News Aggregator

Stop React Native Crashes: A Production-Ready Error Handling Guide

Aggregated on: 2025-10-10 15:10:46

You are demonstrating your next mobile application idea to investors, and suddenly the application crashes. Now you are clueless whether it crashed due to bad WIFI at the venue, your service is down, or your application itself hit a snag. There are no logs or alerts to tell you what just happened. Mere imagination of this scenario can send any founder or developer into panic and nervousness. Therefore, having robust error handling is critical to modern-day mobile applications. React Native has become an industry standard in building cross-platform native mobile applications. React Native boasts a rich ecosystem of error handling at various levels of architecture. However, often projects lack clear guidelines on how to handle various error scenarios. This results in either overdoing or underdoing error handling in otherwise robust and feature-rich applications. In this article, you will learn how to adopt a three-layer error handling mechanism, which is gaining widespread popularity with major enterprise-level applications built at leading companies. The article will give you a practical guide instead of pure theory, so you are ready to adapt these concepts immediately.

Fixing a Test Involves Much More Than Simply Making It Pass

Aggregated on: 2025-10-10 14:10:46

Software tests are essential mechanisms in the development lifecycle designed to verify that code behaves as expected. They catch bugs, ensuring functionality aligns with requirements, and maintain overall system reliability through automated assertions on inputs, outputs, and states. However, fixing a failing test extends far beyond merely adjusting it to pass, as this superficial approach can mask deeper issues in the underlying code or architecture. True resolution demands a thorough investigation into the root cause. It could be a logic error, an environmental mismatch, a dependency failure, or an outdated assumption in the test itself, followed by targeted corrections that preserve the test's intent as a safeguard against regressions. Blindly modifying assertions to match unexpected outcomes, such as changing an expected value from false to true without validating why the discrepancy occurred, risks introducing false positives, eroding trust in the test suite.

AI-Assisted Kubernetes Diagnostics: A Practical Implementation

Aggregated on: 2025-10-10 13:10:46

Kubernetes troubleshooting follows a repetitive pattern: identify unhealthy pods, examine descriptions, review logs, analyze events, and correlate information to find root causes. For common issues like CrashLoopBackOff, ImagePullBackOff, or OOMKilled pods, engineers repeat the same diagnostic steps daily, sometimes dozens of times per week in busy production environments. The traditional workflow requires running multiple kubectl commands in sequence, mentally correlating outputs from pod descriptions, container logs, event streams, and resource configurations. An engineer investigating a single failing pod might execute 5–10 commands, read through hundreds of lines of output, and spend 10-30 minutes connecting the dots between symptoms and root causes. For straightforward issues like memory limits or missing images, this time investment yields solutions that follow predictable patterns.

Building Realistic Test Data in Java: A Hands-On Guide for Developers

Aggregated on: 2025-10-10 12:10:46

There’s something that every backend or API developer faces sooner or later: the need for good fake data. Whether you’re testing a new API, populating a database for demos, or simply trying to make your unit tests less “boring”, fake data is part of your daily routine. The problem? Most fake data feels… fake. You end up with “John Doe” and “123 Main Street” repeated over and over, which doesn’t look great when showing a prototype to your team or client.

Securing HTTPS From the Inside Out: Preventing Client-Side Interception Attacks

Aggregated on: 2025-10-10 11:10:46

Overview HTTPS is the most common mechanism used to protect client-server communication on the internet. Most teams focus on SSL/TLS and server-side hardening — and for good reason — but security is layered: the system is only as strong as its weakest link. This article focuses on a specific class of HTTPS man-in-the-middle (MITM) attacks that is not widely discussed. The aim is to harden one of the weaker links in many deployments. If you believe it’s perfectly safe to use a banking site over HTTPS on a device that isn’t yours (a friend’s laptop, an office machine), please read on.

Popular DevOps Automation Tools

Aggregated on: 2025-10-09 19:10:45

DevOps automation tools streamline the path from idea to deployment by turning repetitive, error-prone steps into reliable, repeatable workflows that reduce toil and shorten mean time to recovery (MTTR). This article walks through five categories of DevOps automation tools. Expanding your tool stack thoughtfully is less about quantity and more about reducing change failure rate and increasing deployment frequency in a safe way.

