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Siliconangle

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New Sentry logging feature adds structured logs to error tracking workflow

Sentry Inc. introduced a new logging feature in open beta for JavaScript and Python applications.
The feature integrates structured logs into error and performance monitoring workflows for a more unified debugging experience.
Logs are automatically associated with related issues and traces, enhancing root cause analysis and reducing context switching between tools.
Future plans for the feature include log-based alerts, visual dashboards, live log tailing, and expanded support for additional SDKs.

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Logrocket

324

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Building an agentic AI workflow with Ollama and React

Building agentic AI workflows with Ollama and React allows for cost-efficient, private, and reliable AI processes by running local models like Llama 3, Gemma 3, and DeepSeek R1 seamlessly.
The evolution of AI applications has transitioned from rule-based systems to machine learning and neural networks, leading to the development of Large Language Models (LLMs) based on transformer models.
LLMs enable tasks like advanced chatbots, content generation, and question-answering systems, with some LLMs capable of proactive problem-solving and agentic workflows.
Agentic workflows involve autonomous planning, reasoning, and adaptive capabilities, allowing AI agents to dynamically change strategies based on feedback and information.
Key components for effective AI agents include perception, reasoning and planning, memory management, and action implementation.
Using local models like Ollama offers enhanced data privacy, reduced operational costs, offline support, and improved performance for agentic AI workflows compared to cloud-based solutions.
Ollama simplifies running various LLMS on a machine, providing CLI and API access to download and serve models like Llama 3, Mistral, and Gemma for different AI tasks.
Setting up Ollama involves downloading the installer, pulling models from the library, and running models via commands on the local machine to interact with the AI systems.
A demo travel planner app showcasing agentic AI capabilities is built using Gradio and React, highlighting the balance between rapid development with Gradio and advanced scalability with React.
Other AI agent frameworks like Semantic Kernel, LlamaIndex, LangGraph, Rasa, Hugging Face Transformers, and more offer unique features for developing intelligent, context-aware agents.
Utilizing local models with tools like Ollama in conjunction with React frontends presents a powerful approach to creating robust, user-friendly AI applications with enhanced privacy and performance.

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Logrocket

392

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3 case studies of why speed isn’t always best for your product

In the realm of product development, speed is often celebrated, but excessive speed can lead to long-term issues such as technical debt, bad user experiences, and team fatigue.
Three case studies are explored to showcase the effects of speed: Sonos faced a $500 million loss due to rushed app updates, Osborne Computer Corporation suffered from the 'Osborne Effect' after leaking future product plans prematurely, and Apple thrived by prioritizing deliberate pacing and perfectionism.
The desire for speed in product development stems from competitive pressure, investor expectations, user demands, and lean development principles.
Moving too fast can result in technical debt, compromised user experience, and a lack of strategic thinking, leading to longer delays and higher costs.
Rushed product development can cause a product to lose trust and credibility, as well as lead to feature creep and unreliable direction changes.
Companies like Sonos and Osborne Computer Corporation experienced significant setbacks due to prioritizing speed over sustainability in product development.
Apple's deliberate and methodical approach to product launches, emphasizing quality over speed, has contributed to its success and user trust.
Balancing speed and sustainability requires careful execution, appropriate prioritization, incremental development, scalability design, and fostering a positive workplace culture.
Striking the right balance between speed and sustainability is crucial for achieving long-term growth and success in product development.
Speed in product development can be a double-edged sword, where rapid iteration is beneficial but undue haste can lead to detrimental consequences; thus, moving strategically is key.

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Medium

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Search, Click, Earn: Turning Your Everyday Internet Habits into Income

Traditional search engines benefit from advertising, but new platforms share revenue with users based on their searches and clicks.
Ways to earn from internet searches include using alternative engines with reward programs, browser extensions/apps, and 'Paid-to-Search' websites.
Earnings are modest (in cents per search) but can accumulate over time with frequent searching, appealing to various user demographics.
Tips for earning from searches include researching reputable platforms, understanding payout thresholds, prioritizing privacy, and considering personal search habits.

