# practical Published articles for practical. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## New Bug-Fix Releases Are Available for MPS Versions 2026.1.1, 2025.3.2, 2025.2.4, and 2025.1.4 DevFeed: [New Bug-Fix Releases Are Available for MPS Versions 2026.1.1, 2025.3.2, 2025.2.4, and 2025.1.4]() Original publisher: [Read original article]() Author: Vaclav Pech Published: 2026-09-16T20:06:31Z Content type: release Language: en Sources: [The JetBrains Blog]() Topics: [JetBrains MPS](), [releases](), [version](), [jetbrains]() Tags: [2](), [2025](), [2026](), [3](), [agent](), [agents](), [bug](), [changes](), [create](), [development](), [diagnostics](), [editor](), [improvements](), [major](), [manipulate](), [mps](), [practical](), [release](), [releases](), [updates](), [version]() ### AI overview JetBrains has released bug-fix updates for MPS versions 2026.1.1, 2025.3.2, 2025.2.4, and 2025.1.4. The MPS 2026.1.1 update includes improvements to the Projectional Agent Toolkit, editor context, diagnostics, agent guidance, and test execution. ### Source excerpt We've released updates for multiple major MPS versions that fix several issues. DOWNLOAD MPS 2026.1.1 Check out all the updates in each particular version below: MPS 2026.1.1 The Projectional Agent Toolkit receives several practical improvements that allow agents to: See and invoke intentions and quick-fixes on individual nodes. Manipulate NodeAttributes, PropertyAttributes, and others. Create copies [...] ## AI Security Governance: A Practical Framework for 2026 DevFeed: [AI Security Governance: A Practical Framework for 2026]() Original publisher: [Read original article]() Author: Christine Ferrusi Ross Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Security](), [Securing AI](), [ai-governance](), [Software Engineering]() Tags: [2026](), [ai](), [ai-security](), [governance](), [practical](), [security]() ### AI overview This article presents AI security governance as a structured program built on four pillars: policy, risk assessment, monitoring and audit, and accountability. It explains how these controls address untracked AI systems, unclear ownership, and missing records of automated actions, and discusses regulatory and organizational pressures driving adoption. ### Source excerpt Build an AI security governance framework covering policy, risk assessment, monitoring, and accountability, plus a risk register template to copy today. | Blog ## Laravel Queue Gotchas Collected from Experience DevFeed: [Laravel Queue Gotchas Collected from Experience]() Original publisher: [Read original article]() Author: Freek Van der Herten (freek@spatie.be) Published: 2026-09-10T12:06:27Z Content type: tutorial Language: en Sources: [freek.dev - all blogposts]() Topics: [Laravel](), [gotchas]() Tags: [best-practices](), [gotcha](), [gotchas](), [laravel](), [practical](), [queues]() ### AI overview An article about gotchas in Laravel queues that the author says they collected through experience. ### Source excerpt Laravel queues are great out of the box, until they bite. Over the years I've collected a few gotchas the hard way. Let me save you the headache. Read more ## What to expect at the Zephyr Project Meetup (September 17, 2026) - Zurich, Switzerland DevFeed: [What to expect at the Zephyr Project Meetup (September 17, 2026) - Zurich, Switzerland]() Original publisher: [Read original article]() Author: Susan Remmert Published: 2026-09-10T05:00:25Z Content type: news Language: en Sources: [Zephyr Project]() Topics: [Embedded Systems](), [Open Source](), [Embedded Software Dev](), [Tooling](), [Artificial Intelligence]() Tags: [2026](), [blog](), [community](), [debugging](), [developer-tools](), [developers](), [embedded](), [embedded-systems](), [event](), [events](), [meetup](), [modem](), [networking](), [open-source](), [practical](), [switzerland](), [technical]() ### AI overview An announcement for the September 17, 2026, Zephyr Project Meetup in Zurich, Switzerland, organized by Zoi TechCon GmbH. The event will include presentations on Zephyr modem support, embedded applications, developer tools, hardware, and practical implementation experiences. ### Source excerpt The Zephyr Project community is heading to Zurich, Switzerland! Join us on Thursday, September 17, 2026, for an in-person Zephyr Project Meetup organized by Zoi TechCon GmbH. The meetup will take place at Westhive Kitchen, Hardturmstrasse 161, 8005 Zürich, Switzerland. The event is open to developers, engineers, contributors, students, technology professionals, and anyone interested in open source and embedded systems. ## Run AI in the Browser: A Practical Guide to Transformers.js DevFeed: [Run AI in the Browser: A Practical Guide to Transformers.js]() Original publisher: [Read original article]() Author: Freek Van der Herten (freek@spatie.be) Published: 2026-09-09T14:50:26Z Content type: tutorial Language: en Sources: [freek.dev - all blogposts]() Topics: [transformers.js](), [browser](), [Artificial Intelligence](), [AI Models](), [Back end](), [API keys]() Tags: [ai](), [ai-models](), [api-keys](), [article](), [backend](), [browser](), [guide](), [internet](), [javascript](), [js](), [machine-learning](), [practical](), [run](), [transformers](), [transformers-js]() ### AI overview A practical guide to Transformers.js, covering how it runs AI models directly in the browser, available models, and the trade-offs of client-side AI compared with traditional AI providers. ### Source excerpt Transformers.js lets you run AI models directly in the browser without a backend, API keys, or an internet connection after the model is cached. The article explores how it works, which models are available, and the trade-offs of client-side AI compared to traditional AI providers. Read more ## Metric cardinality limits in OpenTelemetry: a practical guide DevFeed: [Metric cardinality limits in OpenTelemetry: a practical guide]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-08-06T07:43:47Z Content type: article Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [SDK](), [telemetry](), [dashboards]() Tags: [cardinality](), [dashboards](), [filter](), [guide](), [memory](), [metric](), [metrics](), [opentelemetry](), [practical](), [production]() ### AI overview This practical guide explains how OpenTelemetry metric cardinality limits protect process memory from unbounded growth. When a metric stream overflows, total values remain correct, but attribute-based filtering and grouping can undercount, affecting dashboards, SLOs, and alerts. ### Source excerpt OpenTelemetry metrics are designed to be safe to use in production. One part of that safety is the cardinality limit in the metrics SDK. The limit protects your process from unbounded memory growth when a metric receives too many unique attribute combinations. That protection is useful, but it has a consequence many users do not expect: when a metric stream overflows, the total value remains correct, while queries that filter or group by attributes can undercount. This can affect dashboards, service-level objectives (SLOs), and alerts that looked correct before overflow started. ## Prevent cognitive debt by manually retyping LLM-generated code DevFeed: [Prevent cognitive debt by manually retyping LLM-generated code]() Original publisher: [Read original article]() Author: Freek Van der Herten (freek@spatie.be) Published: 2026-08-04T12:56:26Z Content type: opinion Language: en Sources: [freek.dev - all blogposts]() Topics: [Large Language Model](), [Code]() Tags: [ai](), [best-practices](), [code](), [code-quality](), [cognitive-load](), [developer-experience](), [llm](), [model](), [practical](), [prevent](), [understand]() ### AI overview Ankur Sethi argues that manually retyping code generated by large language models can help developers understand the code, identify poor suggestions, and maintain a strong mental model of their codebase, despite slowing development. ### Source excerpt Ankur Sethi argues that manually retyping LLM-generated code is a practical way to avoid cognitive debt. It slows you down, but helps you understand the code, catch bad suggestions, and keep a strong mental model of your codebase. Read more ## What Is Enterprise Knowledge Management (EKM) and How Do You Actually Build It? DevFeed: [What Is Enterprise Knowledge Management (EKM) and How Do You Actually Build It?]() Original publisher: [Read original article]() Author: Janeera Published: 2026-07-30T12:23:25Z Content type: tutorial Language: en Sources: [Knowledge Management Tips, Best Practices and More]() Topics: [knowledge-management](), [decision-making]() Tags: [enterprise-knowledge-management](), [how-to](), [knowledge-management](), [knowledge-management-system](), [practical]() ### AI overview A practical guide to enterprise knowledge management (EKM), covering the knowledge organizations hold, how to assess program maturity, the components of an effective system, common failure points, and audits before investing in tooling. ### Source excerpt A senior engineer gives two weeks' notice. She mentions, almost offhand, that she's ... The post What Is Enterprise Knowledge Management (EKM) and How Do You Actually Build It? appeared first on Document360. ## June developer updates: AI capabilities, releases, projects, and Temporal guidance DevFeed: [June developer updates: AI capabilities, releases, projects, and Temporal guidance]() Original publisher: [Read original article]() Author: Temporal Technologies Published: 