Forem: Muhammad Sheraz

Your CSS Animations Are Doing Too Much Manual Labor — Fix It With FSCSS

Muhammad Sheraz — Tue, 14 Apr 2026 01:22:27 +0000

We Need to Talk About Keyframes 🤦

CSS animations are genuinely fun — right up until you need to animate something that counts, steps, or cycles through a list.

You know the moment. You're building a loading indicator, a progress bar, or a sequenced visualization, and then it hits you:

@keyframes progress {
  0%   { content: "0%"; }
  1%   { content: "1%"; }
  2%   { content: "2%"; }
  /* ... please send help ... */
  100% { content: "100%"; }
}

That's over a hundred lines of CSS to do something a for loop handles in two seconds. Reviewing this in a PR? Painful. Modifying it six months later? Even worse.

The instinct is to offload this to JavaScript — but JS adds complexity, and if you're not careful with how you update the DOM, you'll end up causing layout thrashing that hurts your page's rendering performance.

What if CSS itself could just... loop?

FSCSS: A Pre-Processor Built for This Exact Problem 🛠️

FSCSS — short for Figured Shorthand Cascading Style Sheet — is a CSS pre-processor with one core mission: eliminate repetitive animation code.

Where Sass and Less focus broadly on making CSS more programmable, FSCSS is laser-focused on keyframe generation. It brings three new ideas to your stylesheet:

🗂️ Value arrays — group ranges or lists of values under a name
🔄 Loop syntax — iterate over those arrays directly inside @keyframes
🧮 Auto-calculation — the compiler handles all the percentage math

Write less. Generate more. Ship cleaner code.

How It Actually Works

The old way — writing it all out by hand

@keyframes countUp {
  0%   { content: "0%"; }
  1%   { content: "1%"; }
  /* this goes on forever */
  100% { content: "100%"; }
}

The FSCSS way — let the compiler handle it

@arr numlist[count(100)];

@keyframes countUp {
  @arr.numlist[]%{
    content: "@arr.numlist[]";
  }
}

You define the array with @arr, loop over it, and reference the current value for each blog. The compiler does the expansion and spits out a complete, browser-ready CSS file. Clean input, correct output, no manual counting.

Three Solid Reasons to Add This to Your Toolkit

🔧 1. Changes Take Seconds, Not Hours

Requirements shift. A loader that counts to 100 today might need to count to 500 tomorrow — or jump in increments of 10 instead of 1. In plain CSS, that's a full rewrite.

Change Needed	Standard CSS	FSCSS
Extend range to 500	Rewrite everything	Edit one number
Switch to 10-step increments	Start over	Edit one number
Swap out a value	Hunt through the file	Update the `@arr`

One-line edits. Recompile. Done.

⚡ 2. Zero JavaScript, Full CSS Performance

Because the output is pure CSS, your animations run directly on the browser's rendering engine. The JavaScript thread stays completely untouched — free to handle the logic that actually needs it. Smoother animations, better frame rates, cleaner architecture.

🗜️ 3. Tiny Source, Compressible Output

Yes, the compiled CSS file can get large with hundreds of keyframes. But repetitive text compresses extremely well — Gzip was practically made for this kind of output. Your users download a fraction of the raw file size, while you maintain a source file that's small enough to read in under a minute.

Setting It Up

You'll need Node.js on your machine before anything else.

Step 1 — Install globally via npm

npm install -g fscss

Step 2 — Write your source file

Create styles.fscss and write your animation logic using FSCSS syntax.

Step 3 — Compile to standard CSS

fscss styles.fscss styles.css

The resulting styles.css is completely valid, framework-agnostic CSS. Drop it anywhere.

A Practical Example: Animating Through a Color Palette

Say you want an element to transition through four brand colors over the course of an animation:

@arr palette[#e63946, #457b9d, #2a9d8f, #e9c46a];

@keyframes brandCycle {
  @arr.palette[]%{
    background-color: @arr.pelette[];
  }
}

FSCSS figures out that four values need four evenly-spaced stops — 0%, 33%, 66%, 100% — and generates the corresponding CSS automatically. Add more colors to the array, and it recalculates everything on the next compile.