Using LLMs to Automate Root Cause Analysis in Incident Response

Aggregated on: 2025-10-09 18:25:45

Executive Summary In today’s complex cloud and microservices-based systems, it’s no surprise that things break. While we’ve made huge strides in detecting issues quickly with modern observability tools, getting to the actual root of a problem — what really caused the incident — is still a tough, manual, and time-consuming task. That’s where large language models (LLMs) step in. These AI models are trained to understand logs, alerts, documentation, and natural language — all of which are crucial during incidents. By tapping into the power of LLMs, teams can significantly speed up root cause analysis (RCA), reduce downtime, and even lay the foundation for self-healing systems.

Evaluating LLM-Powered Voice Assistants: A Guide Beyond Traditional Metrics

Aggregated on: 2025-10-09 17:10:45

Voice assistants have evolved from being simple, rule-based systems to advanced conversational agents driven by large language models (LLMs). Early versions of voice assistants could only handle specific tasks with pre-defined commands. In contrast, modern LLM-powered assistants can now engage in long and open-ended conversations, follow complex instructions, and perform multi-step reasoning. These improved capabilities bring new evaluation challenges. Traditional metrics like intent classification accuracy, slot-filling accuracy/recall, and goal completion rates can no longer capture the overall quality of a voice assistant. Assistant responses can sound fluent and plausible, even when they contain factual errors or unsafe content. For example, an LLM assistant might correctly identify a user’s request to “find Italian restaurants” (intent) and extract the location “downtown” (slot), but then respond with a restaurant name that doesn’t even exist. Traditional benchmarks would mark the intent/slot task as successful, without accounting for the factual error. Therefore, new metrics and techniques are needed to assess factuality, safety, reasoning ability, instruction following, and user experience.

Building a Supply Chain Digital Twin Technology

Aggregated on: 2025-10-09 16:10:45

About Supply Chain Supply chain means that the entire system is involved, from the producer to the customer. This process involves producing and delivering a product or service to the customer. It includes all the methods, systems, organizations, people, activities, information, and resources. The following are some of the steps involved in the supply chain:

How GenAI Can Eliminate SME Bottlenecks in Enterprise Systems

Aggregated on: 2025-10-09 15:25:45

In large-scale enterprises, tribal knowledge often stalls developer productivity and slows operational agility. Subject matter experts (SMEs) become bottlenecks when critical business logic and configuration decisions live only in legacy codebases or in the minds of a few veterans. This article presents an architecture that leverages GraphCodeBERT embeddings, FAISS vector search, and large language models (LLMs) like Sonnet or Claude to transform complex enterprise logic into conversational explanations. Drawing on real-world use cases in asset lifecycle processing and internal platform operations, it outlines a scalable, GenAI-driven approach to overcoming SME bottlenecks and accelerating engineering velocity.

Low Code, High Impact: A Solution Architect’s Guide to Building Scalable Community Platforms With AI and Low-Code Tools

Aggregated on: 2025-10-09 14:10:45

As a solution architect, I’ve spent most of my career building massive enterprise systems — cloud-native platforms, scalable APIs, and robust infrastructure. So when I took it upon myself to build a digital hub for our Chhath Puja community in Southern California, it was a refreshing shift from the corporate grind. This time, there was no project team, no IT budget, and no stakeholder meetings. Just me — and the need to launch something meaningful, quickly.

Virtualization Meets Acceleration: Powering AI Workloads

Aggregated on: 2025-10-09 13:25:45

Artificial Intelligence has quickly moved from buzzword to business driver. From chatbots and fraud detection to medical imaging and predictive analytics, AI has found a home in nearly every industry. But as AI evolves, so do the infrastructure demands that support it. Training large models or running real-time inference pipelines isn’t trivial — it takes serious compute, bandwidth, and orchestration. Here’s the good news: most enterprises already have the core building blocks needed for an AI-ready high-performance computing (HPC) environment sitting quietly in their data centers. We're talking about Cisco UCS servers, Cisco network switches, and VMware virtualization — technologies that are already deeply embedded in IT ecosystems across industries.