2026-06-30T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [releases](), [Strands Agents](), [SDKs](), [Amazon Web Services](), [Cloud](), [Command-line interface](), [Serverless](), [Open Source](), [Python]() Tags: [ai](), [announcements](), [cli](), [cloud](), [community](), [open-source](), [practical](), [pre-release](), [preview](), [python](), [releases](), [scale](), [teams]() ### AI overview A June digest covering Temporal updates, including an AWS Strands Agents integration in public preview, a Cloud CLI extension in pre-release, stable Namespace Endpoint IPs, Custom Roles, and the Temporal OSS v1.31 release. It also highlights live events, community projects, and a Python tutorial. ### Source excerpt Highlights from June include new AI capabilities, major releases, community-built projects, and practical guidance from teams running Temporal at scale. ## Building a Local AI Task Manager with PydanticAI and Ollama DevFeed: [Building a Local AI Task Manager with PydanticAI and Ollama]() Original publisher: [Read original article]() Author: Alex Razvant Published: 2026-03-22T14:03:18Z Content type: tutorial Language: en Sources: [Neural Bits]() Topics: [Ollama](), [Local AI](), [Pydantic](), [App](), [Large Language Model](), [Python](), [Code](), [Development]() Tags: [ai](), [code](), [dev](), [examples](), [guide](), [introduction](), [local](), [models](), [ollama](), [practical](), [tools]() ### AI overview A practical tutorial on building a local AI task manager with Ollama and PydanticAI. The application uses local language models and typed agent tools to handle tasks such as adding work, marking tasks complete, and listing overdue items. ### Source excerpt A practical introduction to agent-based architectures using typed models, tools, and runtime context in Pydantic AI. ## 12 OOP Concepts EVERY Developer Should Know DevFeed: [12 OOP Concepts EVERY Developer Should Know]() Original publisher: [Read original article]() Author: Ashish Pratap Singh Published: 2026-02-12T04:27:26Z Content type: tutorial Language: en Sources: [AlgoMaster Newsletter]() Topics: [Object-oriented programming (OOP)](), [Programming](), [Code](), [interfaces](), [Polymorphism](), [App]() Tags: [class](), [classes](), [code](), [concepts](), [developer](), [interface](), [interfaces](), [object-oriented](), [oop](), [practical](), [programming](), [real-world]() ### AI overview An introductory tutorial on object-oriented programming explains how classes, objects, and interfaces organize state and behavior. It uses real-world examples such as users, orders, payments, and payment gateways, and notes that these concepts are relevant to low-level design interviews. ### Source excerpt Key Object-Oriented Programming Concepts ## Common Data Pipeline Patterns You'll See in the Real World DevFeed: [Common Data Pipeline Patterns You'll See in the Real World]() Original publisher: [Read original article]() Author: SeattleDataGuy Published: 2026-01-05T19:58:06Z Content type: article Language: en Sources: [SeattleDataGuy's Newsletter]() Topics: [Data pipelines]() Tags: [data](), [data-pipeline](), [patterns](), [practical](), [real-world]() ### AI overview The article provides a practical overview of the different ways data pipelines appear within real companies. ### Source excerpt A practical look at the many ways data pipelines show up inside real companies ## Tips for running Temporal on Kubernetes DevFeed: [Tips for running Temporal on Kubernetes]() Original publisher: [Read original article]() Author: Cubby Sivasithamparam Published: 2025-12-15T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Kubernetes](), [Helm charts](), [Deployment](), [autoscaling](), [Resilience](), [Latency]() Tags: [autoscaling](), [charts](), [deployment](), [helm](), [how-to](), [kubernetes](), [performance](), [practical](), [production](), [scaling](), [temporal](), [tips]() ### AI overview This article provides practical guidance for deploying and operating Temporal on Kubernetes. It explains how Temporal adds durable state persistence, retries, and recovery, and recommends using Helm charts with external production dependencies rather than bundled development configurations. ### Source excerpt Learn practical tips for deploying and scaling Temporal on Kubernetes. Covers Helm charts, KEDA autoscaling, and production performance tuning. ## From Crash to Resolution: A Practical Guide for Xbox & Windows Developers DevFeed: [From Crash to Resolution: A Practical Guide for Xbox & Windows Developers]() Original publisher: [Read original article]() Author: Dean Hume Published: 2025-11-24T10:08:19Z Content type: opinion Language: en Sources: [Dean Hume]() Topics: [Windows](), [Xbox](), [App](), [Tool]() Tags: [crash](), [developers](), [diagnose](), [game-development](), [guide](), [practical](), [tools](), [windows](), [workflows](), [xbox]() ### AI overview The author describes an article about diagnosing and resolving app crashes on Xbox and Windows, sharing practical tips, tools, and workflows for developers building games or apps. ### Source excerpt If you've ever had an app crash at the worst possible moment, you'll know how frustrating it can be - both for developers and players. Recently, I wrote an article for the Microsoft Developer blog that dives deep into this exact challenge: how to diagnose and resolve ## How to lead a project DevFeed: [How to lead a project]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2025-11-19T00:00:00Z Content type: tutorial Language: en Sources: [Swizec Teller]() Topics: [task management](), [To-Do]() Tags: [how-to](), [practical](), [progress](), [project](), [real-time](), [review](), [scope](), [task-management](), [team](), [weekly]() ### AI overview A practical guide to leading a project by defining its outcome, target date, and scope; organizing work in a task management system; meeting weekly with stakeholders; and shipping work in small, reviewable increments. ### Source excerpt you were asked to lead or own a project. Now what? Here are a few practical steps to help you succeed. ## Why traditional motivation techniques can undermine intrinsic motivation in tech teams DevFeed: [Why traditional motivation techniques can undermine intrinsic motivation in tech teams]() Original publisher: [Read original article]() Author: Tom Published: 2025-09-26T00:00:00Z Content type: opinion Language: en Sources: [Tomasz Gągor]() Topics: [DRIVE]() Tags: [autonomy-mastery-purpose](), [best-practices](), [daniel-pink-drive](), [effective-leadership-strategies](), [intrinsic-motivation](), [leadership](), [leadership-best-practices](), [motivation-in-tech-teams](), [people](), [practical](), [strategies](), [team](), [team-engagement](), [tech]() ### AI overview This workshop-style article examines how traditional rewards, pressure, and micromanagement can undermine intrinsic motivation, especially in complex and creative tech work. Drawing on Daniel Pink's Drive, it encourages team leaders to support autonomy, mastery, and purpose. ### Source excerpt Discover why traditional motivation techniques can backfire in tech teams and how leaders can foster intrinsic motivation through autonomy, mastery, and purpose. Learn actionable strategies to empower your team and boost engagement, based on insights from Daniel Pink's "Drive." ## Seven Ways to Combine SEO and Generative Engine Optimization for Content Visibility DevFeed: [Seven Ways to Combine SEO and Generative Engine Optimization for Content Visibility]() Original publisher: [Read original article]() Author: Emma Adler Published: 2025-09-24T00:00:00Z Content type: tutorial Language: en Sources: [Mintlify Blog]() Topics: [Search engine optimization (SEO)](), [Artificial Intelligence](), [Google](), [Website]() Tags: [ai](), [ai-tools](), [ai-trends](), [content-strategy](), [generative-engine-optimization](), [geo](), [google](), [how-to](), [practical](), [search](), [seo](), [strategy](), [tips](), [visibility]() ### AI overview This tutorial explains how Generative Engine Optimization (GEO) complements search engine optimization (SEO) as AI tools and AI Overviews change how online content is discovered. It recommends concise Q&A-style content, authoritative and timely material, and user-generated content to improve the likelihood of visibility and citation in AI-generated answers. ### Source excerpt Practical tips on how to adapt your content strategy for GEO. ## What Should Repositories Return in Domain-Driven Design? DevFeed: [What Should Repositories Return in Domain-Driven Design?]() Original publisher: [Read original article]() Author: Furkan Kolcu Published: 2025-09-09T16:41:47Z Content type: article Language: en Sources: [Furkan Kolcu - Software Engineer Blog]() Topics: [Domain-driven design (DDD)](), [Repositories](), [Persistence]() Tags: [aggregates](), [clean-architecture](), [design-patterns](), [domain-driven-design](), [domain-driven-design-ddd](), [examples](), [lightweight](), [practical](), [repositories](), [repository-pattern](), [software-architecture](), [software-engineering](), [technology]() ### AI overview This article examines what repositories should return in Domain-Driven Design. It compares aggregates, DTOs or arrays, and primitives or special results, concluding that repositories should return aggregates when domain behavior is needed and primitives when they express valid domain-level answers. ### Source excerpt Repositories are a core part of Domain-Driven Design, but what they should return is often debated. Should it be aggregates, DTOs, or simple values? In this post, I share practical guidelines, examples, and tradeoffs to help clarify how to keep repositories focused on serving the domain. ## Bridging the Gap between Business Stakeholders and Engineering Teams: A Business Analyst's Playbook... DevFeed: [Bridging the Gap between Business Stakeholders and Engineering Teams: A Business Analyst's Playbook...]