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AI: Find your way

Software engineering has entered a new phase — and it’s no exaggeration to say the community is on fire. The rise of LLMs has dramatically increased productivity and unlocked possibilities that, until recently, felt out of reach. The emergence of highly scalable products built by extremely lean teams — even a single founder powered by AI — makes it clear: this isn’t a passing trend, it’s a structural shift in how software is designed and delivered. Tools like Claude and other AI assistants ha...
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Healthcare Platform development

Excited to begin sharing my journey as a full-stack developer focused on healthcare platform development. I’m currently building my skills with Python, Django, FastAPI, React, JavaScript, SQL, and cloud technologies while exploring secure APIs, healthcare data privacy, AI-powered tools, and scalable patient-management systems. My goal is to create reliable, user-friendly software that improves healthcare operations and patient experiences. I’ll be sharing projects, lessons learned, tech...
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Your data, your rules. But how do you explain local-first?

For us, another challenge is adoption. Working with personal data takes time, and the value becomes clearer as that data grows. So for now, rather than trying to convince everyone, we’re starting with smaller groups of people who already feel the need to bring their personal data together and have more control over it. We built SynDiary around a simple philosophy: your data, your rules. We recently launched the free Core version with calendar synchronization, structured entries, Faceboo...
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I put an LLM agent on a static site for free. Here is the actual bill

The previous post made a claim I still stand behind: this site has no server, no database and nothing to patch. It is a repository that becomes HTML. Then there is a button in the bottom right corner that answers questions about me, in full sentences, out of a language model. Both things are true at the same time. The second one is only free at the point where you happen to be looking. Where the agent actually runs Not here. It is a Docker image on a Hugging Face Space , on...
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Language Models and Languages: Why "Multilingual" Is an Illusion of Equality

When people see ChatGPT or Claude answer fluently in Swahili or Thai, the natural impression is that the model "knows" all languages equally well. It doesn't — and the gap isn't cosmetic. It runs straight through the architecture of how these models read and process text. What follows is a breakdown of where that gap actually comes from, how large it is, and what's being done about it. 1. The problem starts before the model "thinks" — at tokenization An LLM never reads text direc...
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Consolidation Is the Missing Phase in Agent Memory

The field has one answer to running out of context, and that answer is more context. Windows went from thousands of tokens to hundreds of thousands to millions, and the next number is already being quoted. The implicit theory is that a large enough window makes the memory problem go away. Biological intelligence had the same problem and did not solve it that way. Working memory in humans is famously tiny, a handful of items, and it did not grow. What grew instead was a second process, running...
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Processing Heterogeneous IoT Logs with Fluent Bit and Elasticsearch

A lightweight two-stage approach for parsing, preprocessing and storing semi-structured home automation data The full configuration example is available on GitHub. Home automation systems tend to generate a surprisingly heterogeneous collection of logs and measurements. In this project, most data originates from Domoticz, but additional information is produced by ESP8266/D1 devices, alarm scripts, monitoring tools and other IoT components. Some records are plain text, some contain ti...
Python Pandas to the Rescue: The Ultimate Data Cleanup Guide
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Python Pandas to the Rescue: The Ultimate Data Cleanup Guide

Introduction Every data science, analytics, business intelligence, and any other data-related report depends on a clean dataset. However, almost 90% of the time, we can't clean and process to begin with. In most cases, the datasets are characterized by inconsistent formatting, varying levels of missing values, and other structural anomalies. While there are different tools for data preprocessing, Python's pandas is often utilized. Thus, to provide a detailed understanding of the pandas li...
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Taming SPAs with VORTEX: How a Crawler Actually Understands React, Vue, and Angular

💡Let’s run a mental experiment. You open a SPA built with React. You point your favorite scanner—the one you've used for years, the one that "never fails"—to audit it. You wait. It generates a neat, polished report with a nice logo and a progress bar. And it tells you: "2 routes found. 0 critical vulnerabilities." Two routes. In an application featuring a complete dashboard, an admin panel, over forty endpoints, and half a dozen features locked behind feature flags. The scanner isn't b...
A Series of Unfortunate Jobs
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A Series of Unfortunate Jobs

You can't tell me Laravel queues haven't bitten you at least once. It's great that we get them out of the box, but man, they can be confusing as hell sometimes. Over the years, I've screwed up, more than once, and collected quite a few lessons along the way. Claude is currently Pondering.. , I'm waiting, and bored, so shall we? Gotcha #1 I want you to look at the code below and tell me if you can spot anything wrong: <?php namespace App\Jobs ; use Da...
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I Built GPT Image 2.5: AI Image Generation with Both Classic Prompts and a Chat Agent

I recently built GPT Image 2.5, a web-based AI image generation and editing workspace: https://gpt-image-2-5.org/ Most AI image tools follow the same pattern: choose a model, write a prompt, select a size, click generate, and wait for the result. That workflow is still useful, so GPT Image 2.5 supports the classic image generation flow. But I also wanted to explore a more natural way to create images: generating through conversation. Two ways to create images GPT Image...
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Membangun SAPA: AI Agent pendeteksi pesan penipuan untuk UMKM Indonesia

Penjual online di Indonesia menerima pesan penipuan setiap hari. Modus yang paling sering muncul ada dua. Pertama, phishing yang mengatasnamakan marketplace, lengkap dengan ancaman akun diblokir dan permintaan kode OTP. Kedua, pembeli gadungan yang mengirim screenshot bukti transfer lalu mendesak penjual mengirim barang sebelum uang masuk. Korbannya hampir selalu sama: pelaku UMKM yang panik dan tidak sempat berpikir. SAPA lahir dari masalah itu. Nama panjangnya Scam Analysis and Protection A...