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Hi, my name is Ilia. I founded Perfect Wiki — a SaaS product for creating internal company knowledge bases that works directly within Microsoft Teams. We created a simple and convenient tool for storing, editing, and sharing knowledge within companies. It all started with the idea to resolve one specific pain point: the built-in Wiki in Microsoft Teams offered was inconvenient, and there was no worthy alternatives with full integration to the platform.

In this article, I want to share how the idea came about, the mistakes I made, how I found my first customers, and how I gradually grew to a steady income of $250,000 a year over five years. All of this — without investors, a 20-person team, or a “Series A” round.

Hi to everyone!

I'm new here. Someone told me that Habr is like russian reddit for developers (and maybe not). And I'm here today to share my story and get opinions from you, part of this community.

In August 2024 I visited Moscow, and got Russian starter pack, even if foregneir :-)
Will be useful later because I'm moving here, Русский язык coming soon, извините!

So let's start with getting a new bank account, make a new mobile number and start to register to some essential service platforms like Metro, Gorod, ВВ, Perekrostak and Yandex for delivery and taxis. And in every service I found something strange. A certain "Ivan" (I've changed the name for privacy) is present in all my accounts where I try to register.
That's it! The phone number that my bank gave me was just.... recyled! So I could start to get personal data through all these existing account on this new phone number of mine but the most shocking thing occured today!

Alarm on 9:00, I woke up and I got a message by Yandex:

If your code has many nested executions of stored procedures, you can benefit from building popular "flame diagram" of the execution time which is de facto standard for performance profiling.

Postgres Pro Enterprise 17 introduces major improvements in performance and scalability. The key feature of this new release is the proxima extension, which combines connection pooling, proxying, and load balancing within the database core. Developers also gain improved tools for managing message queues, optimizing queries, enhancing security, and utilizing smart data storage. Want to know how these and other features can impact your applications and simplify database administration?

This article provides a brief overview of the release, accompanied by the links to more detailed information.

Automation can be an exhilarating, albeit exhausting, journey‑especially for those just dipping their toes into it. The tasks are often labeled as “interesting” or “non‑standard,” which, let”s be honest, often translates to “challenging” or even “impossible.” Among these challenges, one question halts around 50% of novice automators in their tracks: How to bypass CAPTCHA!

In the world of blockchain, where the word "gas" is most often associated not with gas stations, but with fees for transactions in Ethereum, the search for ways to minimize these costs is becoming increasingly relevant. Less heartache for an empty wallet and more time to solve really important issues... for example, what to cook for lunch =)

Similar to the epic Batman vs Superman battle, compare GSN and Account Abstraction. As in any superhero story, each of them has its own unique abilities and disadvantages, which we will look at in detail.

Wilhelm Röntgen discovered X-ray November 8th 1895, when he did experiments with cathode rays in a vacuum tube. To capture and save images of the shadows from the X-rays, he used ordinary photoplates. Fortunately, sensitive to visible light silver based photoemulsions turned out to be sensitive to the X-ray too. These photoplates became the first X-ray detectors.

More than 100 years of scientific progress led to the creation of a number of various detectors for recording X-ray images. Developments of the microelectronics and semiconductor manufacturing technologies are crucial for development of the modern X-ray detectors. These detectors can transform the energy of the X-ray photon directly to the electrical signal. They allow capturing detailed, digital, high-resolution X-ray images.

Digital images are easy to work with. For example one can merge multiple macro images into an image of the whole object and represent monochrome images in false colors like Simon Procz did with this X-ray image of a flower he did in 2012.

Hey! My name's Kirill Ziborov and I'm a member of the Distributed System Security team at Positive Technologies. In this article, I'll be continuing the discussion of methods and tools for the formal verification of smart contracts and their practical application to prevent vulnerabilities. The main focus will be on the deductive verification method, or more precisely, the ConCert framework for testing and verifying smart contracts.