Efficiently Reading Large Excel Files (Over 1 Million Rows) Using the Open-Source Sjxlsx Java API

Aggregated on: 2025-10-09 12:10:45

If you are a developer, regardless of the technologies you use, at some point, you will face the challenge of handling large Excel files. Most commonly, you will see the "out of memory" error when handling these files.

Theia Deep Dive, Part 2: Mastering Customization

Aggregated on: 2025-10-09 11:25:45

In the first part, we set up the basics: Theia runs in the browser, plugins work, themes and icons load, and we even added a splash screen. That gives us a functional IDE, but it’s still pretty close to stock. This part is about shaping it into our own product. We’ll start by stripping out what we don’t need, then adjust the UI and wire up contributions so the editor feels focused and intentional.

The Top 20 Problems With Batch Processing (and How to Fix Them With Data Streaming)

Aggregated on: 2025-10-08 19:25:45

Batch processing has long been the default approach for moving and transforming data in enterprise systems. It works on fixed schedules, processes data in large chunks, and often relies on complex chains of jobs that run overnight. While this was acceptable in the past, today’s digital businesses operate in real time — and can’t afford to wait hours for fresh insights. Delays, errors, and inconsistencies caused by batch workflows lead to poor decisions, missed opportunities, and growing operational costs. In this post, we’ll look at common issues with batch processing and show why data streaming is the modern alternative for fast, reliable, and scalable data infrastructure.

Strapi v5: Customization Nuances

Aggregated on: 2025-10-08 18:25:45

Strapi is an open-source headless CMS. The library allows integration with external databases, the implementation of custom controllers, and customization of the UI to match a project's branding. According to GitHub, around 30,000 developers use Strapi CMS in their projects. This article is primarily aimed at developers who work with or plan to integrate Strapi CMS into their applications.

Theia Deep Dive, Part 1: From Zero to Your Own IDE

Aggregated on: 2025-10-08 17:25:45

Intro: Why Build Your Own IDE? There are countless reasons to create your own IDE. Perhaps you are creating a sandbox similar to CodeSandbox, but adapted to your own framework. Or an Arduino-style environment where a strictly controlled user interface is required for flashing firmware and interacting with hardware. Maybe your SaaS product needs a built-in cloud editor. Maybe you're creating an educational platform where users should only see part of the code. Or you're releasing your own language or framework, and want the developer tools not to look like an add-on plugin. Or maybe you've decided to create your own Cursor with an AI assistant. Whatever your goal, creating your own IDE is more than possible. In this guide, I'll show you how to do it with Eclipse Theia: a fully modular, open-source platform designed to adapt to your needs.

Converting ActiveMQ to Jakarta (Part III: Final)

Aggregated on: 2025-10-08 16:25:45

Advanced Technical Approach Some Java frameworks have taken on the complexity of supporting both javax and jakarta package namespaces simultaneously. This approach makes sense for frameworks and platform services, such as Jetty and ActiveMQ, where the core development team needs to move the code base forward to support newer JDKs, while also providing a way for application developers to adopt Jakarta EE gradually. This simplifies the support for open-source frameworks, as there are fewer releases to manage, and in the event of a security bug, being able to release one mainline branch vs having to go back and backport across past versions. However, supporting both javax and jakarta namespaces simultaneously in a single application is complicated and time-consuming. Additionally, it opens additional scenarios that may lead to errors and security gaps for enterprise applications. This limits the ability to set up verification checks and source code scanning to block pre-Jakarta libraries from being used or accidentally pulled in through transitive dependencies. It creates a lot of ambiguity and reduces the effectiveness of DevOps teams in providing pre-approved SDKs to be used by enterprise developers. With the pitfalls outweighing the benefits, enterprise projects should not need to support both javax and jakarta namespaces simultaneously in most scenarios.

