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Web-Accessibility
Web Accessibility for Startups: 5 Small Wins That Scale Palak jain Palak jain Palak jain Follow Oct 7 '25 Web Accessibility for Startups: 5 Small Wins That Scale # webaccessibility # webdev # frontend # startup 21 reactions 4 comments 4 min read
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100 Days of DevOps and Cloud (AWS), Day 14: Restoring a Broken httpd, and the One EC2 Command With No Undo
Some commands you can walk back. Terminating an EC2 instance is not one of them. Day 14 paired a recoverable problem, a web server knocked over by a rogue process, with an unrecoverable one, deleting a server on purpose, and the contrast is the whole lesson. One Linux task, one AWS task. Track down the process blocking Apache and restore the service, then terminate an EC2 instance and confirm it is gone. The tasks come from the KodeKloud Engineer platform. httpd: diagnose in order, then restore When httpd will not start, resist the urge to guess. Work in order. Start with what the service itself reports: # What does httpd think is wrong systemctl status httpd systemctl start httpd The status output usually names the problem, and a failed bind on the port is the classic one. Before assuming a rogue process, check that httpd's own config is sane, because a wrong port or hostname produces the same "won't start" symptom: # Check the configured listen port and server name grep -i listen /etc/httpd/conf/httpd.conf vi /etc/httpd/conf/httpd.conf # Fix the ServerName directive if it is wrong: ServerName hostname:<port> If the config is fine and the port is genuinely taken, then you go hunting for the process holding it: # Find the PID on the conflicting port sudo su - yum install -y net-tools netstat -tulpn # Clear it, then bring httpd back kill -9 <PID> systemctl enable httpd systemctl start httpd systemctl status httpd kill -9 is SIGKILL, the instant, no-cleanup kill. It is the right tool when a process is wedged and ignoring a polite request, but as a default habit, it is worth trying a plain kill first. The order that matters here is diagnostic: config before process, gentle signal before forceful one. Rushing to kill -9 at the first sign of trouble is how you mask the real cause instead of fixing it. Terminating EC2: the command with no undo Day 9 was about protecting an instance from termination. Day 14 is the other side of that lever, actually terminating one, on purp
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How Netflix Built GenPage: a Single GenAI Model to Build Personalized Homepages
GenPage is a generative AI system developed by Netflix to replace its traditional multi-stage recommendation pipeline by directly generating personalized user homepages. GenPage leverages user history and request context as a prompt to produce the entire page, resulting in improved user engagement and reduced serving latency. By Sergio De Simone
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Can an Apple lawsuit derail OpenAI’s hardware plans?
On the latest episode of Equity, we debate whether Apple's lawsuit will cast over OpenAi's much-discussed plans to get into hardware and go public.
科技前沿
NASA shares beautiful timelapse of the Psyche spacecraft's view over Mars
The spacecraft made a close approach to the red planet in May on its way to explore the asteroid it's named after.
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How We Distribute Video Events Across Regions With NATS JetStream
When a new video shows up in one of our regional crawlers, three things need to happen almost immediately: the SQLite FTS5 search index for that region needs a new row, the discovery ranking cache needs to be invalidated, and the sitemap generator needs to know a URL was born. For a long time we did all of this inline, inside the same cron process that fetched the video. It worked until it didn't. A slow FTS5 rebuild would stall the fetch loop, a sitemap write would fail silently, and a crash halfway through meant one region had the video indexed and another didn't. The fetch and the fan-out were fused together, and every failure was a partial failure. The fix was to stop treating "a video was discovered" as a function call and start treating it as an event. At TrendVidStream we run discovery across 8 regions, and the moment we introduced NATS JetStream as the spine between the crawler and the downstream consumers, the whole system got calmer. This post is the concrete version of how we did it: the stream config, the publishers, the consumers, and the mistakes we made that you can skip. Why Not Just Use a Queue Table in SQLite We already had SQLite everywhere, so the obvious move was a jobs table. We tried it. The problems showed up fast: Polling latency vs. load tradeoff. Poll every second and you hammer the DB with mostly-empty SELECT queries across 8 regions. Poll every 30 seconds and your search index lags noticeably behind your crawler. No fan-out. One row, one worker. If the sitemap generator and the FTS5 indexer both need the same event, you either duplicate rows or invent a consumed_by bitmask. Both are ugly. Locking. SQLite's writer lock means the queue table and the actual data table start contending under the multi-region cron bursts we run. Cross-region delivery. Our regions aren't all on the same box. A queue table doesn't cross machines without you building a replication story on top. JetStream solves all four: push-based delivery (no polling), multipl
