ARTICLES

Notes from the field.

Practical writing on web scraping, data pipelines, automation, and building with AI. From real project experience, not theory.

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Building

The Generalist Advantage: Why Knowing Architecture Matters More Than Knowing One Language

In an era where AI writes code faster than most developers, the real skill is knowing how systems connect. A case for generalists who build across the stack.

April 14, 20267 min read
Industry PlaybookMay 19, 2026

Data for Marketing Agencies: What Your Clients Need and How to Deliver It

How marketing and social media agencies use managed data pipelines for competitor tracking, creator intelligence, and campaign reporting across Instagram and TikTok.

7 min read
Industry PlaybookMay 16, 2026

Web Scraping for Recruiters: Building a Candidate Pipeline Without Burning LinkedIn Accounts

How recruiting teams use managed data extraction to build candidate pipelines at scale without risking their Sales Navigator seats or rep accounts.

7 min read
Industry PlaybookMay 15, 2026

Web Scraping for Real Estate Investors: What Data You Actually Need

A practical guide to using web scraping for off-market deals, tax-delinquent lists, probate leads, and county records. What data matters, where to get it, and what it costs.

8 min read
Case StudyMay 12, 2026

Tracking 300 Instagram Competitors for a 45-Brand Agency

How I built an Instagram competitive intelligence pipeline for a social media agency managing 45 brand accounts. 300+ competitor profiles tracked, weekly reports, and a 22% engagement lift.

7 min read
Case StudyMay 9, 2026

Building a Real-Time SEC Filing Pipeline: 3.2 Minutes from Publication to Data

How I built a real-time SEC EDGAR pipeline for a quant hedge fund. 2,000+ filings daily, 180+ normalized metrics, 99.4% accuracy, and the XBRL gaps that made it necessary.

8 min read
Web ScrapingMay 8, 2026

How Web Scraping Works (And When You Need a Professional)

A plain-language explanation of what web scraping is, how it works under the hood, and the point where doing it yourself stops making sense.

7 min read
Case StudyApril 22, 2026

How I Built a LinkedIn Enrichment Pipeline for 70,000 Profiles

A deep dive into building a managed LinkedIn profile enrichment pipeline for a B2B sales team. 70,000 profiles, 87% match rate, zero account bans, and what went wrong along the way.

8 min read
Web ScrapingApril 22, 2026

The Anti-Bot Landscape in 2026: What You Need to Know Before Starting a Scraping Project

An honest overview of what anti-bot protection looks like in 2026, which sites are hardest to scrape, and what that means for your project scope and budget.

7 min read
AutomationApril 17, 2026

n8n vs Custom Code: When a Visual Workflow Beats a Script

When to use n8n for automation and when to write custom code. Based on real projects where I have used both, sometimes in the same pipeline.

6 min read
Data EngineeringApril 16, 2026

What a Data Pipeline Actually Looks Like (From Source to Dashboard)

A plain-language walkthrough of what a data pipeline is, how the pieces connect, and what happens between 'I need data' and 'the dashboard updates automatically.'

6 min read
Case StudyApril 16, 2026

TikTok Creator Intelligence: Profiling 25,000 Creators Across 14 Niches

How I built a TikTok creator intelligence pipeline for an influencer marketing agency. 25,000 creators profiled, custom scoring models, audience demographics, and what the SaaS databases miss.

7 min read
Web ScrapingApril 11, 2026

The Real Cost of Web Scraping: DIY vs Hiring a Specialist

A breakdown of what web scraping actually costs, from writing your own scripts to hiring someone who has done it 200+ times. Based on real project numbers, not guesses.

8 min read
Data EngineeringApril 7, 2026

Web Scraping vs API: When to Use What

APIs and web scraping both get you data, but they work differently, cost differently, and break differently. Here is how to decide which one fits your project.

6 min read
Case StudyMarch 28, 2026

How I Built a Pipeline Covering 932 US Counties

A deep dive into a real project: building and maintaining a property records extraction pipeline across 932 US counties for a proptech startup. What worked, what broke, and what I learned.

9 min read