Transforming Your Node.js REST API into an AI-Ready MCP Server

Aggregated on: 2025-10-08 15:25:45

The evolution of large language models (LLMs) and agentic AI requires a fundamental shift in how applications expose their capabilities. Traditional REST APIs are designed for software-to-software communication, requiring developers to read documentation and write custom integration code. The Model Context Protocol (MCP) is an open standard designed to solve this by creating a unified, machine-readable interface that AI agents can dynamically discover and interact with. This article provides a comprehensive guide on converting an existing Node.js REST API into an MCP server using the official TypeScript SDK, focusing on the architectural changes and crucial use cases that this conversion unlocks.

When Offline Still Matters: Why Some Mobile Apps Work Without Wi-Fi — and Others Don’t

Aggregated on: 2025-10-08 14:25:45

Ever been stranded with no Wi-Fi and suddenly discover that your go-to app is useless? You're sitting on a delayed flight, stuck in the middle of a subway tunnel commute, or out camping in some serene spot (but signal-less), and you fire up that one app you use every day, only to be greeted by an error message. "No internet connection." Brilliant.

Golden Paths in IDPs: From Developer Chaos to Clarity

Aggregated on: 2025-10-08 13:25:45

A new team spins up a service. They wire together a CI pipeline, stitch in some Terraform for infrastructure, and maybe — remember to add monitoring. Another team does the same, but with different tools, different conventions, and different assumptions. Fast forward a few months, and what was once a fast-moving engineering org is now struggling with undocumented know-how, snowflake pipelines, and production incidents caused by inconsistent practices. Developers spend more time debugging environments than delivering features. Platform teams are stuck firefighting, trying to enforce standards that retroactively were never embedded in the first place.

8 Challenges in Multimodal Training Data Creation

Aggregated on: 2025-10-08 12:25:45

Multimodal AI processes multiple forms of data, like images, sounds, and words, all at once, to empower your applications to not just listen to our voice or read text but also pick up facial expressions and the details around us. This technology is rapidly making our daily interactions easier and natural, and when using applications with which you can communicate, it feels almost as if you are chatting with your friends. The first multimodal large language model that handled both text and images effectively was GPT-4 in 2023. The most recent multimodal model, GPT-4o Vision, is equipped to create interactions that are incredibly lifelike.

The Agile AI Manifesto

Aggregated on: 2025-10-08 11:25:45

TL;DR: The Agile Manifesto Predicted AI The Agile world is splitting into two camps: Those convinced AI will automate practitioners out of existence, and those dismissing it as another crypto-level fad. Both are wrong. The evidence reveals something far more interesting and urgent: Principles written in 2001, before anyone imagined GPT-Whatever, align remarkably well with the most transformative technology of recent years. This is not a coincidence. I believe it is proof that human-centric values transcend technological disruption; it is the Agile AI Manifesto. The Broken Debate Walk into any Agile community event today, and you will encounter two opposing camps, each equally confident and equally wrong:

Pattern Searching and PostgreSQL Full-Text Search: Understanding the Mismatch

Aggregated on: 2025-10-07 19:25:45

A while ago, a request emerged to implement a global find functionality in one of our products. Briefly, the purpose was to be able to search for multiple (different) entities by a pattern that is looked up and matched against several of their attributes. Not very complicated at first glance, such a feature comes with a lot of concerns and trade-offs that need to be analyzed, in addition to the implementation itself, in order to ensure at least a pleasant user experience. As the underlying database was PostgreSQL and I was aware of its powerful full-text search (FTS) capability, I considered it a potentially good candidate, so I started researching it, trying things out, aiming to compile the solution around it. Unfortunately for the requirement, but fortunately for me and for the interesting FTS capabilities I became aware of during this study, a few hours later, I understood why it cannot be used for pattern searching.

Building Cost-Effective Internet Scale Applications

Aggregated on: 2025-10-07 18:25:44

As developers, it is important that when we build an application, we design keeping both its targeted scale and the cost of running it in mind. If we are building an internet-scale application that could start from zero traffic on day one and gradually achieve a scale of millions of daily users, we have to choose a design and set of tools that can scale in a similar fashion. This is easier said than done. Developers usually over-provision in anticipation of higher traffic and end up paying larger costs than they could have managed without. Following an appropriate design and the right choice of technologies can make a huge difference. In this article we will take a look at various serverless technologies offered by cloud providers and focus on AWS as a reference to discuss how we can build a fairly common kind of application which involve front end, backend and a database that could be blazingly fast, while if designed well could cost you zero in your monthly bill to start with and eventually scale as your user base scales.

