# Tech Debt Published articles for Tech Debt. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Blog posts that influenced Simon Willison's thinking about software engineering DevFeed: [Blog posts that influenced Simon Willison's thinking about software engineering]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-14T20:21:48Z Content type: opinion Language: en Sources: [Simon Willison's Weblog]() Topics: [Software Engineering](), [Tech Debt](), [Database]() Tags: [charity-majors](), [charity-majors-10](), [individual-contributor](), [joel-spolsky](), [joel-spolsky-10](), [management](), [software-engineering](), [software-engineering-64](), [tech-debt](), [will-larson](), [will-larson-17]() ### AI overview Simon Willison describes three blog posts that influenced his thinking: Joel Spolsky's "The Law of Leaky Abstractions," Will Larson's "Migrations: the sole scalable fix to tech debt," and Charity Majors' "The Engineer/Manager Pendulum." He says they shaped his approach to understanding software layers, treating migrations as an important engineering skill, and moving between engineering management and individual-contributor work. ### Source excerpt My comment on What blog posts influenced your thinking the most? -- Lobste.rs. An early Joel Spolsky one for me was The Law of Leaky Abstractions. I read that near the start of my career and it's encouraged me to always be looking for improved understanding of the layers under where I'm working, just in case one of those abstractions leaks. A more recent one, from 2018, is Migrations: the sole scalable fix to tech debt by Will Larson. I absolutely love his idea that migrations (e.g. replacing one service with a new one, or switching database engines, or whatever) are part and parcel of software engineering and are a skill that you should invest in and get good at, not avoid or treat as special one-offs. The Engineer/Manager Pendulum by Charity Majors was hugely influential for me. I was stuck in engineering management and worried that if I switched back to being an "Individual Contributor" (ugh I hate that term) I'd damage my career. Charity gave me permission to make the switch by pointing out that many of the most successful software developers pendulum from one track to the other multiple times over their career, and doing so makes you better at both sides. Tags: joel-spolsky, software-engineering, will-larson, charity-majors ## How to Implement Feature Flags for Safe and Gradual Rollouts DevFeed: [How to Implement Feature Flags for Safe and Gradual Rollouts]() Original publisher: [Read original article]() Author: Abisoye Alli-Balogun Published: 2026-09-14T14:58:55Z Content type: article Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [feature flags](), [CI/CD](), [Deployment](), [Development](), [Tech Debt](), [Testing]() Tags: [architecture](), [best-practices](), [ci-cd](), [deployment](), [development](), [experimentation](), [feature-flags](), [how-to](), [tech-debt](), [testing]() ### AI overview This article explains how to implement feature flags for safe, gradual rollouts. It covers separating deployment from release, boolean toggles, percentage-based rollouts, user segmentation, experimentation, kill switches, lifecycle management, and common anti-patterns. ### Source excerpt Feature flags are one of the most powerful tools in a team's deployment arsenal. They decouple deployment from release, meaning your CI/CD pipeline can push code to production servers on every merge, ## 5 Billion Records, 10 Terabytes, Four Weeks: A Real Data Migration Playbook DevFeed: [5 Billion Records, 10 Terabytes, Four Weeks: A Real Data Migration Playbook]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-09-02T07:27:50Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [migration](), [data](), [Databases](), [API](), [Logging](), [Tech Debt]() Tags: [api](), [data](), [database](), [logging](), [migration](), [tech-debt]() ### AI overview This Wix engineering article presents a data migration playbook based on lessons from large and complex migrations. It argues that success depends less on changing tooling than on identifying recurring problems before migration begins, especially by auditing inconsistent source data, implementing a read phase, and logging suspicious fields and structures. It also outlines using a V2 API, an API proxy, population-based rollout, change data capture, continued synchronization, and eventual decommissioning of V1. ### Source excerpt By the time you finish reading this, someone at Wix is probably in the middle of a data migration. We've run migrations that lasted anywhere from a few months to two years. More recently, we've completed large and complex migrations in a few weeks. The difference wasn't the tooling, which barely changed. It was that we had finally learned which problems show up in every migration, and started dealing with them before the migration began