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Last weekend I started building SiteGrade — a free instant SEO audit tool that gives any website an A–F letter grade and the top fixes ranked by impact. I just launched it. This post is the build log: the architecture decisions that worked, the ones that didn't, and the gotchas you'd save time knowing about. If you're considering building a similar audit/scanner tool, or just want to see what a 2026 Next.js + Supabase + Stripe stack looks like in practice, this should be useful. Why I built it I got tired of family and friends asking me "how's the SEO on my website?" and not having a good answer to send back. Every existing tool I tried either cost $99+/month (Ahrefs, Semrush) or threw 200 metrics at people who just wanted to know if their site was OK. The wedge I built around: one letter grade, three top fixes, plain English, no signup. The paid tier ($29/mo) re-audits weekly and emails the report so non-technical users can track improvements as their developer makes them. The stack Nothing exotic. Everything is the obvious choice for a 2026 indie SaaS, which is the whole point — boring stack means I spent zero time fighting infrastructure and 100% of my time on the actual audit logic. Next.js 14 App Router — frontend + API routes in one repo Supabase — Postgres + auth + RLS + file storage, EU-hosted for GDPR Stripe — subscriptions + Billing Portal + webhooks Resend — transactional email (audit reports, weekly reports, Supabase auth via Custom SMTP) Vercel — hosting + cron jobs for the weekly re-audit cheerio — HTML parsing for the audit checks Google PageSpeed Insights API — Core Web Vitals + mobile performance Total monthly infrastructure cost at zero traffic: ~$0 (everyone on free tiers). At 100 paying customers it'd still be under $30/mo. The audit logic — what 15 checks look like in code Each audit runs 15 checks and produces a score from 0-100, then maps that to a letter grade (A: 90+, B: 75+, C: 60+, D: 45+, F: below 45). The checks are structured as pure fu

Birgitta Böckeler, Distinguished Engineer at Thoughtworks, returns to discuss the rapid evolution of AI in software delivery. She touches on the evolution from vibe coding, the changing tools landscape and the more autonomous agents that, besides higher velocity, introduce higher risk. By Birgitta Böckeler

The Problem Wasn't Writing It was starting. Sometimes I wanted: A social media caption A motivational quote A writing prompt A meaningful message But my mind would go completely blank. Not because I had nothing to say. Because: Coming up with the right words at the right moment is surprisingly difficult. We've All Done This Open a new tab. Search: "Motivational quotes" "Success quotes" "Life quotes" "Funny quotes" Scroll for 10 minutes. Copy one. Close the tab. Why I Built This Tool So I built something simple: 👉 https://allinonetools.net/quote-generator-tool/ A tool that instantly generates quotes across different categories. Whether you need: Motivation Success Life Leadership Creativity Social media inspiration You can generate quotes in seconds. No signup. No setup. Just: Click → Generate → Use What I Realized People don't always look for quotes because they need content. Often they're looking for: A different perspective. A good quote can do something interesting. It can say in one sentence what takes us paragraphs to explain. The Surprising Part The most popular quotes are rarely complicated. They're simple. Short. Easy to remember. Yet somehow they stick with us for years. Why Quotes Still Matter In a world full of endless content: Attention is limited Time is limited Patience is limited A strong quote delivers an idea instantly. That's powerful. The Problem With Searching Manually Most quote websites feel: Cluttered Slow Full of ads Hard to browse And sometimes you spend more time searching than actually reading. What I Focused On I wanted the experience to feel: Fast Clean Inspiring Fun to explore Because finding inspiration shouldn't require effort. What Surprised Me After building it: Some people used it for: Social posts Presentations Daily motivation Writing inspiration But one thing surprised me most. People kept generating quote after quote. Not because they needed one. Because they enjoyed discovering them. The Real Insight Sometimes tools aren't abo