Why Incomplete Documentation Is a Security Vulnerability in SaaS

Aggregated on: 2025-10-07 17:25:44

Many SaaS teams pay more attention to encryption, firewalls, and compliance checks. They often overlook an essential asset: documentation. Documentations may not be as exciting as a new firewall or security tool. However, unclear, outdated, or incomplete setup guides, API references, and internal runbooks can lead to security gaps.

Building a Production-Ready Conversational AI Agent With Cloudflare Workers and AI Gateway

Aggregated on: 2025-10-07 16:25:44

Conversational AI is fundamentally transforming customer support, delivering instant, context-aware responses at a massive scale. With the global conversational AI market projected to reach $32.6 billion by 2030, growing at a CAGR of 23.6%, developers need efficient ways to deploy these powerful tools. Edge computing platforms like Cloudflare Workers and AI Gateway provide the ideal solution, enabling the deployment of low-latency, serverless AI agents without the complexity of managing infrastructure. This tutorial provides a comprehensive guide to building a production-ready chatbot. We will use Cloudflare Workers for the serverless backend, AI Gateway to manage and route model inference, and Tailwind CSS for a clean, responsive frontend. The result is a context-aware customer support agent powered by a high-performance large language model like Llama 3.1.

Dynamization of Static Data Structures

Aggregated on: 2025-10-07 15:25:44

Most of us in software engineering have been there. You design a static data structure that supports blazing-fast queries for counting elements, searching patterns, or similar tasks. However, the moment you need to support insertions, performance collapses because rebuilding from scratch after every update is too slow. If you're lucky, you might find (or invent!) a different data structure which:

Master Developer Writing: From Docs and Pull Requests to Blog Posts

Aggregated on: 2025-10-07 14:25:44

Developers are natural problem-solvers. We think in systems, patterns, and code. But one of the most underrated skills in a developer's toolkit has nothing to do with code; it’s writing. According to Atlassian’s 2025 State of DevEx report, developers lose an average of six hours per week due to poor documentation and organizational inefficiencies. That’s despite AI helping with productivity. The real bottleneck? Communication. Whether it’s in documentation, pull requests (PRs), or blog posts, writing well accelerates engineering velocity and makes teams better.

Booleans vs Integers in Databases: Understanding the Trade-Offs

Aggregated on: 2025-10-07 13:25:44

When designing a database, developers often encounter a seemingly simple decision: Should we use a boolean or an integer to represent a (decision) field? While the difference might seem trivial at first, the choice can have significant implications for storage, maintainability, and scalability. Let’s explore the pros and cons of each approach, with a focus on storage size, operational overhead, and long-term maintainability. Booleans: The Simple, Binary Option Initial Design A boolean field is ideal when a value can only have two states: true or false. For example, fields like isActive or isAdmin fit perfectly into that. Here’s a typical example:

Smart Choices Between Inter- and Intra-GPU Communication

Aggregated on: 2025-10-07 12:25:44

Why the Way GPUs Talk to Each Other Matters Imagine you’re back in school, working on a group project. Everyone in the group is smart and capable, but the project keeps dragging. Not because people don’t know the answers, but because they waste time passing notes around or waiting for someone else to finish. That’s exactly what happens with GPUs. These processors are incredibly powerful, but the way they communicate — both inside a single GPU and across multiple GPUs — determines whether your workload flies or crawls. Prerequisites: The Building Blocks Before we get into how GPUs share data, let’s cover the key pieces you need to understand.