() Original publisher: [Read original article]() Author: Shelby Boyle Published: 2025-05-30T06:49:43Z Content type: tutorial Language: en Sources: [GumGum]() Topics: [Support](), [Data Science](), [jira](), [dashboards](), [data]() Tags: [bridging](), [business-analytics](), [collaboration](), [communication](), [data-science](), [engineering](), [guide](), [practical](), [product-development](), [teams](), [ticketing]() ### AI overview A business analyst playbook explains how to translate stakeholder needs into product solutions. It covers clarifying problems and impacts, using JIRA to support engineering work, and applying data science models and dashboards to analyze variables, customer behavior, revenue, and conversions. ### Source excerpt Bridging the Gap between Business Stakeholders and Engineering Teams: A Business Analyst's Playbook to Creating Quality Product SolutionsDoes your bridge look like this?! Tsingy Bemaraha National Park, Madagascar (my own photo August 2024) In today's evolving technology world, communication and collaboration are vital between business and engineering teams to deliver functional, scalable solutions. The Business Analyst (BA) is the problem-solver who ensures that business needs are translated into practical products to fuel powerful strategic decisions. What does this process look like? This is a detailed playbook BAs can follow to guide from stakeholder need to fully materialized product. 1. Meet with Stakeholders on Problem and the Impact The first step in solving any business problem is understanding the problem itself. What is the problem? What would be the desired outcome? What is the business impact of the problem? What would be the business impact of a possible solution? Ask these questions of your stakeholders and encourage them to distill the problem to its core. Meeting with stakeholders guarantees no details are left out: not just what may be documented, but what may not be documented as the problem. Using an engineering ticketing system like JIRA can facilitate this initial step. The better scoped the problem is, the sooner you can start working on analytic solutions. These initial conversations set the foundation for all subsequent steps. It makes your work easier too! 2. Define the Problem and Impact After initial stakeholder conversations, the BA defines the core problem, the present consequences of not having a solution, and the impact of constructing a product solution. These are some examples of this step: We need to understand variable likeness e.g. finding types of words associated with a holiday event or grouping customers based on shopping behavior. Without knowing this, we cannot derive target strategies for success or resolve weakness. Cue the ## Practical Considerations for Advancing AI Collaboration in Software Development DevFeed: [Practical Considerations for Advancing AI Collaboration in Software Development]() Original publisher: [Read original article]() Author: Peter Lawrey (noreply@blogger.com) Published: 2025-05-15T19:35:00Z Content type: opinion Language: en Sources: [Vanilla Java]() Topics: [Artificial Intelligence](), [AI Development](), [Development](), [Prompt Engineering](), [Software Engineering]() Tags: [ai](), [challenges](), [collaboration](), [development](), [evaluation](), [info](), [maintainability](), [mentoring](), [opinion](), [practical]() ### AI overview This article examines practical considerations for collaborating with AI in software development. It argues for human oversight, stronger documentation and context, critical evaluation of probabilistic outputs, diverse model use, and awareness of deskilling, ethical, intellectual-property, and software-economics risks. ### Source excerpt TL;DR Human-in-the-loop is essential; AI offers probability, not certainty. AI excels at word-smithing, so spend more time on documentation and context. Leverage diverse AI models for varied research, improvements, and analysis. Be wary of deskilling: if AI makes a task trivial, agents may soon replace it. You should feel like you are testing the boundaries of what AI is capable of for at least some tasks. The Problem AI's proficiency in handling routine coding allows human engineers to dedicate more time to strategic activities such as system design, architectural planning, intricate requirement elicitation, and the rigorous evaluation of