Kata Containers is actually now the main way to run containers in an isolated virtual machine for greater security. I tell you how to install them for use with Containerd and Docker while still being able to switch between release versions.

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 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.

The students of the Intelligent Systems Department successfully defended their bachelor’s and master’s theses. This year, 14 Bachelor’s and 8 Master’s students earned their degrees in Physics, Mathematics, and Computer Sciences. We are proud to say that our Department is unique in publishing the complete set of defense materials during the last ten years. These materials include the text of the dissertation work, the published papers, the code of the computational experiments, and the slides with video of the defense talk.

In this post, we gladly summarize the defended works of our BS and MS students and highlight the results. A recording of their pre-defence presentations can be found here and here in Russian. Most part of the theses has a publicly available English version. 

An Integrated Approach: Philosophical Barriers to Creation and Practical Methods for Detecting Subjectivity in Artificial Systems (from modeling AI consciousness to diagnosing it)

Complex systems often appear chaotic or incomprehensible, yet closer examination reveals that such complexity can frequently be reduced to a simple underlying mechanism. By systematically removing layers of emergent behavior, one can uncover a fundamental rule or equation from which the entire system originates.

For years, we’ve studied Oracle to make PostgreSQL a more migration-friendly option. We introduced tools similar to SQL profile and SQL plan baseline as AQO and sr_plan extensions. In some cases, PostgreSQL even outperforms Oracle, especially in automatic re-optimization.

Migrations from Oracle to PostgreSQL are usually smooth performance-wise, and we’ve even developed session variable extensions to make the transition easier. While many enterprise-only features exist, PostgreSQL often integrates popular solutions directly into the core.

In this tutorial, I’ll explain in simple terms what AI, AI agents, and workflows are, and then I’ll walk you through building your very first AI agent in Python using Google’s Agent Development Kit (ADK). By the end, you’ll understand the differences between these concepts and have a working content-assistant agent you can run from your terminal or a web interface.

Admit it, how many times have you wanted to quickly create an image for a post or presentation, but instead got stuck in an editor or endless searches for a suitable image on Google? Wouldn't it be great if the picture in your head could just appear instantly? Time is money, inspiration is on pause, and that's where AI comes to the rescue. Neural networks can generate anything you want, including the craziest ideas. No need to spend hours searching when, with a few clicks, you can see what was in your thoughts just a second ago.

By the way, notice the cover with the dinosaur? Let's call him Rex. Rex is himself a product of neural network creation. Today he'll be the main star of our experiments. But what will we do? Remember I mentioned crazy ideas? Well, to understand all the possibilities of generation, let's give AI a difficult task. We'll send Rex somewhere in space, for example to the Moon, let him put on a spacesuit and and have him grill some barbecue with Earth in the background. Interested? Then buckle up, we're heading into the world of image generation.

Historically, we’ve ended up using a few rather obscure PHP extensions—written and barely (if at all) maintained by their original authors—that aren’t available in standard Debian package sources.

We stick to the principle of “do it right, and it’ll work right,” which means Slackware-style dropping binaries into the system outside of package managers is frowned upon.

So instead, we’ll be building proper .deb packages for PHP extensions—without breaking compatibility with the existing environment.

A lot of people around me spend time trading on the stock market. Some trade crypto, some trade stocks, others trade currencies. Some call themselves investors, others call themselves traders. I often see random passersby in various cities and countries checking their trading terminals on their phones or laptops. And at night I sometimes write analytical or backtesting software—well, I did up until recently. All these people share a common faith and a set of misconceptions about the market.

We are a brokerage platform operating in a dynamic and complex domain. This specificity comes with a set of challenges. On the one hand, it entails a high variability of scenarios and potentially significant risks associated with errors. On the other hand, it has short development iterations with frequent delivery cycles. 

In this article, we will share how we maintain the quality of our numerous backend services, which provide essential information to our trading terminals.