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Week 2: I Found the Best Free Blockchain Course on the Internet — Here's My Honest Review
My Zero to Blockchain Engineer journey — Week 2 update Last week I announced I was teaching myself blockchain engineering from zero. This week I went deep into Cyfrin Updraft — and I have to be honest, it changed how I think about learning Web3. Here's everything I covered, what surprised me, and why I think this platform is the best free resource for anyone serious about becoming a blockchain developer. What I covered this week I'm currently 45% through the Blockchain Basics course on Cyfrin Updraft. Here's exactly what the lessons covered: Section 1 — What Is A Blockchain? This section answered the question properly — not in a surface-level way, but by starting with the problem blockchain solves. The lesson on centralized control hit differently. Think about it in a Nigerian context — banks freezing accounts, payment processors blocking transactions, elections where results can't be independently verified. These aren't hypothetical problems. They're things we live with. Blockchain's answer: a shared ledger where truth is verified by math, not by a middleman. That framing made everything click for me. Key lessons I completed: What Is A Blockchain — centralized problems vs decentralized solutions History Of Blockchain — from the double-spend problem to Bitcoin to Ethereum Benefits Of Blockchain — permissionless, immutable, credibly neutral Use Cases — DeFi, cross-border payments, DAOs, digital ownership Many Many Chains — L1s, L2s, Mainnets vs Testnets The Oracle Problem — why smart contracts can't access real-world data alone The Purpose Of Smart Contracts — math-based promises vs trust-based agreements What Is The EVM — Ethereum's computation engine explained simply Benefits Of Smart Contracts — decentralization, immutability, transparency Section 2 — Sending Transactions This is where things got hands-on — and where Cyfrin pulled ahead of every other platform I've tried. Key lessons: What Is A Wallet — your public address as a digital mailbox Setting Up A Wallet
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On-Premise AI Code Review: How We Deployed Claude Locally in an Air-Gapped Environment (Setup Guide)
The security officer said no. Not "maybe with some modifications." Not "let us review the data handling policy." No. Cloud-hosted AI code review was not going to happen in their environment. The codebase contained classified material. The network was air-gapped. No data leaves the building. End of conversation. This was a defence contractor. Their development team was writing code that couldn't touch any external API, any cloud service, any SaaS platform. But they were also writing 200,000+ lines of code per year with a team that was struggling to maintain review quality across twelve engineers, the exact problem that AI code review solves. The challenge: deploy AI code review capability that runs entirely on-premise, in an air-gapped network, with no external connectivity, while meeting the security and compliance requirements of a classified computing environment. This is the guide we wish existed when we started that project. It covers hardware requirements, model selection, inference server setup, CI/CD integration and the security architecture that made it pass the compliance review. Why air-gapped AI code review is different from everything else Most AI code review guides assume cloud connectivity. The model runs on the provider's infrastructure. The code is sent via API. The review comes back. The security question is about data handling policies, encryption in transit and vendor trust. In an air-gapped environment, none of that applies. The model runs on hardware you control. The code never leaves your network. There is no vendor to trust because there is no vendor in the loop. This sounds simpler from a security perspective. In some ways it is. In other ways it's significantly more complex because you're now responsible for the entire stack, model selection, quantisation, inference hardware, deployment, monitoring, updating and maintaining the system that in a cloud deployment is someone else's problem. Hardware requirements The hardware question is the fir
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What Is a Pointer in C? A Beginner's Guide