One of the first cloud concepts many people encounter while learning AWS is EC2 . The name sounds technical. The documentation is extensive. And the number of configuration options can make it feel like something fundamentally different from a regular computer. But while trying to understand cloud computing, I found myself repeatedly coming back to a simple thought: At the end of the day, an EC2 instance is just another computer. That realization helped me understand cloud infrastructure much more clearly. The Intimidation Factor When people first open the AWS console, they encounter terms such as: EC2 VPC Security Groups Elastic IPs Auto Scaling It is easy to feel that cloud computing is an entirely different world. But before diving into those concepts, it helps to ask a simpler question: What is an EC2 instance actually providing? Starting with the Name EC2 stands for: Elastic Compute Cloud The important word here is: Compute AWS is essentially renting computing resources. When you launch an EC2 instance, AWS allocates: CPU Memory (RAM) Storage Networking to a virtual machine that you can access. In other words: You are renting a computer that lives inside AWS's infrastructure. Comparing It to a Personal Computer Consider a typical laptop. It contains: A processor RAM Storage An operating system Network connectivity Now consider an EC2 instance. It also contains: Virtual CPUs RAM Storage An operating system Network connectivity The location is different. The concepts are the same. The Main Difference: Ownership The biggest difference is not technical. It is operational. With a personal computer: You own the hardware. The machine sits near you. You maintain it. With EC2: AWS owns the hardware. The machine runs in a data center. AWS manages the physical infrastructure. You only manage the virtual machine running on top of it. Why Linux Knowledge Transfers This was one of the most interesting observations during my learning. If an EC2 instance runs Linux, many of th

A few weeks after switching from Windows to Linux, I noticed something interesting. The hardware had not changed. The processor was the same. The RAM was the same. The SSD was the same. And yet, the laptop felt noticeably faster. Not necessarily because applications were completing tasks dramatically quicker, but because the entire system felt more responsive. Keyboard input felt immediate. Windows opened faster. Terminal commands appeared instantly. The desktop experience felt smoother. This raised a question: How can the same hardware feel different simply because the operating system changed? While I'm still learning, this is the mental model I've built so far. The Hardware Didn't Change Consider a laptop with: AMD Ryzen processor 16 GB DDR5 RAM NVMe SSD Modern integrated graphics When switching operating systems, none of these components change. The CPU does not suddenly become faster. The RAM does not magically increase. The SSD remains identical. From a hardware perspective: ```text id="u3m9xd" Before → Same Hardware After → Same Hardware So the difference must come from somewhere else. --- ## An Operating System Is Not Just a User Interface Many people think of an operating system primarily as the desktop they see. But an operating system does far more than display windows and icons. It manages: * Memory * CPU scheduling * Processes * Storage * Networking * Device drivers * Background services In other words: > The operating system decides how hardware resources are used. Two operating systems can therefore create very different experiences using the same hardware. --- ## Perceived Performance vs Raw Performance One thing I have learned is that performance is not always about benchmarks. A system can have excellent benchmark scores and still feel sluggish. Why? Because users experience responsiveness, not benchmark numbers. Examples include: * How quickly a window opens * How fast a menu appears * How responsive typing feels * How quickly applications launch

One of the first networking concepts that confused me was this: Why does a computer need both a MAC address and an IP address? At first glance, they seem to solve the same problem. Both appear to identify a device. Both show up in networking tools. Both appear in packet captures. So why do we need two different addresses? While exploring Linux networking tools and Wireshark, the distinction finally started making sense. This article summarizes the mental model that helped me understand the difference. Looking Inside the Machine Before discussing addresses, it helps to understand where they come from. If you open a typical laptop, you will usually find components such as: Battery RAM Storage Processor Cooling system Network interfaces One of those network interfaces is typically: A Wi-Fi card An Ethernet controller These components are responsible for network communication. They are the parts of the machine that actually send and receive data across a network. Every Network Interface Has an Identity A network interface needs a way to identify itself. This is where the MAC address comes in. A MAC address is associated with a network interface card (NIC). Example: ```text id="q3d9nm" 2C:9C:58:8B:2D:7B Think of it as the identity of the network interface itself. Not the operating system. Not the browser. Not the application. The network hardware. --- ## What Is a MAC Address? MAC stands for: **Media Access Control** A MAC address operates at the **Data Link Layer** of the OSI model. Its primary purpose is to help devices communicate within a local network. Examples include: * Laptop to router * Router to switch * Switch to printer In other words: > MAC addresses help devices find each other on the same local network. --- ## What Is an IP Address? An IP address serves a different purpose. Example: ```text id="g8x4tc" 192.168.1.20 or ```text id="v6u7mz" 2405:201:8000::1 IP addresses operate at the **Network Layer**. Their job is to identify where a device exists within a