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Medium

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Jules, Google’s GitHub Copilot

Jules is Google's AI coding assistant with an octopus mascot, similar to GitHub Copilot and Clippy.
Jules is designed to assist programmers in rewriting code by integrating with GitHub and handling code fixes or features quickly.
Created by a Google engineer, Jules is meant to symbolize multitasking and efficiency with its eight virtual arms and energetic octopus mascot.
The AI coding assistant aims to make programmers question their existence while providing support in navigating through buggy codebases.

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Macrumors

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Apple's Swift Powers the New Things 3 Cloud System

Popular task management app Things 3 has revamped its cloud backend using Apple's Swift programming language.
Transition to the new Swift-based infrastructure occurred seamlessly with no disruption to users.
The new system has brought significant performance improvements in terms of handling traffic peaks and reducing compute costs.
The legacy system built with Python 2 and Google App Engine was replaced to overcome challenges like rising infrastructure costs and slow response times.

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Dev

397

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Entrance Exams, Top Colleges and Career Options

Top 5 Engineering Entrance Exams 2024 outlined for aspiring engineers in India.
Importance of structured exam preparation highlighted for various fields like Engineering, Medical, Law, Indian Navy, Fashion Designing, etc.
Details of All India Entrance Examination for Design (AIEED) after Graduation 2024 provided, emphasizing its significance for aspiring designers.
Eligibility criteria, exam format, and career opportunities post AIEED discussed for those interested in fashion, interior, and product design careers.

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Dev

157

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🌍 Tourism Management System Project in Java – With Source Code

The Tourism Management System Project in Java provides a real-world application with various features for students and developers to explore Java projects.
It automates and streamlines travel or tourism business operations through modules such as customer information, tour packages, bookings, payments, and admin/user login system.
Key features include user & admin login, tour package management, booking system, date & duration handling, and data storage using Java Swing, Core Java, and text file I/O.
Recommended for students, Java learners, and startup demos, future enhancements can include connecting to a database, making it web-based, developing a mobile version, and adding a dashboard for analytics.

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Dev

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The Future of Work APIs: What Developers Should Know About HR Tech Integration

The workplace is evolving with remote work, hybrid teams, and AI-enhanced HR, making APIs crucial for developers in shaping the future of work.
HR tech APIs are now essential for building smarter integrations, with major players like Workday, BambooHR, Gusto, and Greenhouse offering robust APIs.
Interoperability is key in modern HR tools to ensure adoption, with examples like triggering Slack messages for onboarding and syncing PTO statuses to Google Calendar.
Developers must prioritize security, compliance, context in AI usage, real-time updates, and creating systems that respect human dignity in building HR tech for the future.

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Dev

257

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My Early Python Journey: Small Wins, Big Motivation 🚀🐍

The author shares their early journey with Python, emphasizing the value of celebrating small victories in coding.
The author tackled problems like even or odd number checker, reversing a string, counting vowels, Celsius to Fahrenheit converter, and word count in a sentence.
Through these challenges, the author learned important coding principles and techniques, such as if-else conditions, string manipulation, and input validation.
The author highlights the significance of small wins in building confidence and a strong foundation for tackling more advanced coding challenges.

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Infoq

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Spring AI 1.0 Released, Streamlines AI Application Development with Broad Model Support

The Spring team has released Spring AI 1.0, a framework to simplify AI-driven application development in the Java and Spring ecosystem.
Key features of Spring AI 1.0 include support for various AI models like chat, image generation, and transcription, as well as portable service abstractions and RAG integration.
The framework integrates with major generative AI providers such as OpenAI, Anthropic, and Google Vertex AI through a unified API layer, supporting different model types across modalities.
Spring AI 1.0 also includes Model Context Protocol (MCP) support, dedicated client and server Spring Boot starters, and higher-level APIs for common AI application patterns.