What Is a Pointer in C? A Beginner's Guide If you're learning C and pointers are the moment things suddenly feel harder, you're not alone. Pointers trip up more beginners than almost any other concept in the language. But the core idea is simpler than it looks once you strip away the confusing syntax: a pointer is just a variable that stores an address instead of a value. A Variable Normally Stores a Value When you write int age = 25; , C sets aside a small chunk of memory, gives it a label called age , and stores the number 25 inside it. Every variable in your program lives somewhere in memory, and every location in memory has an address, similar to a house having a street address. Most of the time you don't think about that address at all. You just use the variable name and C handles the memory bookkeeping behind the scenes. What a Pointer Actually Stores A pointer is a variable, but instead of holding a regular value like a number or character, it holds the memory address of another variable. Here's what that looks like: int age = 25 ; int * agePointer = & age ; The & symbol means "give me the address of," and * when declaring a variable means "this variable is a pointer." So agePointer doesn't contain 25. It contains the address where 25 is stored. If you want to see the value at that address, you dereference the pointer using * again: printf("%d", *agePointer); would print 25, not the address. Why Not Just Use the Variable Directly? This is the question that trips up most beginners, and it's a fair one. If you already have age , why bother with a pointer to it? The real value of pointers shows up in a few common situations: Passing large data to functions. When you pass a variable to a function in C, it normally gets copied. For a single integer that's cheap, but for a large array or struct, copying is wasteful. Passing a pointer instead means the function works with the original data directly, without duplicating it. Modifying a variable inside a function. Nor
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Backbeat Forge
Turn drum audio into a score you can actually edit Discussion | Link
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Does Prisma respect Supabase RLS? No — here's why
Prisma and Drizzle connect as the postgres role and bypass Supabase RLS entirely, so your policies never protect ORM queries. Here's the fix. TL;DR: No. Prisma and Drizzle open their own direct Postgres connection and log in as the postgres role, which owns your tables and carries BYPASSRLS — so Row Level Security is skipped on every ORM query. Point your app's connection at a dedicated, non-owner NOBYPASSRLS role (and keep the auth check in your code), not at postgres . If you built your Supabase project assuming RLS is a safety net on the data itself, adding an ORM quietly punches a hole straight through it. Your policies are still there. They just never run for the ORM's connection. Here's the mechanism, the myth to unlearn, and three fixes in order of how much you should reach for them. Does Prisma respect Supabase RLS? No. RLS is not a global property of the database — Postgres enforces it per role, per statement . A policy only bites for a role that is (a) not the table's owner, (b) has no BYPASSRLS attribute, and (c) is not a superuser. The Supabase JS client satisfies all three because it reaches Postgres through PostgREST, which runs your query as the unprivileged anon or authenticated role. Prisma and Drizzle satisfy none of them: they read DATABASE_URL and open a raw SQL connection as postgres , which owns virtually every table you migrated and holds BYPASSRLS . Either fact alone is enough for Postgres to skip your policies. So the same query that returns one tenant's rows through supabase-js returns every tenant's rows through Prisma. That is not a bug in your policy — it's the connection role. Two doors into the same database There are two completely different paths to your data, and they authenticate as different roles. The supabase-js path (RLS enforced). supabase-js talks HTTP to PostgREST, not to Postgres directly. PostgREST connects as authenticator , validates the request JWT, and does a SET ROLE into anon or authenticated for the statement. Those
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Error Analysis
To learn how to analyze an error, we are going to use the error below as an example: nx run mobile : android ✔ 7 / 7 dependent project tasks succeeded [ 6 read from cache ] Hint : you can run the command with -- verbose to see the full dependent project outputs ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————— > nx run mobile : android > npx expo run : android › Opening emulator Medium_Phone › Building app ... Starting a Gradle Daemon ( subsequent builds will be faster ) Configuration on demand is an incubating feature . > Configure project : [ ExpoRootProject ] Using the following versions : - buildTools : 36.0 . 0 - minSdk : 24 - compileSdk : 36 - targetSdk : 36 - ndk : 27.1 . 12297006 - kotlin : 2.1 . 20 - ksp : 2.1 . 20 - 2.0 . 1 > Configure project : app ℹ️ Applying gradle plugin ' expo-max-sdk-override-plugin ' [ expo - max - sdk - override - plugin ] This plugin will find all permissions declared with `android:maxSdkVersion` . If there exists a declaration with the `android:maxSdkVer sion` annotation and another one without , the plugin will remove the annotation from the final merged manifest . In order to see a log with the changes run a clean build of the app . ℹ️ Applying gradle plugin ' expo-dev-launcher-gradle-plugin ' > Configure project : react - native - firebase_app : react - native - firebase_app package . json found at / home / user / projects / my - app / node_modules / @ react - native - firebase / app / package . json : react - native - firebase_app : firebase . bom using default value : 34.10 . 0 dencies of : app : debugRuntimeClasspath > : react - native - firebas : react - native - firebase_app : play . play - services - auth using default value : 21.5 . 0 : react - native - firebase_app package . json found at / home / user / projects / my - app / node_modules / @ react - native - firebase / app / package . json : react - native - firebase_app : version set from