Who Governs Your NHIs? The Challenge of Defining Ownership in Modern Enterprise IT

Aggregated on: 2025-10-07 11:25:44

"Ownership" is one of the harder concepts to define in the modern enterprise. This feels deceptive because, from a personal and human level, ownership is a rather straightforward concept. When you own something as a person, like your car or your house, you control it completely, and you're accountable when things go wrong. Ownership means something fundamentally different for individuals than it does for enterprises, especially when we're talking about non-human identities (NHIs).

Playwright for Real-Time Applications: Testing WebSockets and Live Data Streams

Aggregated on: 2025-10-06 19:25:44

Real-time applications are everywhere these days. From chat apps to stock dashboards and collaborative tools, users expect instant feedback. If you’ve ever tried to test these apps, you know the challenge: traditional automation just doesn’t cut it. The page doesn’t reload, elements appear and disappear unpredictably, and multiple users can interact simultaneously.

Hyperparameter Tuning and Feature Engineering: A Guide to Optimizing Machine Learning Models

Aggregated on: 2025-10-06 18:25:44

Unlocking maximum performance from machine learning (ML) models rarely comes down to modeling choices alone. Far more often, excellence rests on how well one tunes hyperparameters and how deftly one engineers features. These processes-the quiet backbone of practical machine learning-are where the gap between acceptable and outstanding results is made or lost. This guide explores actionable strategies and decision frameworks for both, showing experienced developers and ML leads how targeted optimization can drive tangible business outcomes. Why Model Optimization Matters: Impact on Outcomes Building a machine learning model is relatively straightforward. Ensuring that the model is reliable, performant, and cost-effective in real-world environments is not. Under-optimized models carry hidden costs: wasted compute, poor user experience, biased or unstable predictions, and missed commercial opportunities. In production, these issues can translate to direct business losses or negative user impact.

Developing Low-Cost AI-Based Similarity Search

Aggregated on: 2025-10-06 17:25:44

The world of artificial intelligence (AI) and large language models (LLMs) often conjures images of immense computing power, proprietary platforms, and colossal GPU clusters. This perception can create a high barrier to entry, discouraging curious developers from exploring the fundamentals. I recently embarked on a project — a sophisticated yet simple AI-powered chatbot I call the Wiki Navigator — that proves this complexity is often unnecessary for learning the essentials. By focusing on core concepts like tokenization, vector embeddings, and cosine similarity, I built a functional RAG (retrieval-augmented generation) search solution that operates across 9,000 documents in the Chromium open-source codebase. It took me a few hours to run, and the next day, I was able to reuse the same codebase to train a chatbot on open-source books about the Rust programming language to have useful help during my Rust learning journey.

Predictable Low Latencies for Apache HBase

Aggregated on: 2025-10-06 17:25:44

Apache HBase Apache HBase is an open-source, strongly consistent distributed database designed to store record-oriented data across a scalable cluster of machines. HBase stores rows of data in tables that can be grouped into namespaces, and a table can belong to only one namespace at a time. Tables are split into groups of lexicographically adjacent rows called regions. By "lexicographically adjacent," we mean that all rows in the table that sort between the region’s start row key and end row key are stored in the same region. Regions are distributed across the cluster, hosted, and made available to clients by RegionServer processes. Regions are the physical mechanism used to shard and distribute the write and query load across the fleet of RegionServers. Regions are also non-overlapping: A single row key belongs to exactly one region at any point in time. Together with the special META table, a table’s regions effectively form a B-tree for the purposes of locating a row within a table.

LangGraph Beginner to Advanced: Part 1 — Introduction to LangGraph and Some Basic Concepts

Aggregated on: 2025-10-06 17:25:44

Welcome to this LangGraph Beginner to Advanced series. LangGraph is one of the most popular frameworks for building agentic AI applications. With agentic AI, the application has a lot more scope and tasks to accomplish by navigating various flows and autonomously invoking various agents to fulfill a task completely. LangGraph is built within the LangChain system to act as an orchestration framework to build a multi-step flow for each task execution. Unlike a linear chain of events that you build with LangChain, with a multi-step flow, the orchestration can have logical conditions that decide which agent to invoke, it can make decisions, use various tools, and maintain the state of the conversation throughout the flow. If you’ve ever wanted to build AI agents and design graph-based conversational workflows, this course-style blog series is for you.