Quick Comparison

	Vanilla CSS	FSCSS
100-step animation	100+ lines	~5 lines
Updating the range	Full rewrite	Edit 1 value
Needs JavaScript	Optional	Nope
Runtime performance	CSS engine	Same (CSS engine)
Source readability	😵	😌

Final Thought

Frontend tooling has gotten incredibly sophisticated on the JavaScript side. Our CSS tooling deserves the same love — especially for animations, which are often the most repetitive part of any stylesheet.

FSCSS doesn't try to replace Sass or reinvent CSS. It just solves one specific, painful problem really well.

Give your keyframes a break. Let the compiler earn its keep.

🔗 Explore FSCSS on GitHub

What's the most absurd keyframe block you've ever had to write? Share it below — bonus points if it made a coworker visibly uncomfortable 👇

Anthropic vs OpenAI: The Revenue Race That's Reshaping AI in 2026

Muhammad Sheraz — Mon, 13 Apr 2026 05:24:20 +0000

Introduction

Eighteen months ago, Anthropic was a well-funded AI lab with impressive research and modest commercial scale. OpenAI was the undisputed king of generative AI, riding a wave of ChatGPT adoption that no rival could match.

Fast forward to April 2026, and the story is dramatically different.

Anthropic has just crossed $30 billion in annualized revenue, officially surpassing OpenAI's $25 billion run rate. OpenAI, meanwhile, closed 2025 with $20 billion in confirmed ARR — itself a historic achievement — but finds itself playing catch-up in the enterprise segment it once dominated.

This is a breakdown of the numbers, what's driving them, and what they mean for anyone building on top of these platforms.

📊 The Revenue Scoreboard (April 2026)

Metric	Anthropic	OpenAI
Annualized Revenue (Apr 2026)	~$30B	~$25B
End of 2025 ARR	$9B	$20B
Year-over-year Growth	~1,400%	~3.3×
Valuation	$380B	~$730–852B
Primary Revenue Driver	Enterprise API + Claude Code	ChatGPT Subscriptions + API
Enterprise Market Share (LLM API)	32%	25%
Cash Burn (2025)	~$3B	~$9B

🚀 Anthropic: The Fastest Revenue Growth in Enterprise Software History

From $1B to $30B in 15 Months

Anthropic's trajectory has no precedent in B2B software history. Here's the timeline:

December 2024: $1B annualized revenue
Mid-2025: $4B annualized revenue
December 2025: $9B annualized revenue
February 2026: $14B annualized revenue (officially announced)
March 2026: ~$19B annualized revenue (per Bloomberg)
April 2026: $30B+ annualized revenue (confirmed)

For context: Slack, Zoom, and Snowflake — three of the fastest-growing SaaS companies ever — never came close to this pace. Anthropic went from $1B to $14B ARR in roughly 14 months.

Claude Code: The Killer App

The single biggest growth driver has been Claude Code, Anthropic's agentic coding tool that launched to the public in May 2025. By February 2026, Claude Code alone was generating $2.5B in annualized revenue — a number that had more than doubled since the start of 2026.

According to data cited by multiple analysts, Claude Code now holds a 54% market share in the AI programming tool segment, far ahead of GitHub Copilot and Cursor. Roughly 4% of all public GitHub commits are now authored by Claude Code.

Enterprise users account for more than half of Claude Code's revenue, and business subscriptions to the product quadrupled between January and April 2026.

The Enterprise Playbook

Anthropic's monetization model is a masterclass in enterprise focus:

API Revenue (70–75%): Pay-per-token consumption from enterprises and developers
Subscription Revenue (~25–30%): Claude.ai Pro and Team plans
Enterprise Agreements: Large-scale contracts with Fortune 500 companies

Eight of the Fortune 10 are now Anthropic customers. The number of enterprise customers spending over $1 million annually doubled in just two months, surpassing 1,000 businesses. Monthly visits to claude.ai surged from 16 million in January 2025 to 220 million in January 2026 — a 13× increase in twelve months.

