Hi, I'm Krunal Kanojiya
Technical Content Writer based in Ahmedabad, India specialising in Blockchain, AI/ML and Software Development.
I turn complex technical concepts into articles developers actually want to read. Web3 deep dives, AI explainers, engineering case studies, developer documentation. Writing for global tech audiences since 2021.
About Me
The person behind the words
I'm a Technical Content Writer from India with a developer's background. I started as a full-stack developer in 2021, which means I understand the code before I write about it.
My specialisation is blockchain and Web3 technical writing. Smart contracts, DeFi protocols, consensus mechanisms, and Layer 2 scaling. The topics most writers skip because they're hard to get right. I also write deeply researched articles on AI/ML, data engineering, and cloud infrastructure for global tech audiences.
Good technical writing does more than explain a concept. It teaches the reader how to think about it. Whether it's a blockchain deep dive, an AI explainer, or a product case study, every piece I write is built to respect the reader's time and intelligence.
Skills & Expertise
What I Do
Services I offer
Blockchain deep dives, AI explainers, case studies, and technical tutorials. Written for developers and the companies that build for them.
Blockchain & Web3 Articles
Deep-dive technical articles on smart contracts, DeFi, Layer 2 scaling, NFTs, consensus mechanisms, and emerging blockchain protocols.
AI & Machine Learning Content
Accessible yet rigorous articles on AI/ML concepts, model architectures, data pipelines, Databricks, Azure ML, and the latest in generative AI.
Technical Tutorials
Step-by-step guides with working code that teach developers how to build, configure, and ship software. Written by someone who has actually built it.
Case Studies & Services Pages
Conversion-focused case studies and services pages that communicate technical depth while speaking directly to decision-makers and buyers.
Developer Blog Posts
In-depth engineering articles on software architecture, developer tooling, and best practices. The kind readers bookmark and share on X.
SEO-Optimised Tech Content
Technical content built for both developers and search engines. Targeting high-intent queries, building topical authority, and driving organic traffic that converts.
Experience
Where I've worked
Technical Content Writer
CurrentLucent Innovation
Writing technology blog posts, product case studies, and services pages for Lucent Innovation. Covering AI, software development, cloud, and emerging technologies to support both SEO and brand authority.
Blockchain Technical Content Writer
Cromtek Solution Pvt Ltd
Specialised technical content writer focused exclusively on the blockchain domain. Produced in-depth articles on DeFi, smart contracts, Layer 2 protocols, NFTs, and Web3 development for a global developer audience.
Developer & Technical Content Writer
Freelance
Started as a full-stack developer and gradually transitioned into technical writing. Worked with global tech clients building web applications and writing tutorials, guides, and developer content across software development topics.
From the Blog
Latest writing
Tech deep dives, tutorials, and beyond.
Neural Networks and Backpropagation: Where the Math Starts Doing Something
This is where linear algebra and probability stop being theory and start training a model. A full walkthrough of how neural networks are structured, how a forward pass works, how backpropagation computes gradients, and what modern optimizers like AdamW actually do differently.
Probability and Statistics: What AI Actually Means by Confidence
Before you can understand how LLMs train or why they hallucinate, you need probability and statistics. This article covers distributions, entropy, Bayes' theorem, and cross-entropy loss with real code examples — the exact concepts that show up in neural network training.
Linear Algebra and Calculus: The Math Your AI Model Runs On
Before you build LLMs or AI products, you need to understand the math underneath. This article breaks down vectors, matrices, dot products, derivatives, and gradients — the exact operations that run inside every neural network.
I Built a Tiny GPT Model From Scratch — Here's Exactly How It Works
How GPT really works, explained by building a 10M-parameter model from scratch in PyTorch. Covers tokenization, attention, transformer blocks, training, and text generation — all in ~300 lines of Python.
TurboQuant Explained: Google's Breakthrough in AI Model Compression
A deep dive into TurboQuant, Google's new AI compression algorithm that promises 6x memory reduction without accuracy loss.
Let's work together
Got a technical writing project, documentation need, or blog content strategy? I'd love to hear about it. Just send me an email. No forms, no fuss.
Send me an emailimkrunalkanojiya@outlook.comI typically respond within 24 hours · No contact form required