instead of in the middle of it. Recap: Why We Migrate,... ## How AI Is Reshaping Cybersecurity for Attackers and Defenders DevFeed: [How AI Is Reshaping Cybersecurity for Attackers and Defenders]() Original publisher: [Read original article]() Published: 2026-08-17T05:30:00Z Content type: opinion Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [Cybersecurity](), [OpenAI](), [Threat Research](), [Vulnerabilities](), [AI Models]() Tags: [ai](), [ai-models](), [cybersecurity](), [openai](), [openai-hugging-face-incident](), [security](), [tech-debt](), [vulnerabilities]() ### AI overview OpenAI discusses how AI is changing cybersecurity for both attackers and defenders. The article describes the OpenAI-Hugging Face incident, argues that AI can accelerate the discovery and exploitation of security weaknesses, and outlines defensive measures including stronger security fundamentals and AI-assisted vulnerability remediation. ### Source excerpt AI is reshaping cybersecurity for attackers and defenders alike. Learn how OpenAI is strengthening its defenses and what security teams can do now. ## How to move fast toward the right thing DevFeed: [How to move fast toward the right thing]() Original publisher: [Read original article]() Author: Jake Albaugh Published: 2026-08-13T20:30:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Artificial Intelligence](), [Tech Debt](), [Large Language Model](), [Vibe coding](), [agentic-coding](), [sdlc]() Tags: [agentic-coding](), [ai](), [developers](), [llms](), [sdlc](), [tech-debt](), [vibe-coding]() ### AI overview AI makes software building faster and more accessible, but can also produce tech debt and encourage uncritical acceptance of polished outputs. The article argues that teams should begin with clear intent, carefully decide what is worth building, and use AI to translate that intent into software while retaining human judgment. ### Source excerpt With AI, speed comes easy, but so does tech debt. That's why the best teams don't just ship something fast; they consider it carefully, build it efficiently, and make it stand out. ## Agents change the math on big bang migrations DevFeed: [Agents change the math on big bang migrations]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-08-01T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [migration](), [Tailwind CSS](), [Bootstrap](), [Design system](), [Tech Debt](), [ui](), [React]() Tags: [agents](), [bootstrap](), [design-system](), [migrations](), [react](), [tailwind](), [tech-debt]() ### AI overview An opinion article argues that AI agents may change how teams approach large software migrations. It describes a one-step migration of hundreds of pages from Bootstrap to Tailwind in a 22,000-line pull request, which the author says fixed 13 small bugs without materially disrupting the company. ### Source excerpt I just did a team's worth of work in 5 days. Honestly I am shook to the core of my 20 YoE ## Top 3 agentic workflows for platform engineers in Port DevFeed: [Top 3 agentic workflows for platform engineers in Port]() Original publisher: [Read original article]() Author: Tomasz Skora Published: 2026-07-31T11:56:54Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Platform Engineering](), [AI Development](), [Tech Debt](), [Developer experience](), [developer-productivity](), [software-development]() Tags: [agentic](), [developer-experience](), [developer-productivity](), [platform](), [platform-engineering](), [software-development](), [tech-debt](), [workflows]() ### AI overview This article introduces agentic workflows for platform engineers, describing how AI agents can be integrated into existing software development and platform operations. The supplied excerpt focuses on autonomously resolving non-urgent engineering tasks, such as minor bugs, UX/UI issues, and refactoring, to reduce tech debt and improve developer productivity. ### Source excerpt Learn about the agentic workflows you can build in Port today and how they solve major productivity challenges. ## Agentic Engineering: Evolution of Developer Portals DevFeed: [Agentic Engineering: Evolution of Developer Portals]() Original publisher: [Read original article]() Author: Zohar Einy Published: 2026-07-30T11:25:32Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Artificial Intelligence](), [AI Development](), [Software Engineering](), [Developer experience](), [DevOps](), [Cloud Native Ecosystem](), [Microservice](), [Kubernetes](), [GitOps](), [CI/CD](), [incident](), [Vulnerabilities]() Tags: [agentic](), [ai](), [ai-agents](), [ci-cd](), [cloud-native](), [developer](), [developer-experience](), [devops](), [engineering](), [kubernetes](), [microservices](), [tech-debt]() ### AI overview The article presents agentic engineering as the next evolution of software engineering, with AI agents autonomously handling code, tests, pull requests, incidents, vulnerabilities, technical