I’ve spent 10 years building bots that bypass anti-fraud systems. Now I fight them by building anti-bot detection systems - and most defenses don’t work. In this article, I’ll break down how human-like bot traffic actually works - and show a simple way to make bots click on hidden links. Almost every website receives large volumes of “direct” and “referral” visits that are not real users. These vi
If you've ever built a form backend or an automation workflow, I built MultiValidator to fix that. One API call. Up to 50 fields. Send a batch of fields, get back validation results for all of them: import requests payload = { "fields": [ {"type": "email", "value": "[email protected]", "field_name": "email"}, {"type": "phone", "value": "+447911123456", "field_name": "mobile"}
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It Started With a Bug When I was building VMMS — a voucher management system MySQL. Clean queries. Fast results. Then I deployed to a server running MariaDB. Half my charts broke. I had written date queries like this all over the codebase: // This breaks on MariaDB DB::table('voucher_transactions') ->selectRaw('MONTHNAME(created_at) as month, COUNT(*) as total') ->groupByRaw('MONTH(crea
I spent long hours debugging why Google couldn't index my React app. Lighthouse showed green scores. The app felt fast. But Search Console kept flagging LCP failures and CLS shifts I couldn't reproduce locally. The fix? Four lines of metadata and one misunderstood render strategy. If you've ever shipped a "fast" SPA and watched it flatline in search rankings, this Core Web Vitals SEO guide is for
If you are running production workloads, this is for you. Not side projects. Not early-stage experiments. Not a single-service app with low traffic. This is for teams shipping real systems. Systems with users, uptime expectations, and release pressure. Because at that stage, your deploy process is no longer a convenience. It is part of your product. And right now, for most teams, it is the weakest
Most teams treat cloud cost as a finance problem. But the root cause is usually engineering. Bills spike, dashboards grow, alerts fire — but the underlying issue rarely gets fixed. That idea stood out to me while reading about an approach where AWS cost was handled like an SRE problem — using the same mindset applied to reliability and performance. Instead of asking “why is the bill high?”, the fo
I started where a lot of us do: a LangChain RAG walkthrough. You chunk some text, embed it, retrieve top‑k chunks, and wire an LLM to answer questions. It clicks quickly, which is exactly why it’s easy to walk away thinking you’ve “done RAG.” What bothered me was that the demo corpus is usually tiny and artificial. I write on DEV.to about things like NLP routing and CNN image classification. If I