Join us

ContentUpdates from superworks...
Link
@faun shared a link, 1 month ago

Writing Load Balancer From Scratch In 250 Line of Code

A developer rolled out a fully working **Go load balancer** with a clean **Round Robin** setup—and hooks for dropping in smarter strategies like **Least Connection** or **IP Hash**. Backend servers live in a custom server pool. Swapping balancing logic? Just plug into the interface...

Writing Load Balancer From Scratch In 250 Line of Code
Link
@faun shared a link, 1 month ago

Organize your Slack channels by “How Often”, not “What” - Aggressively Paraphrasing Me

One dev rewired their Slack setup by **engagement frequency**—not subject. Channels got sorted into tiers like “Read Now” and “Read Hourly,” cutting through noise and saving brainpower. It riffs off the **Eisenhower Matrix**, letting priorities shift with projects, not burn people out...

Link
@faun shared a link, 1 month ago

Privacy for subdomains: the solution

A two-container setup using **acme.sh** gets Let's Encrypt certs running on a Synology NAS—thanks, Docker. No built-in Certbot support? No problem. Cloudflare DNS API token handles auth. Scheduled tasks handle renewal...

Privacy for subdomains: the solution
Link
@faun shared a link, 1 month ago

Users Only Care About 20% of Your Application

Modern apps burst with features most people never touch. Users stick to their favorite 20%. The rest? Frustration, bloat, ignored edge cases. Tools like **VS Code**, **Slack**, and **Notion** nail it by staying lean at the core and letting users stack what they need. Extensions, plug-ins, integrati..

Link
@faun shared a link, 1 month ago

Authentication Explained: When to Use Basic, Bearer, OAuth2, JWT & SSO

Modern apps don’t just check passwords—they rely on **API tokens**, **OAuth**, and **Single Sign-On (SSO)** to know who’s knocking before they open the door...

Link
@faun shared a link, 1 month ago

Uncommon Uses of Common Python Standard Library Functions

A fresh guide gives old Python friends a second look—turns out, tools like **itertools.groupby**, **zip**, **bisect**, and **heapq** aren’t just standard; they’re slick solutions to real problems. Think run-length encoding, matrix transposes, or fast, sorted inserts without bringing in another depen..

Link
@faun shared a link, 1 month ago

Building a Resilient Data Platform with Write-Ahead Log at Netflix

Netflix faced challenges like data loss, system entropy, updates across partitions, and reliable retries. To address these, they built a generic Write-Ahead Log (WAL) system serving a variety of use cases like delayed queues, generic cross-region replication, and multi-partition mutations. WAL abstr..

Link
@faun shared a link, 1 month ago

Jupyter Agents: training LLMs to reason with notebooks

Hugging Face dropped an open pipeline and dataset for training small models—think **Qwen3-4B**—into sharp **Jupyter-native data science agents**. They pulled curated Kaggle notebooks, whipped up synthetic QA pairs, added lightweight **scaffolding**, and went full fine-tune. Net result? A **36% jump ..

Jupyter Agents: training LLMs to reason with notebooks
Link
@faun shared a link, 1 month ago

Implementing Vector Search from Scratch: A Step-by-Step Tutorial

Search is a fundamental problem in computing, and vector search aims to match meanings rather than exact words. By converting queries and documents into numerical vectors and calculating similarity, vector search retrieves contextually relevant results. In this tutorial, a vector search system is bu..

Link
@faun shared a link, 1 month ago

Building a Natural Language Interface for Apache Pinot with LLM Agents

MiQ plugged **Google’s Agent Development Kit** into their stack to spin up **LLM agents** that turn plain English into clean, validated SQL. These agents speak directly to **Apache Pinot**, firing off real-time queries without the usual parsing pain. Behind the scenes, it’s a slick handoff: NL2SQL ..

Building a Natural Language Interface for Apache Pinot with LLM Agents
Who We Are?

We Are Superworks

We believe to transform enterprises for building a revolutionary workplace with better productivity.

Our Mission:

By putting people first, we strive to make every workplace a place where individuals are motivated, valued, and fulfilled. Join us in our quest to shape the future of your business.

Our Vision:

Our vision is to drive the next technological evolution and equip our clients with the essential tools for future success. We believe to empower every business to grow more with the help of software as a service. We believe to deliver cutting-edge technology that simplifies business operations and streamlines processes.

Core Values:
Our core values embody our identity and principles. We understand the significance of having a set of values for a productive work environment. These values must be harmonized to the advantage of everyone involved. We are dedicated to making a meaningful difference in our customers' lives through our offerings.

Our core values include:

A meaningful approach

Innovative ideas

Customer satisfaction

Willingness to learn

Continues upgradation

Trust and transparency

What’s Our Agenda:

Boost Productivity and Drive Efficiency Through Automation