Here's the maths most calculators get wrong Most freelance rate calculators are wrong. Not buggy — conceptually wrong. They take your income goal, divide by hours, and hand you a number that will quietly lose you money all year. I got tired of explaining the correct calculation to freelancer friends, so I built a tool that does it properly. Here's the logic behind it, and a bit about how I built it. The flawed formula The typical calculator does this: hourly_rate = annual_income_goal / annual_hours_worked So if you want $80,000 and work 2,080 hours a year (40 × 52), it tells you to charge ~$38/hr. This is wrong in three separate ways. Fix 1: Tax is not optional Your income goal is a net number — what you want to keep. But you're taxed on gross. So the first correction is grossing up: const grossIncome = netTarget / ( 1 - taxRate ); // $80,000 / (1 - 0.28) = $111,111 That's already a $31,000 gap the naive formula ignores. Fix 2: You don't bill every hour you work This is the big one. Freelancers bill roughly 55–65% of their working hours. The rest is admin, proposals, invoicing, sales calls, and learning. const totalHours = weeksWorked * hoursPerWeek ; // 46 * 40 = 1840 const billableHours = totalHours * billableRatio ; // 1840 * 0.6 = 1104 So your real billable capacity isn't 2,080 hours. It's closer to 1,104. Pricing on the wrong denominator is how people end up working 50-hour weeks and still missing their income target. Fix 3: Business expenses come out of gross Software, hardware, insurance, courses — all real costs that need covering before you pay yourself: const totalNeeded = grossIncome + annualExpenses ; The corrected formula Putting it together: function minimumRate ({ netTarget , taxRate , expenses , weeks , hoursPerWeek , billableRatio }) { const gross = netTarget / ( 1 - taxRate ); const totalNeeded = gross + expenses ; const billableHours = weeks * hoursPerWeek * billableRatio ; return totalNeeded / billableHours ; } minimumRate ({ netTarget : 80000 ,

A few months back I got frustrated. I needed to calculate something — nothing crazy, just a loan payment — and every site I landed on either wanted me to sign up, showed ads on every input, or was in English only (not helpful when sharing with family abroad). So I built Calculora . It's a free calculator site. 150+ tools, 13 languages, zero data collection. Everything runs in your browser — nothing gets sent anywhere. Why 13 languages? Because most people on the internet don't speak English as a first language. I wanted it to actually work for them — not just have a translated homepage, but real localized URLs, right-to-left layout for Arabic, the whole thing. Getting that right in Next.js took more time than I expected. Each tool has a different slug per language, so the routing has to map hundreds of combinations correctly. Totally worth it though. The math rendering For tools like the equation solver and statistics calculator, I wanted the formulas to look like real math — not just text. I used KaTeX for this. It's fast, lightweight, and renders LaTeX properly in the browser. The step-by-step solutions actually show the working — discriminant, roots, the full process — rendered cleanly. Some tools I'm proud of Equation Solver — linear and quadratic, with full steps shown Statistics Calculator — mean, median, mode, IQR, std dev, exportable FIRE Calculator — retirement planning done simply Debt Snowball/Avalanche — side-by-side payoff comparison What's next More tools, better mobile experience, and filling in gaps across the language versions. If you try it, I'd genuinely love feedback — especially on anything that feels off or missing. calculora.net

If you run Aviatrix on Azure, there is a slow-moving infrastructure change happening underneath your gateways right now that is worth paying attention to. Microsoft started rolling out a new generation of network hardware on May 26, 2026, called MANA (Microsoft Azure Network Adapter). For most Azure workloads, the change is invisible. For network virtual appliances (NVAs) like Aviatrix gateways, it is not, and Aviatrix has issued a field notice ( FN-2026-AZ-001 ) telling customers to take action. What is MANA and Why is Microsoft Rolling it Out? For roughly a decade, Azure VMs with Accelerated Networking enabled have used Mellanox-based NICs exposed to the guest as mlx4/5 SR-IOV adapters . SR-IOV (Single Root I/O Virtualization) lets the VM talk to the network card hardware directly, bypassing the hypervisor's virtual switch. This is what gives Accelerated Networking its low-latency, high-throughput characteristics. Microsoft has been quietly building its own in-house networking silicon. MANA is the result: a Microsoft-designed network adapter that replaces the Mellanox hardware Azure has been using on the host side. From an Azure customer's perspective, MANA preserves Accelerated Networking semantics, but the device the guest OS sees is different. The driver is different. The interface name is different. And that is where Aviatrix gateways run into trouble. Why Aviatrix Gateways Are Affected Aviatrix gateways are not generic VMs. They run a custom data plane that binds tightly to the underlying NIC for performance reasons. Specifically, the gateway image expects the Mellanox driver to be present and operational. On MANA hardware, that driver is no longer in play, and the gateway image does not yet include a MANA-aware driver. Per the field notice, the symptom is intermittent performance degradation rather than an outright outage. That makes it harder to detect: throughput drops, latency spikes, or session resets that look like noise can be the early signs of a gate

The pre-order trailer also revealed new voice actors.