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Learning Software Engineering in the Era of AI
Learning software engineering in the past was a straight forward process, you learn the programming language, you build projects in your portfolio, apply to companies, get a job and life goes on. Doing that in the current times might be a little bit different, as when applying for jobs, you can see some new requirements other than your programming skills and portfolio project such as Prompt Engineering, Work with Agents, Claude Code, and others. You may ask yourself, what are those? And if I am new to Software Engineering, will that change my learning path? Lets discuss all this below. Software Engineering in the Past For a long time, the path into software engineering was clear. You picked a language, maybe Java, Python, or JavaScript. You spent a few months learning the syntax, then the fundamentals: data structures, algorithms, how a database works, how the web sends and receives data. After that, you built things such as A todo app, weather app, clone of a website you liked. These projects went into a portfolio, usually a GitHub profile and a simple personal site. Then you applied to companies, passed a technical interview, and started your first job, so the skills you needed were stable, if you learned React in 2018, React was still useful in 2021. Tools changed, frameworks came and went, but the core idea stayed the same: you write the code, you understand what you wrote, and you fix it when it breaks. When Did AI Start Becoming Something Required The shift did not happen in one day. It came in steps. The first step was autocomplete , around 2021, tools like GitHub Copilot started suggesting the next line of code while you typed. Most developers saw it as a nice helper, nothing more. It saved you from writing boilerplate, but you were still the one thinking. The second step was chat , when ChatGPT and Claude became popular, developers started using them to explain errors, review code, and write small functions. Still a helper, but a much stronger one. At this
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Dev Tool Pricing Changes — July 2026
This report analyzes pricing shifts across 35 developer tools tracked over a seven-week period from 2026-W19 to 2026-W29. We have identified 37 total pricing changes during this window, providing a clear snapshot of how platform tiers are evolving for engineering teams. GitHub Copilot’s Tier Expansion GitHub Copilot has seen significant activity in its subscription structure over the last two months. On May 25, the platform solidified its existing pricing, maintaining the Free tier at $0, Pro at $10/mo, and Pro+ at $39/mo. By June 15, the service introduced a "Max" tier priced at $100/mo. This was followed on July 12 by the addition of two enterprise-focused options: Business at $19/mo and Enterprise at $39/mo. Cursor’s Rapid Plan Iterations Cursor has undergone a series of rapid adjustments to its tiering model since late May. On May 25, the platform introduced a Free Hobby plan and a $20/mo Pro plan while removing the Individual tier. This structure was short-lived; on June 15, the platform removed both the Hobby and Pro tiers, replacing them with a single $20/mo Individual plan. As of the latest tracking, the current price for the Cursor Pro plan is listed at $20/mo. Netlify and Windsurf Pricing Shifts Infrastructure and IDE-integrated tools are also shifting their cost models. On July 12, Netlify moved its Enterprise tier from a "contact sales" model to a defined starting price of $500/month. Windsurf also saw a notable change on June 15 regarding its Teams offering. The price shifted from a flat $40/user/month to a base of $80/mo plus an additional $40/mo per seat. This follows Windsurf's earlier introduction of a Free ($0/month) tier on May 25. Vercel and Firebase Updates Platform-as-a-Service providers have focused on refining their entry-level and usage-based offerings. On May 25, Vercel added a Free Hobby plan and updated its Pro tier to $20/mo (plus additional usage). During that same week, Firebase added a Spark plan ($0) and a usage-based Blaze plan, whi
开发者
Developing a TUI in Go with Bubble Tea
submitted by /u/der_gopher [link] [留言]
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I hate that I don’t hate this song made with Suno
I would never go so far as to say there's no place for AI in music (I'm a fan of Holly Herndon, after all). But I generally find music made with generative AI to be offensively boring, especially the outputs of Suno. So I'm having a bit of a tough time processing the fact that […]
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transcribe.cpp
submitted by /u/namanyayg [link] [留言]
开源项目
ditto.site
Clone any website into clean code. Free & open source Discussion | Link
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Creed
Your personal context file for every agent. Discussion | Link
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A tutorial on building a merkle tree AIR script in Plonky3
submitted by /u/badcryptobitch [link] [留言]