debt, and other software development lifecycle activities. It argues that developer portals can help provide the guidance and guardrails needed to manage the complexity created by DevOps, cloud-native systems, microservices, Kubernetes, GitOps, and extensive CI/CD automation. ### Source excerpt Internal developer portals are changing. Read all about Port's next evolution, the agentic engineering platform. ## Meet Engineering 360: Your hub for developer experience DevFeed: [Meet Engineering 360: Your hub for developer experience]() Original publisher: [Read original article]() Author: Roi Talpaz Published: 2026-07-22T11:34:04Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [internal developer portal](), [devex](), [Platform Engineering](), [dora metrics](), [Automation](), [Tech Debt]() Tags: [automation](), [developer-experience](), [developer-tools](), [devex](), [dora-metrics](), [internal-developer-portal](), [platform-engineering](), [tech-debt]() ### AI overview Engineering 360 is presented as a hub for developer experience that combines engineering intelligence, surveys, quantitative metrics such as DORA, and an internal developer portal. It aims to help platform and engineering teams identify friction, prioritize improvements, automate resolutions, and measure outcomes. ### Source excerpt We launched Engineering 360 to help engineering organizations close that loop: to gather insights, prioritize efforts, and turn feedback into visible outcomes. ## The Downsides of Agentic Skills DevFeed: [The Downsides of Agentic Skills]() Original publisher: [Read original article]() Author: Jorge Castillo Published: 2026-05-17T14:18:52Z Content type: opinion Language: en Sources: [Effective Android]() Topics: [context](), [Tech Debt](), [Latency](), [Testing]() Tags: [agentic](), [context](), [evals](), [latency](), [tech-debt](), [testing]() ### AI overview The article discusses tradeoffs of using agentic skills in production projects, including context costs, fuzzy triggering, nondeterministic behavior, harder testing, technical debt, and a growing permission surface. ### Source excerpt Skills are seductive. ## Android ❤ Gemini CLI - tech debt detection Code Maat skill DevFeed: [Android ❤ Gemini CLI - tech debt detection Code Maat skill]() Original publisher: [Read original article]() Published: 2026-03-08T00:00:00Z Content type: tutorial Language: en Sources: [maiatoday]() Topics: [Android](), [Tech Debt](), [Agent Skill](), [Command-line interface](), [Artificial Intelligence](), [Code](), [Git](), [Android Studio]() Tags: [adb](), [agent-skill](), [ai](), [android](), [cli](), [code](), [code-maat](), [command-line](), [gemini](), [gemini-cli](), [git](), [tech-debt]() ### AI overview This tutorial explores using Gemini CLI and an agent skill with Code Maat to identify technical-debt hotspots in the Habitica Android codebase. It describes using Git history to analyze file churn and logical coupling, and compares the approach with the Gemini Agent in Android Studio. ### Source excerpt Introduction What AI tools work for building Android apps? I am exploring some variations. In this post I will look at Gemini CLI, tech debt detection with a skill using Code Maat and how this compares with the Agent of Gemini in Android Studio. I am not starting with a new project. What if you have an existing codebase and you want to find the best place to tackle some tech debt that will make a difference for everyone. The sample codebase is the Habitica app, which had its first commit in 2015. Rather than poking at the code in a random or an "intuitive" way or asking the AI questions, let's look at a more deterministic way to answer this question. Or rather, let's teach the agent to use some scripts to answer this question. The benefit of packaging this functionality in a skill is that you can create this specialisation and script usage in a skill that will be loaded lazily only when you need it. The theory - Code as Crime scene Adam Tornhill wrote a book, Your Code as a Crime Scene, that uses your git history and applies forensic science to figure out where the hotspots, logical coupling, churn and more can be found in your code base. He has a java tool called Code Maat that you can use to analyse this information. The problem is, it is a bit finicky to setup and run and I can never remember all the command line parameters for git or for the tool. The theory TLDR is if you can see which large files change often or which files always change together, you can see which parts of your code are brittle or are coupled. The added benefit is that this analysis is language neutral. So if you build an agent skill for this, it can be used on any codebase. Creating the Code Maat Skill What do we need the link to Code Maat optionally download the code-maat standalone jar and put it in ~/tools/code-maat.jar to speed up the first run Gemini CLI + authentication and API key if you have