Perhaps most telling: Anthropic monetizes at roughly $211 per monthly user, compared to OpenAI's ~$25 per weekly user. That's an 8× difference in monetization efficiency.

💡 Developer Insight: Anthropic's enterprise-first approach means their API pricing, rate limits, and SLAs are optimized for production workloads — worth considering if you're architecting AI-native applications.

🌐 OpenAI: Still a Giant, But Facing Headwinds

The $20B Confirmation

OpenAI CFO Sarah Friar confirmed in January 2026 that the company ended 2025 with $20B in annualized revenue, up from $6B in 2024 and $2B in 2023. That's a 3.3× year-over-year increase — extraordinary by any normal benchmark, even if it's being outpaced by Anthropic.

By early March 2026, OpenAI had climbed to approximately $25B in annualized revenue, per reporting from The Information and Reuters.

Revenue Breakdown

OpenAI's revenue model leans more toward consumers than Anthropic's:

Consumer Subscriptions: ChatGPT Plus ($20/mo), Pro ($200/mo), and the newer Go ($8/mo) tier. As of mid-2025, ChatGPT had 800 million weekly active users.
Enterprise & API: Fastest-growing segment, though market share in enterprise LLM APIs dropped from ~50% to ~34% as Anthropic and Google gained ground.
Microsoft Partnership: OpenAI agreed to pay Microsoft 20% of total revenue through 2032 under a renegotiated deal.

The Cash Burn Problem

Despite the revenue headline, OpenAI's cost structure is punishing:

2025 cash burn: ~$9B
2026 projected cash burn: ~$17B
Projected break-even: 2030

Inference costs alone reached $8.4B in 2025 and are projected to rise to $14.1B in 2026. Total cloud infrastructure commitments through 2030 are estimated at over $500B across Microsoft Azure, AWS, and Oracle.

⚠️ The paradox: OpenAI is growing revenue at 3× per year but burning cash faster than it can collect it. The company does not project positive cash flow until 2030.

🔄 The Competitive Crossover

For most of 2025, OpenAI held a commanding revenue lead. Anthropic was fast-growing but still a fraction of OpenAI's size. What changed?

Three things converged in late 2025 and early 2026:

1. Claude Code went mainstream. The product added $6B to Anthropic's annualized revenue base in February 2026 alone — not for the quarter, not the year. In a single month.

2. Enterprise trust shifted. In the enterprise LLM API market, Anthropic's share climbed to 32% versus OpenAI's 25%. Seven out of ten new enterprise customers, according to some reports, are now choosing Anthropic.

3. Anthropic's efficiency advantage. With $3B in cash burn versus OpenAI's $9B, Anthropic is generating revenue far more efficiently relative to its cost structure. Its gross margin, while still below targets at ~40%, is improving faster than OpenAI's.

According to Epoch AI's analysis, if these trends continue, the full annualized crossover point (where Anthropic sustains higher revenue than OpenAI on a rolling basis) is estimated around August 2026.

💰 Funding and Valuations

Both companies have raised staggering sums:

Anthropic

February 2026: Closed a $30B Series G at a $380B post-money valuation, led by GIC and Coatue
September 2025: $13B Series F at $183B valuation
Amazon investment: $8B total
IPO outlook: Potentially as early as October 2026, with bankers projecting a raise of over $60B

OpenAI

April 2026: $122B round at an $852B valuation, co-led by SoftBank
February 2026: $110B raised at $730B valuation
March 2025: $40B at $300B valuation
IPO outlook: Potential valuation of up to $1 trillion in a public offering

⚡ What This Means for Developers

If you're building AI-native products or integrating LLMs into your stack, these numbers tell a story worth paying attention to:

The enterprise API market is more competitive than it's ever been. Anthropic and OpenAI are both dropping prices, expanding context windows, and racing to ship agentic capabilities. This is good for builders — the cost of intelligence is falling.