A Brief Overview of Designing and Testing Effective Chatbots

Aggregated on: 2025-10-06 17:25:44

As startups, enterprises, and individuals all around are looking to understand how they can incorporate chatbots into their systems for customer service, internal workflows, and compliance, it is incredibly important to understand how you should design and test these for them to be truly effective. With bigger large language models and tools such as retrieval-augmented generation (RAG) and Model Context Protocol (MCP) all the craze, it is important to understand that if a clear understanding of use case, design, and testing isn't done, these will likely become "black boxes."

Beyond a Single AI Assistant: Creating a Team Chat App Using Spring Boot and LangChain4j

Aggregated on: 2025-10-06 17:25:44

Nowadays, wherever we look, AI chat solutions are everywhere. From customer support bots handling inquiries to personal assistants scheduling meetings, AI-powered conversations have become an integral part of digital interactions. Developers experiment with different models, fine-tuning prompts, integrating memory, or giving assistants unique personalities to enhance user experience. However, most of these solutions follow the same fundamental pattern: a single AI assistant engaging with a human user. If I ask anyone whether a conversation with ChatGPT feels realistic, they’ll likely say yes without hesitation, perhaps adding that it sometimes confidently states incorrect information or struggles with counting the "r"s in "strawberry." Yet the most obvious imperfection, its unwavering willingness to answer every question instantly and politely, rarely raises any eyebrows. A chat interaction between two people is never this effortless and seamless. Many factors influence when and how someone responds. They might be busy with other tasks, waiting for you to clarify your question, or unsure of their own answer. Their response could also depend on their level of interest in the topic, their relationship with you, or even external distractions pulling their attention away.

Developer Journey: Debug Complex Systems With Zero Context

Aggregated on: 2025-10-06 17:25:44

Imagine this: You are a developer who has been tasked with solving a difficult problem that causes revenue loss by the minute. Your managers and leaders have pulled you from your current priorities and asked you to look at the codebase behind a service that is repeatedly running into one of the following severe issues: OOM-ing every day for the past week, crashing intermittently under load, leaking memory over time, or exhibiting performance degradations that only surface in production-scale environments. You are here now and need to solve the problem, but you have no clue what the codebase does. There is some AI-generated documentation you can read, but you can’t fully rely on it. There is no SME on the existing team who has been there from the beginning to help.

Mastering AOSP Bluetooth Debugging

Aggregated on: 2025-10-06 17:25:44

If you’re a Bluetooth system engineer working with AOSP, you already know debugging can get messy. Connections drop, profiles misbehave, and sometimes nothing seems to add up. In those moments, the dumpsys tool should be the first thing you reach for. And when it comes to Bluetooth, no command is more useful than adb shell dumpsys bluetooth_manager. This single command can reveal a wealth of information about the state of the Bluetooth stack on your device. It tells you if Bluetooth is enabled, what profiles are running, whether devices are bonded, and even the state machines inside each profile. In short, it gives you a peek behind the curtain so you can figure out what’s really going on.

Guardrails for AI: Protecting Privacy in Both Prompts and Responses

Aggregated on: 2025-10-06 17:25:44

Large language models (LLMs) like OpenAI’s ChatGPT, Anthropic’s Claude, Google’s Gemini, or Meta’s Llama have taken the world by storm, offering powerful text-generation capabilities for everything from coding help to customer service. But as their use grows, so do concerns about privacy and data protection. In the past year alone, an internal data leak at Samsung prompted the company to ban employees from using ChatGPT [1], and Italy’s data protection authority temporarily blocked ChatGPT nationwide over alleged privacy violations [2]. These incidents underscore a critical point: both what we put into these LLMs and AI systems, and what they output, can pose serious privacy risks.

Why GPT-OSS:20B Feels Painfully Slow (And How Quantization Can Save Your Sanity)

Aggregated on: 2025-10-06 17:25:44

If you are into AI and specifically generative AI, you definitely did not miss the buzz about OpenAI releasing open-source models for the first time since February 2019, and this was with GPT-2. It's like OpenAI has finally brought back the open into play.