it the skill-creator skill - this is part of the Gemini CLI install the Habitica Android app ## Fragmentation to framework: Spec-first development at Benchling DevFeed: [Fragmentation to framework: Spec-first development at Benchling]() Original publisher: [Read original article]() Author: Eli Levine Published: 2026-02-19T17:29:16Z Content type: article Language: en Sources: [Benchling]() Topics: [Development](), [Framework](), [data](), [API](), [Tech Debt](), [interoperability](), [configuration](), [migration]() Tags: [api](), [benchling](), [biotechnology](), [configuration](), [data](), [development](), [framework](), [interoperability](), [migration](), [platform-engineering](), [tech-debt]() ### AI overview Benchling describes how manually integrating scientific data objects with APIs, analytics, search, configuration migration, and other platform capabilities created an MxN maintenance burden, technical debt, and behavioral drift. The article introduces a spec-first framework approach intended to make platform functionality more uniform and scalable. ### Source excerpt Reaching the limit of manual platform development Benchling's platform handles diverse scientific data, such as DNA sequences, antibodies, notebook entries, inventory containers, workflow runs, and dozens more. Each object type carries unique domain logic: how it is validated, what relationships it holds, and what actions users can perform on it. As Benchling matured, capabilities were added that customers expected to work across all these objects including REST APIs for integration, a data warehouse for analytics, search indexing, and configuration migration tools for moving setups between tenants, among many others. Each product team is expected to expose their data in all platform surface areas. However, because this process is manual it can also be brittle and costly. With M object types and N platform capabilities, and each object requires custom integration with each capability, you're maintaining MxN integration points. Add a new object? You'll need to integrate it with every platform capability. Add a new capability? You'll need to integrate it with every object. In practice, this meant product and tech debt: some objects were available via API but missing from the warehouse, or a feature was exposed in the UI but not in other platform surface areas. It also meant behavioral drift. The same object would have slightly different field names or validation logic depending on which surface you accessed it through. As Benchling grew, so did its customers. Enterprise customers expect platforms that are designed for multi-modal integration that covers the full spectrum of Benchling's data and functionality. AI is quickly reshaping how knowledge work is done across all industries. But some fundamentals have not shifted. The same integration capabilities that make enterprise architectures more powerful are what makes agents more powerful too: both require data access and interoperability. Thus a different approach was needed. Ideally one where the cost of adding types ## Artsy Mobile 2025 Wrapped DevFeed: [Artsy Mobile 2025 Wrapped]() Original publisher: [Read original article]() Published: 2026-01-09T00:00:00Z Content type: article Language: en Sources: [Artsy]() Topics: [React Native](), [Expo](), [Mobile](), [Tech Debt](), [migration]() Tags: [android](), [ios](), [migration](), [mobile](), [mobile-apps](), [react-native](), [tech-debt]() ### AI overview Artsy reviews 2025 improvements to its mobile apps, including adopting Expo, moving all apps to React Native's new architecture, refactoring navigation, and addressing legacy code and technical debt. ### Source excerpt The past year has been an exciting one for our mobile apps (Artsy, Folio and Palette Mobile) and we started to finally get closer to where we want to be: High-performing and developer-friendly React Native applications, enabling rapid feature iteration and a superior user experience. We would like to share with you some of the improvements we made that might also be applicable to your react-native app. Infra Expo! At the end of 2024, after RFC: Trial Expo in Energy and/or Palette-Mobile, Spike on Eigen Risks, Rewards and Effort, we decided that we are giving Expo a try. Quickly afterwards, we added Expo with Prebuild on 2 out of 3 of our Apps: The CMS App, named Folio and our design system app, named Palette-Mobile. For our main app, Eigen, adding expo sdk happened faster than we thought after Microsoft decided to retire VS App Center. We needed an alternative for code-push, and we settled for Expo over-the-air updates. Eigen still has a lot of native code blocking us from fully migrating to Continue Native Generation (CNG) and sometimes conflicting with Expo. However, our experience from Energy and Palette-mobile has been positive so far and we could imagine CNG in Eigen! We will definitely share more about