application performance across multifaceted metrics. Tools often amplify underlying behaviours and failures -- Rob Lambert Value is increasingly found not in rote knowledge, which AI can often provide, but in the capacity to frame complex problems effectively for AI, critically evaluate its probabilistic outputs, and innovatively integrate AI's capabilities into novel solutions. Developing with AI is not merely about adopting a new tool but about learning to collaborate with intelligence that operates on different principles, sometimes without profound contextual understanding, yet capable of processing and synthesising information at a scale and speed that surpasses human capability. However, this power comes with new challenges: ensuring the reliability of probabilistically generated outputs, managing the 'black box' nature of some AI reasoning, and navigating the ethical and IP landscapes of AI-generated content. Effective collaboration requires developers to master prompt engineering, the art of providing precise context, critically verifying outputs, and understanding the AI's inherent limitations to guide it effectively. This is akin to mentoring an exceptionally capable but occasionally erratic junior partner. Moreover, "disposable" or "ephemeral" AI-generated software carries profound and often unexamined implications for s ## Optimizing Memory Layout in Go: A Deep Dive into Struct Design DevFeed: [Optimizing Memory Layout in Go: A Deep Dive into Struct Design]() Original publisher: [Read original article]() Author: ratneshmaurya2311@gmail.com (Ratnesh Maurya) Published: 2025-01-10T00:00:00Z Content type: tutorial Language: en Sources: [Ratn Labs]() Topics: [Go Language](), [ordering]() Tags: [alignment](), [backend](), [benchmarks](), [deep-dive](), [design](), [go](), [go-backend-system-design](), [golang](), [memory](), [optimizing](), [padding](), [practical](), [system-design](), [tools]() ### AI overview This article explains how Go struct field ordering affects memory usage through alignment and padding. It includes benchmarks across millions of allocations and practical tools for identifying wasted space. ### Source excerpt How Go struct field ordering affects memory via alignment and padding, with benchmarks across millions of allocations and practical tools to detect wasted space. ## How to build a Machine Learning portfolio in 2024? DevFeed: [How to build a Machine Learning portfolio in 2024?]() Original publisher: [Read original article]() Author: Meri Nova Published: 2024-10-16T19:14:35Z Content type: tutorial Language: en Sources: [Meri Nova]() Topics: [Machine Learning & Artificial Intelligence](), [AI Engineering](), [Software Engineering](), [clean-code]() Tags: [ai-engineering](), [how-to](), [machine-learning](), [ml-engineering](), [practical](), [project](), [real-world]() ### AI overview A practical guide to building a machine learning portfolio around a focused area of expertise. It presents the STEP framework: solve real-world problems, use relevant tools, follow strong engineering practices, and publish documented impact. ### Source excerpt Learn about the 4 essential components of an outstanding ML portfolio and land your dream job. ## Personal Notes about Simply Said DevFeed: [Personal Notes about Simply Said]() Original publisher: [Read original article]() Published: 2024-07-12T00:00:00Z Content type: article Language: en Sources: [Mutt0-ds Notes]() Topics: [communications](), [meetings]() Tags: [book](), [communication-skills](), [deep-dive](), [personal](), [practical](), [tips]() ### AI overview Personal notes and a condensed summary of Jay Sullivan's book "Simply Said," focusing on the principle of focusing on others and practical guidance for presentations, oral and written communication, meetings, leadership, and planning. ### Source excerpt "Simply Said" is the best communication book I've read recently. I discovered it thanks to Jordan Cutler (who runs an amazing tech... ## 💚 A Developer's Guide To Setting Boundaries DevFeed: [💚 A Developer's Guide To Setting Boundaries]() Original publisher: [Read original article]() Author: Richard Donovan Published: 2024-03-20T15:02:05Z Content type: opinion Language: en Sources: [The Modern Software Developer]() Topics: [Development](), [code productivity]() Tags: [developer](), [mental-health](), [practical](), [productivity](), [stress](), [work]() ### AI overview A practical guide for developers on setting and communicating personal boundaries to protect time, energy, mental health, and work-life balance. It describes common boundary violations and suggests calmly stating limits, expressing concerns, and proposing solutions aligned with personal values. ### Source excerpt Words < 1000 - Read time < 5 mins [Next page]()