Technical content for AI and developer-focused companies.

In-depth explainers, architecture deep dives, and research-backed content for technical audiences.

Step-by-step how-to guides, API walkthroughs, and integration tutorials developers can actually follow.

Technical use cases, comparison pieces, and workflow guides that show what a product does and why it matters.

Founder POVs, industry analysis, and technical narratives that build credibility and category authority.

An original benchmark of 200 requests across 7 targets, comparing performance and cost for large-scale scraping.

A production-grade tutorial for a stateful AI agent with retry logic and live web scraping.

A step-by-step guide to swapping smolagents' default web tool for a Zenrows-powered one so AI agents can read JavaScript-rendered and bot-protected pages.

An architecture guide for running AI at the edge with no cloud connection required.

Challenge. The value of the role is often spread across product decisions, support, engineering, and internal communication, which makes it difficult to describe with a single metric or job description.

Approach. Interviewed nine senior technical writers, including practitioners from companies such as Google and Mastercard. Coded the interviews for recurring themes and used those themes to build the final narrative.

Outcome. The resource sparked sustained discussion among senior practitioners on LinkedIn, reached around 700 technical writers, and shifted how several of them framed the value of the role inside their own organizations.

Challenge. Comparisons in this space are usually vague or self-serving. The piece had to define a fair methodology, run it across several real targets, and report results honestly, including where the product was not the fastest option.

Approach. Ran a defined test of 200 requests across 7 target sites, compared the platforms on performance and cost, and documented the method so a reader could reproduce it.

Outcome. Published as Zenrows' reference comparison for large-scale scraping, and ranks in search for "Apify vs Zenrows" and related evaluation queries.

Challenge. Edge AI for disconnected environments is real but fragmented: the patterns are spread across separate industries and rarely named or compared. The piece had to make the space concrete without a cloud fallback to lean on, and stay useful to an architect rather than drifting into abstraction.

Approach. Researched how inference and control actually run offline across those industries, then distilled the field into five distinct patterns (the Drone, the Factory, Hierarchical Federated Learning, Store-and-Forward, and the Network), each with its constraints, trade-offs, and the situations it fits.

Outcome. Published on Actian's developer blog, where it ranks number one in search for the "edge AI architecture" keyword.

A model for ranking technical content by how much work it does for the reader.

Writing that serves the product and the person using it at the same time.

A structure for technical pieces that keeps a reader moving through the argument.