Introduction Excel is a powerful spreadsheet program developed by Microsoft that is used to calculate, organize and analyze data. It provides a way of turning raw data into meaningful insights through handling large datasets more efficiently from tracking sales and expenses to analyzing trends. Various Excel applications. Decision making: One of the major ways Excel is used in real-world data analysis is to support decision making. Companies collect large volumes of raw data everyday ranging from customer information, sales records to log records. This data is organized and cleaned by Excel into tables, charts and reports making it easier to derive insights and identify trends that help in decision making. Financial reporting: Excel is also widely used for financial reporting and budgeting. Businesses use it to record income and expenses, calculate profit margins and create financial predictions. By analyzing financial data, organizations are able to monitor their performance over time and plan better for future growth. Marketing performance: In addition to that, Excel can be used in market analysis. Marketing teams utilize Excel to track campaign and social media performance, customer engagement and product popularity. Insights derived from this data helps companies improve their marketing strategies and better understand consumer behavior. This past week I was introduced to several data cleaning features and formulas used in Excel to make analysis less nerve-wracking. For example, in stead of editing data cell by cell in the case of duplicate values, you can use the Find and Replace filter. Also, conditional formatting makes it easier to highlight specific cell ranges and erase duplicate values. Functions and formulas make it easy to obtain statistical and mathematical data. Learning Excel helps you look at data differently. Instead of data being just a bunch of texts, numbers or logs, data becomes something you can use to gain insights, make decisions, reveal pat

As I'm observing engineers, I notice that most of them share the same characteristic: unending loads of curiosity. You, software developers, are deeply interested in how things work underneath; you implement, break, troubleshoot, fix, and break again. You create apps that people use everyday and by doing so, you shape the digitalised world we live in today. Now let me share something personal: I am terrified of breaking things. I am often terrified to such an extent that I find it hard to breathe. I am suffering from something called Generalised Anxiety Disorder (GAD), which basically means I am allergic to uncertainty. While most people see trying something new as exciting, for me it's a source of stress. Every unknown step, every unfamiliar process, every situation where I don't know what comes next — it triggers something. My brain immediately goes to the worst-case scenarios. "I can't do this." "I'll do it wrong." "What if something breaks?" These thoughts don't just pop up and disappear — they pile on top of each other until they become paralyzing. But this story isn't about anxiety — it's about how good UX can change a moment from overwhelming to manageable. And how you, as a software developer, can make a real change for people who are struggling. The app that saved my day A few months ago I decided to change my mobile operator. The alternative offer had much better terms that sounded really appealing to me. No long-term contract, competitive prices, support for eSIM for travellers abroad – in short: very flexible. Head held high, I went to the new operator's office to ask them to transfer my number. But the agent quickly wiped the smile off my face. "Yes, this offer is flexible, but you need to do all the operational work yourself in the app. I can only offer you a regular long-term contract," he said. He gave me my new SIM card, and I, with a long face, went to the nearby cafe. The thought that I had to transfer my number myself felt daunting. "What if I do

Xbox's 25th anniversary collection drops in November.

Microsoft has created a special edition Xbox Series X to celebrate 25 years of the console. The Xbox 25th-anniversary console takes design cues from the original Xbox console, with both the console and controller featuring a translucent green design. "For the first time, we're bringing a translucent design to Xbox Series X, drawing inspiration from […]

One of Microsoft's biggest gaming franchises is sticking with Xbox.

The console industry is in a weird place, and both Xbox and PlayStation have a chance to change the narrative a bit with their showcases at Summer Game Fest. Sony did that by focusing on the single-player titles it’s known for, and then it was Microsoft’s turn. The Xbox Games Showcase was focused mainly on […]

