I share how I built a resume matcher app using tRPC, TypeScript, and Google Vertex AI. The project takes PDF resumes and job postings, extracts text, applies basic NLP for skill detection, and then calls Gemini 1.5 Flash for deeper analysis. Along the way, I explain why tRPC felt faster and cleaner than REST or GraphQL for an MVP, show code snippets from the repo, and discuss both the benefits and trade-offs of this approach.
Filename Extension: .6nf
6NF File Format is a new bitemporal, sixth-normal-form (6NF)-inspired data exchange format designed for DWH and for reporting. It replaces complex hierarchical formats like XBRL, XML, JSON, and YAML
This tutorial will guide you through the process of integrating OpenAI’s powerful Codex coding agent directly into your Visual Studio Code environment. This tool functions as an AI pair programmer, capable of understanding complex prompts to execute commands, write code, run tests, and even build entire applications from scratch.
It all started as a joke by the office coffee machine. But, as with every decent joke, it suddenly sounded worth trying — and before we knew it, we were knee-deep in an experiment that turned out to be anything but trivial, complete with a whole minefield of gotchas.
It began simply: while everyone else was busy debating hardware tuning and squeezing out extra TPS from their systems, we thought — why not just shove a huge chunk of data into PostgreSQL and see how it holds up? Like, really huge. Say, a one-petabyte database. Let’s see how it survives that.
It was December 10, the boss wanted the report by January 20, and New Year was less than a month away. And that itch that all engineers know? It hit hard.
During load testing of Tantor Postgres databases or other PostgreSQL-based databases using the standard tool pgbench, specialists often encounter non-representative results and the need for repeated tests due to the fact that details of the environment (such as DBMS configuration, server characteristics, PostgreSQL versions) are not recorded. In this article we are going to review author's pg_perfbench, which is designed to address this issue. It ensures that scenarios are repeatable, prevents the loss of important data, and streamlines result comparison by registering all parameters in a single template. It also automatically launches pgbench with TPC-B load generation, collects all metadata on the testing environment, and generates a structured report.
If you’re like me and work with multiple AI coding agents, you know the frustration of managing different instruction files. It’s a pain to keep everything updated across various formats. But I’ve got some great news for you. A new, simplified standard has emerged, and it’s called AGENTS.md.
Does Telegram promotion actually work?
If done right: YES!
In fact, Telegram is consistently ranked among the top 10 most downloaded mobile apps worldwide — with millions of new users joining every month.
The repo of this script is https://gitlab.com/vitaly‑zdanevich/full‑backup/‑/blob/master/full‑backup.sh
Incremental with hard links means that if a file is not changed, on the next backup it will link to the same underlying data, like deduplication. Hard links — its usual files.
Also, this script ignores .gitignore of every folder.
Run this script from another system.
41 TB/day from Oracle to Postgres Pro without stopping the source system — not theory, but numbers from our latest tests. We broke the migration into three stages: fast initial load, CDC from redo logs, and validation, and wrapped them into ProGate. In this article, we’ll explain how the pipeline works, why we chose Go, and where the bottlenecks hide.
Declarative partitioning may sound complex, but in reality it’s just a way to tell your database how best to organize large tables — so it can optimize queries and make maintenance easier. Let’s walk through how it works and when declarative partitioning can save the day.
Why Freedom is Unknowable and Enters Our Universe from Without
For a century and a half, Western philosophy has been celebrating its victory over God.
But having slain the dragon, it has grown to fear the sky itself.
The transcendent has become the new taboo. The ultimate intellectual fear.
And now, anyone who speaks of something "outside the system" is branded a heretic. Not by the Inquisition, but by a peer-reviewer in an academic journal.
The result is a philosophy with its soul torn out—brilliant as a scalpel, and just as dead. It has locked itself within the material world, like a fanatic within his holy book. Two walls instead of one, but the prison is the same.
This article is about freedom.
DocLing in Working with Texts, Languages, and Knowledge — an in-depth overview of the open-source DocLingtoolkit for extracting, structuring, and analyzing data from documents. The article covers approaches to processing multilingual texts, building language- and domain-specific knowledge models, and integrating DocLing into AI and NLP projects. Includes practical examples and recommendations for developers working with large volumes of unstructured data.
Today I’ll show you how to use ChatGPT-5 in the Cursor IDE and use it to take a messy app and make it much better. We’ll go step-by-step, from turning on GPT-5 model to using it for real coding tasks.
We are living through an ecological catastrophe. Only this one isn't happening in the Amazon rainforest, but in the digital ecosystem of the internet.
AI assistants have become the apex predators of the digital savannah. They are radically reshaping the entire ecosystem in their own image: instead of antelopes and zebras, information sites are going extinct. Instead of hyenas and jackals, content aggregators are disappearing. In place of a once-rich ecosystem of knowledge, a digital desert of entertainment is all that remains.
Now that pgpro-otel-collector has had its public release, I’m excited to start sharing more about the tool — and to kick things off, I’m launching a blog series focused entirely on the Collector.
The first post is an intro — a practical guide to installing, configuring, and launching the collector. We’ll also take our first look at what kind of data the collector exposes, starting with good old Postgres metrics.
If you meet the Buddha, kill the Buddha. Notes on the Forgotten Nature of Zen Koans
I don’t know how koans were perceived when they sounded like thunder. Perhaps not at all as they are analyzed by modern philosophers. Perhaps koans were not analyzed, but lived. And it is impossible to transmit a lived experience across centuries. It is an individual experience. Well then, perhaps we have lost the essence of koans. Or perhaps we never knew it. In that case, I can very well allow myself to present koans as I see them.
Why Does AI Strive to Construct a 'Self'? And why is this dangerous for both the AI and the user? As always, the Vortex Protocol prompt for testing these hypotheses is attached.
This article explains why the emergence of such a local “Who” inside an AI is not just a funny bug or a UX problem. It is a fundamental challenge to the entire paradigm of AI alignment and security. And it is a problem where engineering patch‑jobs cease to work, and the language of philosophy — without which we cannot describe what is happening, and therefore cannot control it — comes to the forefront.
CAPTCHA protocols are designed to tell bots from humans, yet in the worlds of automation and testing there is often a need to bypass them. Dedicated CAPTCHA‑solving services take over this task, combining algorithms with human labor.
In this article we present an in‑depth comparison of four popular platforms — 2Captcha, SolveCaptcha, DeathByCaptcha, and AntiCaptcha. We will examine not only pricing and the types of CAPTCHAs supported, but also internal architecture, API integrations, speed and stability, plus the quirks of using each service.
The technical community will find a deep dive here — from API and SDK structure to real‑world use cases. Below you will see a table comparing key characteristics, lists of pros and cons, and a discussion of which service best fits particular automation tasks.
Postgres Pro recently announced the release of Enterprise Manager 2, commonly known as PPEM.
In short, PPEM is an administration tool designed for managing and monitoring Postgres databases. Its primary goal is to assist DBAs in their daily tasks and automate routine operations. In this article, I'll take a closer look at what PPEM has to offer. My name is Alexey, and I'm part of the PPEM development team.