Claude Code's dominance in the coding assistant market has implications if you're evaluating AI tools for your engineering team. Anthropic's 54% market share didn't come from marketing spend — it came from engineers choosing it for production workflows.

Neither company is profitable. Both are burning cash at historic rates. This matters for platform risk — if you're deeply integrated with either provider's API, keep an eye on their financial trajectories and consider maintaining flexibility in your architecture.

The IPO timelines are shortening. Both companies may be public by late 2026, which will bring new levels of financial transparency, regulatory scrutiny, and possibly pricing pressure as each company works toward profitability.

🔮 Looking Ahead: The Rest of 2026

Several factors will shape the rest of the year:

Anthropic's IPO: If it proceeds in October 2026, it could be the largest tech IPO since Meta
The Pentagon standoff: Anthropic has been labeled a "supply chain risk" by the Department of Defense over its safety policy restrictions — a designation that could limit access to government contracts
OpenAI's advertising push: The company projected ~$2.5B in advertising revenue for 2026, with ambitions to reach $100B in ad revenue annually by 2030
Competitive pressure from Google and Meta: Both are scaling their own frontier models, which could compress margins across the board

🧾 TL;DR

Anthropic crossed $30B in annualized revenue in April 2026, overtaking OpenAI ($25B) in one of the most dramatic revenue ramp-ups in tech history. Claude Code is the primary growth engine. OpenAI closed 2025 at $20B ARR and is growing steadily, but its cash burn is significantly higher. Both companies are on potential IPO trajectories for late 2026. For developers, the AI API market has never been more competitive — or more interesting.

Sources:

Revenue figures are annualized run rates and may differ from recognized GAAP revenue.

If you found this useful, drop a ❤️ and share it with your team. Follow for more breakdowns on the AI industry, developer tools, and tech finance.

Is WordPress Getting Replaced? Introducing Cloudflare’s EmDash

Muhammad Sheraz — Thu, 09 Apr 2026 14:37:21 +0000

A first look at the TypeScript-powered, serverless CMS that wants to fix the web's biggest security problem.

The "WordPress Problem"

WordPress powers over 40% of the internet, but it’s 24 years old. As developers, we know the pain points:

The Stats:

Plugin Security: 96% of WordPress vulnerabilities come from plugins.
Legacy Tech: Heavily reliant on PHP and traditional server hosting.
Scaling: Handling traffic spikes requires complex caching or expensive infrastructure.

Cloudflare just announced EmDash—a modern CMS built from the ground up to solve these exact issues.

What makes EmDash different?

1. Built with TypeScript & Astro

Unlike the PHP-heavy architecture of the past, EmDash is written entirely in TypeScript. It uses Astro under the hood, making it incredibly fast for content-driven sites.

2. Sandboxed Plugins (The Security Game-Changer)

In WordPress, a plugin has access to everything. EmDash runs each plugin in its own isolated Dynamic Worker (sandbox). A plugin can only do what you explicitly grant it permission to do in its manifest.

3. Serverless by Default

EmDash is built to run on Cloudflare’s global network. It scales to zero when there’s no traffic and handles massive spikes instantly without you managing a single VPS.

4. Native AI Support

It includes built-in Agent Skills and a Model Context Protocol (MCP) server. You can point an AI agent at your codebase, and it will understand how to build plugins or customize your theme automatically.

Why Full-Stack Developers Should Care

As someone working with modern stacks like Next.js and React, EmDash feels much more "natural" than legacy CMS platforms.

Theme Development: Themes are just Astro projects.
Database: Uses a modern, schema-first approach.
Monetization: Built-in support for x402, a standard for pay-per-use content.