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Every time I started a side project, I rebuilt the same five things before I wrote a single line of the actual idea: auth, a database, file uploads, a deploy pipeline, and TLS. Different domain, same plumbing. By the third project I was copy-pasting my own docker-compose.yml from a folder two repos over and renaming things until they stopped erroring. So I stopped. I froze that plumbing into one boilerplate — PocketBase + Next.js + Caddy on a single cheap VPS — and now I ship every side project on it. Same shape every time: clone, rename, write the part that's actually new, push. The thing I care about most isn't the speed, though. It's that I stopped paying for it. A handful of real projects now run on this setup for a few euros a month, total — not a stack of per-service SaaS bills that each want $25 here and $20 there before you've shipped anything. No Vercel seat, no managed Postgres, no Auth-as-a-Service, no object-storage line item. Here's the whole thing. Why this stack The trick that makes the cost collapse is PocketBase . It's a single Go binary that gives you, in one process: Auth — email/password, OAuth, the works, with a real users collection A database — SQLite, with a schema you manage from an admin UI Realtime — subscribe to collection changes over SSE File storage — uploads handled, with on-the-fly thumbnails An admin dashboard — at /_/ , for free That's four or five separate SaaS products collapsed into one binary that runs anywhere and stores everything in a folder. Compared to wiring up Supabase or Firebase, the mental model is tiny: it's one process and one data directory. Back up the directory and you've backed up the entire app — database, uploaded files, auth tokens, all of it. For the front I use Next.js (App Router, React Server Components) because that's where I'm fastest, and Caddy as the reverse proxy because it gets you automatic HTTPS with zero config — it provisions and renews Let's Encrypt certificates on its own. And it all lives on

Before this week, I thought Excel was just a fancy calculator with boxes. But after three days of my Data Science & Analytics course, I realise I was wrong. Really wrong. Excel is a spreadsheet tool used by millions of people from small business owners to data analysts at giant companies. And the best part? You don’t need to be a programmer to use it. You just need to know a few tricks. Here’s how Excel helps solve real-world problems using exactly what I learned in Week 1. 3 Real-World Ways Excel Is Used Business decisions with logic Managers use IF() statements to answer yes/no questions. Example: =IF(Sales>1000, "Bonus", "Needs Improvement"). One cell can decide who gets paid more. Cleaning messy data Real data is never clean. Marketing teams use Remove Duplicates, Find & Replace, and Text to Columns to fix hundreds of messy rows in seconds. No manual typing. Tracking deadlines and ages HR teams use DATEDIF() to calculate employee ages or years of service. TODAY() and NOW() keep reports automatically updated. No more “oh, I forgot to update the date.” 3 Excel Features I Learned This Week Remove Duplicates – One click, and Excel deletes repeated rows. Saved me from sending the same customer email twice. IFERROR() – Hides ugly errors like #DIV/0! and shows something friendly instead (e.g., “Check data”). Your boss will thank you. Sort & Filter – With AutoFilter, I can find all sales above $500 in one second. Then Custom Sort lets me sort by date and region together. My personal reflection Honestly? Learning Excel has changed how I see data. I used to look at a messy spreadsheet and feel lost. Now I see Remove Duplicates, Text to Columns, and TRIM() as tiny tools that bring order to chaos. Data isn’t scary anymore. It’s just a puzzle and Excel gives me the pieces. I’m only one week in. But I already feel like a junior data analyst in training.

I'm sure many of you have experienced the frustration of publishing a new blog post only to find it's not immediately visible in search engine results. I recently learned that search engines like Bing and Yandex offer a way to quickly notify them of new posts via the IndexNow API. So, I decided to integrate this feature into my blog. Attempts and Pitfalls Initially, I created helper functions in services/indexnow_service.py to call the IndexNow API when a post was published. I structured the code to use asyncio.create_task to send a ping asynchronously whenever the post status changed to 'published' in the BlogRepository.update_status method. # services/indexnow_service.py (partial) import asyncio import httpx async def ping_urls ( urls : list [ str ], api_key : str ): async with httpx . AsyncClient () as client : for url in urls : try : response = await client . post ( " https://api.indexnow.org/submit-url " , json = { " url " : url , " key " : api_key } ) response . raise_for_status () print ( f " Successfully pinged { url } " ) except httpx . HTTPStatusError as e : print ( f " Error pinging { url } : { e } " ) except Exception as e : print ( f " An unexpected error occurred for { url } : { e } " ) async def ping_blog_post ( post_url : str , api_key : str ): await ping_urls ([ post_url ], api_key ) # BlogRepository.update_status (partial) async def update_status ( self , post_id : int , new_status : str ): # ... existing logic ... if new_status == ' published ' and INDEXNOW_KEY : post = await self . get_post_by_id ( post_id ) # In reality, you'd get the URL from the post object asyncio . create_task ( ping_blog_post ( post . url , INDEXNOW_KEY )) # ... I also created an admin API endpoint to manually trigger pings. I set up the public/<KEY>.txt file and even configured middleware. But to my surprise, the pings just wouldn't go through, no matter what I tried. After about three hours of debugging, I discovered that the ownership verification file required by the In