Behind the Scenes: How Apps Are Collecting Your Data

Aggregated on: 2025-10-06 17:25:44

Your applications are watching you (even if you’re not looking). These days, it’s hard to imagine life without applications. Whether it’s checking the weather, ordering food, streaming music, or scrolling through the news, they’re always just a tap away. They are fast, friendly, and feel almost invisible in our daily routines. But there’s something else quietly running in the background: data collection. Lots of it and often more than we’d expect or knowingly agree to.

7 AWS Services Every Data Engineer Should Master

Aggregated on: 2025-10-06 17:25:44

If you work in data engineering, you know the job is a constant balance between speed, reliability, and maintainability. It is not enough to just move data from one system to another. You must make sure the process will still work next month, that it can handle more volume next year, and that someone else can understand it without asking you a hundred questions. I have been through years of building ETL jobs, chasing down broken pipelines, rewriting transformations after schema changes, and tuning performance when reports were too slow to be useful. The biggest lesson is that the tools you choose matter more than you think. The wrong choice can lead to constant firefighting. The right one can make the system almost invisible because it just works.

Elevate Customer Engagement by Adding Google Play Instant to Your Android App

Aggregated on: 2025-10-06 17:25:44

Users do not need to install your game or app since Google Play Instant offers an immediate option to access it. This enhances the overall experience for the customer and can greatly increase your app's conversion rates. The possibilities with Google Play Instant are endless. It offers the chance to allow users to try the app or game instantly before they make the full commitment of downloading it. This makes it less intimidating and more encouraging, which leads to an increase in downloads and more engagement in the future. In this article, we are going to show you step by step how you can add Google Play Instant to your Android application. From the very first steps to the intricate details, with our help, you will avoid common mistakes that developers tend to make.

Enhance Development With DevoxxGenie and MCP

Aggregated on: 2025-10-06 17:25:44

Are you interested in adding AI agents to your coding workflow? In this blog, you will learn what MCP agents are and how you can integrate them into your coding workflow. DevoxxGenie will be used, which is a JetBrains IDE plugin supporting AI coding assistance. Enjoy! Introduction Using AI coding assistants can help you during development. One of the available AI coding assistants is DevoxxGenie, a plugin for the JetBrains IDEs. A killer feature of DevoxxGenie is the ability to work with local large language models (LLMs). You can interact with your code and an LLM this way without leaving your local environment, not sharing any code with external providers.

Enabling Risk Management With AI/ML Powered by Cloud Native Data Architecture

Aggregated on: 2025-10-03 13:10:38

Financial crimes are a persistent threat to financial institutions. Financial institutions have to build risk management systems that can detect and prevent malicious activities. The evolution of cloud computing has enabled leveraging computing power for machine learning in risk management functions like anti-money laundering. Risk management in financial institutions will primarily focus on identifying, assessing, maintaining, and monitoring various risks. This is very important to ensure compliance with regulatory requirements and stability of the institution to maintain investor confidence. Each institution will have its own structure and process to define adherence to different types of risk functions. Most of the risk functions will involve the following steps:

Multi-Cloud Infrastructure Challenges and Solutions

Aggregated on: 2025-10-03 12:10:38

The cloud landscape has changed so much, with companies moving to multi-cloud. According to Flexera’s 2024 State of the Cloud Report, 87% of companies are using multiple cloud providers for resilience, cost optimization, and vendor independence. But managing infrastructure across AWS, Azure, Google Cloud, and other providers brings configuration drift, security vulnerabilities, and cost overruns that can overwhelm IT teams.

From Big Data to Agents: My Decade Building Systems

Aggregated on: 2025-10-03 11:10:38

When a Simple Scraper Changed Everything My first “real” task wasn’t glamorous: scrape some data. We all start at the bottom, and scraping is a rite of passage for data engineers — turning unstructured sources into structured signals. That first job taught me a lesson I’ve carried since 2014/15: access to the right data beats cleverness — and the right pattern beats the shiniest tool. Looking back at that moment — and the path since — this article traces how I entered the data world and what changed up to today’s AI revolution.