this if it happens. The new architecture Yes! We did it, all our apps are on the new architecture now. Expect a blog post about this! Tech Debt Eigen is an old repo, it's probably one of the oldest react-native apps out there. This comes with a price though. The industry changed a lot in the past years and a lot of the legacy code can now be rewritten using modern patterns more easily (and efficiently). To address that, we identified some weaknesses we had and prioritised them and decided to address them. Some notable mentions here include: Refactor our navigation Not long ago, it was hard for us to imagine our navigation infra all handled in react-navigation. But with more and more screens being rewritten in react-native and RN becoming more performant, it actu ## How AI May Transform Software Engineering into a Conducting Role DevFeed: [How AI May Transform Software Engineering into a Conducting Role]() Original publisher: [Read original article]() Author: Kaushik Gopal Published: 2025-10-11T18:59:38Z Content type: opinion Language: en Sources: [Kaushik Gopal's Site]() Topics: [Software](), [Orchestration](), [Prompt Engineering](), [Artificial Intelligence](), [systems](), [interfaces](), [context](), [Tech Debt]() Tags: [ai](), [interfaces](), [models](), [orchestration](), [software](), [software-engineer](), [structure](), [tech-debt](), [workflows]() ### AI overview This opinion article argues that AI may reshape software engineering by changing workflows and organizational systems, not merely by improving individual tasks. It proposes that software engineers may increasingly act as "software conductors," coordinating AI-assisted work through precise prompts, system design, and parallel experimentation. ### Source excerpt Engineers won't be replaced by tools that do their tasks better; they'll be replaced by systems that make those tasks nonessential. Sangeet Paul Choudary wrote an insightful piece on AI-driven job displacement and a more transformative way to think about it: To truly understand how AI affects jobs, we must look beyond individual tasks to comprehend AI's impact on our workflows and organizations. The task-centric view sees AI as a tool that improves how individual tasks are performed. Work remains structurally unchanged. AI is simply layered on top to improve speed or lower costs. ...In this framing, the main risk is that a smarter tool might replace the person doing the task. The system-centric view, on the other hand, looks at how AI reshapes the organization of work itself. It focuses on how tasks fit into broader workflows and how their value is determined by the logic of the overall system. In this view, even if tasks persist, the rationale for grouping them into a particular job, or even performing them within the company, may no longer hold once AI changes the system's structure. If we adopt a system-centric view, how does the role of a software engineer evolve?1 I've had a notion for some time -- the role will transform into a software "conductor". Software conductors # music conductors conducting is the art of directing the simultaneous performance of several players or singers by the use of gesture The tasks a software conductor must master differ from those of today's software engineer. Here are some of the shifts I can think of: Task Orchestration Mastery ## The craft is knowing exactly how much detail to provide in prompts: too little and models thrash; too much and they overfit or hallucinate constraints. You'll need to write spec-grade prompts that define interfaces, acceptance criteria, and boundaries -- chunking work into units atomic enough for clear execution yet large enough to preserve context. Equally critical: recognizing when to interrupt and redi ## Quantifying Tech Debt: The Artisan of the Day Is Ed Grosvenor DevFeed: [Quantifying Tech Debt: The Artisan of the Day Is Ed Grosvenor]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-09-06T16:38:00Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [Tech Debt](), [Livewire](), [PHP](), [Tooling](), [Vue.js](), [hosting](), [browser](), [Cloud]() Tags: [developers](), [development](), [eu](), [events](), [hosting](), [laravel](), [php](), [tech](), [tech-debt](), [testing](), [tooling](), [ui](), [vue](), [workflow]() ### AI overview Ed Grosvenor describes Artisan Build's Laravel-focused development workflow, its use of the TALL stack and Livewire, and a product designed to help developers quantify and address technical debt. ### Source excerpt Ed Grosvenor, co-founder of Artisan Build, uses Laravel to help developers quantify tech debt, build tooling, and power client projects. ## From Tech Debt to Top Priority: The Engineer's Guide to Getting Buy-In DevFeed: [From Tech Debt to Top Priority: The Engineer's Guide to Getting Buy-In]() Original publisher: [Read original article]() Author: Caleb Mellas Published: 2025-06-18T12:30:09Z Content type: tutorial