Go is a compiled language — the code is converted into machine‑readable form before execution. From a beginner’s perspective, this means Go catches many errors during compilation, giving you cleaner, faster, and more predictable performance at runtime. Go is widely used for: API development CLI tools Microservices architecture Backend server. DEVOPS activity So it fits perfectly with the kind of
Why I built it I needed a PostgreSQL parser that could run inside Go tooling without CGO, external binaries, or runtime dependencies. SQL is not one grammar PostgreSQL has a lot of dialect-specific edge cases AST shape matters more than “can it parse” Error handling becomes a product feature Real-world SQL is uglier than examples No CGO, easy installation, works in CI, easy to embed in linters a
If you've tried building an AI agent in the last six months, you've hit the same wall: there are half a dozen frameworks, each with a different philosophy, a different API surface, and a different definition of what an "agent" even is. I spent a weekend writing the same simple agent — "read a GitHub issue, classify it as bug/feature/question, and post a comment" — in six different frameworks. This
Originally published on TechSaaS Cloud Originally published on TechSaaS Cloud An API gateway sits between clients and your backend services. It handles cross-cutting concerns so your services do not have to: authentication, rate limiting, request routing, load balancing, caching, and observability. WebMobileIoTGatewayRate LimitAuthLoad BalanceTransformCacheService AService BService CDB / Cache API
A deep, opinionated, practical guide for the engineer who has crossed the mid-level threshold — or is about to. The mental models, technical habits, ownership patterns, communication skills, and career mechanics that separate "solid senior" from "engineer the whole team builds around." Grounded in 2026 reality — AI-augmented coding, distributed async teams, post-ZIRP efficiency pressure, and a mar
In this article, I'll share six Laravel performance lessons we learned from building real client systems, including how Eloquent queries, caching, code structure, deadlines, and communication affected the way we build and maintain applications. We didn't notice anything wrong at first. The app worked, responses were fine, and everything looked clean during development. Then real users started usin
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
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