runnable

Punish the branch. Deliver the message to the tree. — The 36 Stratagems, Point at the mulberry tree...

Hey 👋 Quick backstory — my last post on getting paid after winning a DEV Challenge did way better...