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UX Design

406

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CSS Grid with Galaxy layout: now available in Figma

CSS Grid, a powerful layout system for web, has evolved over nearly two decades and is now available in Figma in 2025.
Using CSS Grid, the author reimagined the Galaxy installation artwork by Korean artist Kim Eull on the web.
Challenges faced in recreating the Galaxy layout precisely in Figma Grid, such as limitations in row and column gaps.
Insights on CSS Grid structure, properties, and values, with a focus on grid-area and grid-template.
Reflections on the process, including implicit vs explicit grids, height in CSS, and the use of fr units for responsive design.
Resources and demos showcasing the diverse possibilities of CSS Grid beyond basic layouts, encouraging creativity and exploration.
A gratitude note to creators and advocates for CSS Grid resources, with suggestions for further learning and inspiration.
Author welcomes feedback and interactions to improve the article, inviting comments and engagement via Bluesky or LinkedIn.

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Medium

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Why your jwt might be lying to you and how to make it tell the truth

JWTs (JSON Web Tokens) have gained popularity but are often misunderstood and misused, posing security risks if not handled carefully.
JWTs are compact tokens made of three base64-encoded parts, easily decodable, and prone to security vulnerabilities if not securely verified.
Common mistakes with JWTs include using long expiration times, accepting alg: none in the header, and failing to verify signatures.
Developers should always verify the signature, claims, and context of JWTs before trusting them for authentication.
Best practices include using short-lived access tokens, storing refresh tokens securely, and never transmitting JWTs over plain HTTP.
It's crucial to validate JWTs properly, rotate secrets periodically, and implement measures like rate limiting and IP filtering for enhanced security.
JWTs do not automatically expire on logout, requiring manual revocation of tokens to ensure security.
Understanding common pitfalls like not verifying signatures and trusting decoded JWT content is essential for secure authentication implementation.
JWTs offer stateless authentication benefits but require careful handling and verification to prevent security breaches.
It is emphasized that JWTs are not inherently flawed, but improper implementation can lead to vulnerabilities.
When using JWTs, developers should prioritize security practices, robust verification, and proactive measures to safeguard against common attack vectors.

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Dev

401

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🚀 Meet ApolloAgent: The Code Assistant I Built So I’d Stop Talking to Myself

ApolloAgent is a terminal-based AI code assistant developed by a programmer as a side project.
The project serves as a proof of concept for learning about implementing an AI agent from scratch and exploring various features.
The main file 'chat_operations.py' handles prompts, tool calls, function results, and fallback responses.
Future plans for ApolloAgent include adding voice input, Docker support, and a sarcastic mode.

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Dev

180

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Why Everyone’s Building AI Apps, and No One’s Fixing the Old Ones

The tech world is immersed in the AI era with startups rapidly developing AI-powered applications while neglecting legacy systems filled with technical debt.
The allure of innovation, financial incentives favoring AI projects, and the invisible nature of technical debt contribute to the focus on new AI apps over old system maintenance.
Neglecting legacy systems for AI apps leads to reliability issues, security risks, scalability challenges, developer burnout, and negative customer impact.
AI tools can ironically help address technical debt by analyzing code quality, automating refactoring, managing dependencies, generating documentation, and predicting maintenance needs.
Real-world examples illustrate the consequences of ignoring technical debt, such as retail system crashes, SaaS scalability failures, and healthcare security breaches.
Strategies for balancing AI innovation and technical debt include prioritizing high-impact debt, allocating maintenance time, integrating AI tools, incremental refactoring, educating stakeholders, leveraging quiet AI, and hiring maintenance specialists.
The future of technical debt in the AI era may involve AI-driven refactoring agents, predictive debt management, standardized maintenance frameworks, and balanced budgets for innovation and maintenance.
AI tools offer a solution to address technical debt, emphasizing the importance of maintaining legacy systems alongside building innovative AI applications to ensure the stability and longevity of technology infrastructures.
Developers are encouraged to balance the excitement of AI innovation with the necessity of maintaining older systems to prevent costly outages, breaches, and operational disruptions.
Prioritizing maintenance and leveraging AI tools can help companies navigate the challenges posed by technical debt, ensuring a sustainable approach to technological advancement.
Maintaining legacy systems is crucial in parallel with developing AI applications, highlighting the need for a balanced approach to technology innovation and system upkeep.

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