Language: en Sources: [Level up software engineering]() Topics: [Tech Debt]() Tags: [guide](), [how-to](), [leadership](), [tech-debt]() ### AI overview A guide to gaining leadership buy-in for addressing technical debt and other large projects across multiple teams, tight timelines, and security concerns. ### Source excerpt How to get leadership buy-in for tech debt and other large projects across multiple teams, tight timelines, security concerns and more. ## Power struggles and long-term strategy in startups DevFeed: [Power struggles and long-term strategy in startups]() Original publisher: [Read original article]() Author: Denis Čahuk Published: 2024-12-30T14:44:46Z Content type: opinion Language: en Sources: [Crafting Tech Teams]() Topics: [Tech Debt](), [Software Engineering](), [Agile](), [Self-organizing Team]() Tags: [agile](), [case-studies](), [collaboration](), [communication](), [complexity](), [cto](), [engineering](), [leadership](), [management](), [pitfalls](), [project-management](), [recommendations](), [roadmaps](), [safety](), [software-development](), [startups](), [team-dynamics](), [tech-debt]() ### AI overview This podcast discussion examines power struggles, short-term thinking, technical debt, and operational inefficiencies in startups and scale-ups. It covers team dynamics, project management, unplanned work, communication, psychological safety, and aligning engineering efforts with business goals. ### Source excerpt Mario Tomić, fractional CTO joined Adrian Stanek and Denis Čahuk for an exchange of situational studies and examples of power struggles and lack of long term strategy in startups. Highlights below 👇 ## Why you need soft skills as a Tech Lead DevFeed: [Why you need soft skills as a Tech Lead]() Original publisher: [Read original article]() Author: Anemari Fiser Published: 2024-11-27T07:01:53Z Content type: opinion Language: en Sources: [Level up as a Tech Lead]() Topics: [Tech Lead](), [Tech Debt](), [Parser]() Tags: [coaching](), [collaboration](), [delegation](), [leadership](), [mentoring](), [tech-debt](), [tech-lead](), [technical]() ### AI overview This opinion article argues that tech leads need soft skills in addition to technical expertise because many recurring technical problems are rooted in interpersonal issues. It discusses listening, relationship building, feedback, delegation, facilitation, conflict resolution, and mentoring or coaching. ### Source excerpt Most tech leads think they only need strong technical skills in order to be effective as tech leads. ## Deployment-Driven Development DevFeed: [Deployment-Driven Development]() Original publisher: [Read original article]() Published: 2024-11-11T22:57:13Z Content type: article Language: en Sources: [Brave New Geek]() Topics: [Deployment](), [Domain-driven design (DDD)](), [software-architecture](), [Platform Engineering](), [Testing](), [Tech Debt](), [sdlc]() Tags: [architecture](), [ddd](), [deployment](), [deployment-driven-development](), [development-process](), [devops](), [domain-driven-design](), [konfigurate](), [platform-engineering](), [qa](), [sdlc](), [security](), [tech-debt]() ### AI overview The article introduces Deployment-Driven Development as a complement to Domain-Driven Design, focusing on delayed feedback and delivery obstacles that affect software architecture, testing, security, compliance, and production readiness. ### Source excerpt Most people use "DDD" to refer to Domain-Driven Design, which is a useful tool for thinking about API boundaries and system architecture. It provides a way to map a business problem into software. At Real Kinetic, we regularly help our clients utilize Domain-Driven Design as well as other strategies to architect their systems, avoid some of the pitfalls of DDD, and build an effective foundation for designing software. But this DDD only speaks to one small aspect of building and shipping software. ## Netflix's Transition from Multiple APIs to GraphQL Federation DevFeed: [Netflix's Transition from Multiple APIs to GraphQL Federation]() Original publisher: [Read original article]() Author: Ishwari Lokare Published: 2024-07-10T09:00:00Z Content type: article Language: en Sources: [Apollo Blog]() Topics: [GraphQL](), [Netflix](), [API](), [API Platform](), [Streaming](), [OpenAPI Specification](), [Tech Debt](), [Back end](), [Front end]() Tags: [api](), [api-platform](), [backend](), [community](), [development](), [frontend](), [graphql](), [netflix](), [openapi](), [streaming](), [tech-debt]() ### AI overview This article describes Netflix's evolution through four generations of APIs, from an API-first OpenAPI strategy and REST-based services to Falcor and eventually GraphQL Federation. It explains how the company used the graph to address API complexity, support collaboration, manage technical debt and reduce organizational barriers. ### Source excerpt Netflix is the world's most popular