One thread. Multiple AIs. Deliberation, not polling. Most people use AI like this: 🤦 Ask one model → get one answer Ask multiple models → compare results That’s not thinking. That’s polling. Not side by side. Not isolated. But in sequence — where each one reads what the previous one said before responding. Manual Council is the simplest form of that idea. No backend. No orchestration. No
Six months ago, AI tools were "assistants." Today, they're shipping code, fixing bugs, writing tests, and even making product decisions. If you still think AI is just autocomplete on steroids, you're already behind. Let’s break down the newest AI tools that are changing how developers actually work in 2026—and how to stay relevant instead of replaced. The biggest change isn't better suggestions—it
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"}
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
Table of Contents Introduction Environment Requirements Core Features Core Design and Code Analysis Actual Execution Demo Architecture Overview How You Can Expand Future Plans & Conclusion What is this It is a basic debugger, running on Linux and implemented in C++, aiming to create a debugger that is easy to read and expand. In addition, Lavender's main function is to help users analyze the logic
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
Every developer has been here. Debugging why Puppeteer crashes in Docker but works on your machine And you still haven't built the actual feature you needed the PDF for. So I built Templar Describe your document Tell the AI what you want an invoice, a report, a contract, a receipt. It generates the HTML template for you. Call the API with your data POST /api/render { "templateName": "invoi