Final Thoughts

Is it time to migrate? EmDash is currently in a v0.1.0 preview. It might be early for production enterprise sites, but for developers looking to build secure, high-performance blogs or apps, it’s a project worth watching.

emdash-cms / emdash

EmDash is a full-stack TypeScript CMS based on Astro; the spiritual successor to WordPress

EmDash

A full-stack TypeScript CMS built on Astro and Cloudflare. EmDash takes the ideas that made WordPress dominant -- extensibility, admin UX, a plugin ecosystem -- and rebuilds them on serverless, type-safe foundations. Plugins run in sandboxed Worker isolates, solving the fundamental security problem with WordPress's plugin architecture.

Get Started

Important

EmDash depends on Dynamic Workers to run secure sandboxed plugins. Dynamic Workers are currently only available on paid accounts. Upgrade your account (starting at $5/mo) or comment out the worker_loaders block of your wrangler.jsonc configuration file to disable plugins.

npm create emdash@latest

Or deploy directly to your Cloudflare account:

EmDash runs on Cloudflare (D1 + R2 + Workers) or any Node.js server with SQLite. No PHP, no separate hosting tier -- just deploy your Astro site.

Templates

EmDash ships with three starter templates:

Blog

A classic blog with sidebar widgets, search, and RSS.

Categories & tags
Full-text search
…

View on GitHub

Check out the EmDash Repository

Are you sticking with WordPress, or are you ready to switch to a TypeScript-native CMS? Let's discuss in the comments!

The Epochalypse is Coming: Are Your 32-bit Systems Ready for 2038?

Muhammad Sheraz — Tue, 07 Apr 2026 14:53:42 +0000

The Countdown You Didn't Know Existed

We all remember the Y2K scare. Well, the tech world has a new "final boss" date:

The Deadline: January 19, 2038, at 03:14:07 UTC.

At this exact second, millions of systems could "time travel" back to December 13, 1901.

This isn't a sci-fi plot; it’s a mathematical certainty for systems using 32-bit signed integers to store time.

The Root Cause: Integer Overflow

Most Unix-based systems measure time as the number of seconds elapsed since the Unix Epoch (January 1, 1970). When this value is stored in a signed 32-bit integer, it has a maximum capacity:

2^{31} - 1 = 2,147,483,647

Once we hit that limit in 2038:

The 31st bit (the sign bit) flips.
The number becomes negative.
The system interprets this as the furthest possible point in the past: December 1901.

Why This Matters for Modern Developers

Even if you use 64-bit hardware, the danger lies in legacy dependencies:

Embedded Systems: Industrial controllers and IoT hardware often run on 32-bit architectures.
Legacy Databases: Older schemas might still store timestamps as INT instead of BIGINT.
File Formats: Many protocols use fixed 32-bit fields for time.

The Fix

The solution is straightforward: Upgrade to 64-bit. By using a signed 64-bit integer, we extend our "time budget" to about 292 billion years.

2^{63} - 1 \approx 9.22 \times 10^{18} \text{ seconds}

Final Thoughts

As developers, our job is to build for the future. Whether you're working on a massive enterprise backend or building custom platforms like this blogging project, checking your timestamp data types today prevents a total "Epochalypse" tomorrow.

muhammadsherazsandila / Bloging-website

📝 Blogora - A Modern Full-Stack Blogging Platform

Blogora is a comprehensive, feature-rich blogging platform built using the MERN stack (MongoDB, Express.js, React, Node.js). Designed during an internship at Certura, Blogora empowers users to express their thoughts, connect with others, and build a vibrant writing community with social networking features.

🚀 Live Demo

🌐 Visit Blogora

✨ Features

📝 Blog Management

Create, Edit, and Delete Posts: Full CRUD operations for blog posts with rich text editor
Image Upload: Cloudinary integration for seamless image hosting and optimization
Tags System: Organize posts with customizable tags for better discoverability
Search Functionality: Find posts quickly using keyword search

👥 Social Features

User Authentication: Secure JWT-based registration and login system
User Profiles: Customizable profiles with bio, about section, and profile pictures
Follow System: Follow/unfollow other users to stay updated with their content
Comments & Replies: Engage with posts through nested comments and replies
Like…

View on GitHub

Are you working on legacy systems that might be affected by 2038? Share your thoughts or strategies in the comments!