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Google shipped Gemma 4 12B this week — a model that packs near-26B performance into something that runs on a consumer laptop with 16GB of RAM or unified memory. That alone would be notable. But the more significant move is the architecture: no multimodal encoders at all. Vision and audio go straight
This is a submission for the GitHub Finish-Up-A-Thon Challenge FlowDesk is a fully offline, production-quality productivity dashboard that combines three tools I always wanted in one place — a habit tracker, a Pomodoro focus timer, and a Kanban task board — all in a single beautiful React app with z
Building a Docker image from scratch can seem daunting at first, but a Dockerfile is really just a step-by-step recipe. Whether you're containerizing a FastAPI app or an Nginx server, you need to understand exactly what each instruction does. Here is a concise breakdown of the core Dockerfile concep
Have you ever seen an AI demo where five agents talk to each other, assign tasks, debate plans, write code, review code, fix bugs, and declare victory? It looks futuristic. It also looks suspiciously like a meeting with no manager, no agenda, and everyone speaking confidently at once. Multi-agent sy
I’ve been building SerionFlow, an AI-powered programmatic SEO platform for B2B SaaS teams. The original idea sounded simple: Find search opportunities, generate SEO pages, and help companies publish them under their own domain. But the more I built it, the more I realized the hard part was not gener
Introduction Conversational AI is no longer a niche hobby; enterprises use it for customer support, lead qualification, and internal tooling. Rasa Open Source gives you a production‑ready stack that runs on‑premise, lets you keep data private, and offers full Python extensibility. In this article we
Everyone will repeat the headline 12B. What actually changes things is the 2B that fits in your pocket. Google released the Gemma 4 family this week, and most of the coverage will fixate on the biggest model. I want to point at the other end of the range, because that is where the real shift lives.
E-commerce operations live and die by data velocity. For enterprise engineering teams running Magento 2 (Adobe Commerce), extracting transactional order data for downstream fulfillment, accounting, or B2B sales pipelines can be a persistent infrastructure bottleneck. Most companies either rely on ar
A year of AI-coding discourse taught me one thing: the hardest part isn't the tools — it's the vocabulary wall. If English isn't your first language, "token", "context window", "hallucination", "harness" don't sound like concepts. They sound like spells. 🪄 Matt Pocock's brilliant Dictionary of AI C
Detect AI agent hallucinations without labeled data. Zero-shot LSC detection, claim decomposition, and real-time guardrails. Python code included. Your AI agent returns confident answers. Half of them are fabricated. Standard metrics say everything's fine. This is the silent failure problem: agents
Hi everyone, I'm a complete beginner to Golang and programming. I've recently started learning Go, but I'm finding it difficult to understand the syntax and how different parts of the language fit together. I've gone through some tutorials, but I still get confused by things like functions, variable
Charlie Holtz, CEO and co-founder of Conductor (YC-backed), recently walked through his entire AI coding workflow on Y Combinator's Full Stack video series. I watched it twice. Not because it was flashy. Because it confirmed something I've been feeling for months about my own AI coding workflow in 2
Every developer writing code today has a copilot open somewhere. It sits in the IDE, it autocompletes, it chats, it explains. It has become as natural as syntax highlighting. And for most teams, the copilot is quietly sending every prompt, every function name, every variable, every piece of business
Generating High-Quality PDFs in Django with Playwright (When Other Libraries Fall Short) PDF generation is one of those tasks developers often underestimate — until you try to render modern HTML, Tailwind CSS, external images, or embedded map screenshots. Suddenly, the limitations of traditional Pyt
My first attempt at a remote vibration monitoring system ended with a network switch that couldn't handle the throughput and a cloud bill that made me question my life choices. I was streaming raw high-frequency accelerometer data from several machines directly to a central cluster, thinking that "c
My last two posts were about not installing things the browser already gives you — native elements over libraries. But that's only half a rule, and leaving it there would be dishonest, because I install plenty of libraries. The point was never "zero dependencies." It was "no redundant ones." So here
What it takes to build a prediction market platform like Polymarket in 2026, why you can't just fork it, and how to ship one on Base with an onchain CLOB, dual-oracle resolution, and a TypeScript SDK. People ask me how to build their own Polymarket more than they ask anything else. The reasons vary.
In the previous article, I showed how I built a dynamic form renderer using JSON configuration in React + Formik. Rendering the form fields turned out to be the easy part. The real challenge started when I needed validation. In a traditional form, creating a Yup schema is straightforward because the
Modern applications demand long‑lasting workflows that can withstand crashes, restarts, and failures, often relying on external platforms. pg_durable integrates durable workflow orchestration directly into PostgreSQL, enabling workflows to be created in SQL and reliably executed, monitored, inspecte
Gemini Flash + Supabase pgvector + Langfuse = a fully functional RAG chatbot with observability that costs exactly zero dollars. I wanted a chatbot on my portfolio that could answer questions about my projects, skills, and experience - without paying for infrastructure. No OpenAI bills. No Pinecone