streaming service. While everyone knows how it paved the way for a whole new industry when it moved from its physical DVD business to the cloud, you may not know how Netflix's API platform powered that transition. As Bruce Wang, Director of Engineering of Games Platform at Netflix shared at a Champions Corner Webinar, they went through four generations of APIs before transitioning to GraphQL Federation. ## Security, Maintainability, Velocity: Choose One DevFeed: [Security, Maintainability, Velocity: Choose One]() Original publisher: [Read original article]() Published: 2024-04-17T17:41:24Z Content type: opinion Language: en Sources: [Brave New Geek]() Topics: [Security](), [Development](), [Software Engineering](), [software-development]() Tags: [breach](), [cloud](), [development](), [governance](), [idp](), [internal-developer-platform](), [konfigurate](), [maintainability](), [platform-engineering](), [product-development](), [ransomware](), [security](), [software-development](), [software-development-triangle](), [software-engineering](), [tech-debt](), [velocity]() ### AI overview The article presents security, maintainability, and development velocity as competing priorities in software development. It argues that organizations often treat these priorities as a "choose one" trade-off, while suggesting that deliberate planning can help achieve all three. ### Source excerpt There are three competing priorities that companies have as it relates to software development: security, maintainability, and velocity. I'll elaborate on what I mean by each of these in just a bit. When I originally started thinking about this, I thought of it in the context of the "good, fast, cheap: choose two" project management triangle. But after thinking about it for more than a couple minutes, and as I related it to my own experience and observations at other companies, I realized that in practice it's much worse. For most organizations building software, it's more like security, maintainability, velocity: choose one. ## Balancing delivery speed and high-quality code DevFeed: [Balancing delivery speed and high-quality code]() Original publisher: [Read original article]() Author: Mike Published: 2023-09-22T23:17:08Z Content type: opinion Language: en Sources: [Dev Details]() Topics: [Test-driven development](), [Testing](), [Code quality](), [Tech Debt]() Tags: [quality](), [tdd](), [tech-debt](), [testing]() ### AI overview The article argues that delivery speed and code quality can be balanced by envisioning the desired end state, working backward through milestones, and taking deliberate shortcuts with known tradeoffs. It presents behavior-focused tests written alongside code as the main way to deliver faster while maintaining quality, and cautions that poor or absent tests increase delivery friction over time. ### Source excerpt When building out new features, how do you balance speed of delivery with implementing higher quality yet more time-consuming code? ## The Role Of A System Architect DevFeed: [The Role Of A System Architect]() Original publisher: [Read original article]() Author: jesalg Published: 2023-08-08T00:00:00Z Content type: opinion Language: en Sources: [Jesal Gadhia]() Topics: [Development](), [Agile](), [Tech Debt](), [reliability]() Tags: [agile](), [architect](), [architecture](), [collaboration](), [engineering](), [engineering-management](), [leadership](), [mentoring](), [reliability](), [software-development](), [system-design](), [tech-debt]() ### AI overview This opinion article examines the proposed role of a system architect in startups experiencing rapid growth. It discusses how the role could identify and reduce technical bottlenecks, complexity, silos, and technical debt while improving coordination, architecture, development quality, performance, and reliability. It also considers how the role fits with Agile practices. ### Source excerpt A Step-by-Step Sprint Planning Guide for Engineering Leaders ## Migrating to Dart 3 and null safety DevFeed: [Migrating to Dart 3 and null safety]() Original publisher: [Read original article]() Author: Manideep Polireddi Published: 2023-05-12T17:00:00Z Content type: tutorial Language: en Sources: [@okmanideep]() Topics: [Dart](), [Flutter](), [Pull Request](), [Script](), [Tech Debt](), [pattern matching]() Tags: [dart](), [flutter](), [migrate](), [pattern-matching](), [script](), [tech-debt](), [upgrade]() ### AI overview A practical guide to gradually migrating an existing Flutter codebase to Dart 3 and sound null safety. It describes adding null-safety markers, using pull-request checks to guide incremental conversion, identifying untouched files for migration, and handling large difficult files as technical debt. ### Source excerpt Dart 3 is here, but we cannot adopt it unless our entire codebase is null safe. Here are few strategies we have been using to slowly migrate our codebase [Next page]()