# real-world Published articles for real-world. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How Marathon Incidents Expose Organizational Fragility and Require Structured Incident Response DevFeed: [How Marathon Incidents Expose Organizational Fragility and Require Structured Incident Response]() Original publisher: [Read original article]() Author: Vanessa Huerta Granda Published: 2026-09-17T09:30:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [incident](), [Incident response]() Tags: [devops](), [incident](), [incident-response](), [infoq](), [limits](), [organizational](), [outages](), [presentation](), [qcon-san-francisco-2026](), [qcon-software-development-conference](), [real-world](), [stream-incidents](), [structured](), [system](), [transcripts]() ### AI overview Vanessa Huerta Granda discusses how prolonged incidents reveal gaps between planned work and work as performed. Drawing on real-world scenarios, the presentation examines organizational fragility, human limits, system interdependencies, and the need for structured, humane, cross-functional incident response. ### Source excerpt Vanessa Huerta Granda explains how marathon incidents expose the gap between work as imagined and work as done. Drawing from real-world scenarios, she shares how complex outages reveal organizational fragility, human limits, and system interdependencies--and why incident response requires structured endurance, humane rotations, and holistic cross-functional coordination. By Vanessa Huerta Granda ## Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award DevFeed: [Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award]() Original publisher: [Read original article]() Author: Erin Lee | Lincoln Laboratory Published: 2026-09-11T13:45:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Development](), [Software]() Tags: [2026](), [ai](), [ai-assisted-catheterization-device](), [ai-guide](), [artificial-intelligence](), [asha-rajagopal](), [autonomus-medical-technologies](), [awards-honors-and-fellowships](), [devices](), [emergency-medicine](), [engineering](), [excellence-in-technology-transfer-awards](), [federal-laboratory-consortium-for-technology-transfer](), [field](), [funding](), [health-sciences-and-technology](), [industry](), [invention](), [lincoln-laboratory](), [mass-general-hospital](), [medical-device-invention](), [medical-devices](), [medicine](), [mgh](), [military-medics](), [mit-intellectual-property](), [mit-lincoln-laboratory](), [mit-startups](), [mit-technology-licensing-office-tlo](), [national-institutes-of-health-nih](), [nih-funding](), [portable](), [prototype](), [real-world](), [research](), [samuel-kesner](), [startup](), [startups](), [technology](), [u-s-armed-forces](), [u-s-army]() ### AI overview AI-GUIDE, a portable catheterization device developed by MIT Lincoln Laboratory and Massachusetts General Hospital, received the Federal Laboratory Consortium's 2026 Excellence in Technology Transfer Award. The project is transferring its prototype to AutonomUS Medical Technologies for commercialization. ### Source excerpt The handheld catheterization device AI-GUIDE, created by Lincoln Laboratory and Massachusetts General Hospital, promises improved health outcomes for injured service members and civilians. ## Scratch a simple data model, find a complex one DevFeed: [Scratch a simple data model, find a complex one]() Original publisher: [Read original article]() Author: jonskeet Published: 2026-08-14T10:09:48Z Content type: opinion Language: en Sources: [Jon Skeet]() Topics: [data]() Tags: [complex](), [data](), [general](), [model](), [real-world]() ### AI overview The article examines how a data model that initially appears simple becomes more complex when it must represent the Bible across English translations, differing book sets, alternate book titles, chapters, and verses. ### Source excerpt I seem to have a knack for discovering corner cases - or in many situations being a corner case. One category of this is where I find myself using a data model which appears simple to start with - and then the real world interferes. I've always found this sort of thing interesting, and recently ... Continue reading Scratch a simple data model, find a complex one -> ## When the human is the Workflow: Durable Execution in harsh physical field operations DevFeed: [When the human is the Workflow: Durable Execution in harsh physical field operations]() Original publisher: [Read original article]() Author: Saman Batool Published: 2026-08-11T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [implementation](), [Architecture & Design](), [Orchestration](), [Process](), [Encryption]() Tags: [community](), [compliance](), [distributed](), [encryption](), [idempotency](), [implementation](), [infrastructure](), [microservices](), [network](), [offline-first](), [orchestration](), [real-world](), [retries]() ### AI overview A case study describes how Xgrid and a construction company rebuilt crew clock-ins, daily reporting, and document signing on Temporal. It presents a single durable Workflow per shift as the source of truth for unreliable, offline-first field operations, with patterns for idempotency, compliance, retries, encryption, and scalable execution. ### Source excerpt This blog from Xgrid, a Certified Temporal Cloud Partner, explores how field operations in construction, infrastructure, and facilities management can be modeled as a Durable Execution problem rather than a collection of fragile services. Drawing from a real-world implementation, it shows how crew clock-ins, daily reporting, and document signing were rebuilt on Temporal using a single Workflow per shift as the durable source of truth. ## 8 ways teams use Mintlify to keep docs updated automatically DevFeed: [8 ways teams use Mintlify to keep docs updated automatically]() Original publisher: [Read original article]() Author: Peri Langlois Published: 2026-03-20T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Automation](), [Documentation](), [Code](), [OpenAPI Specification]() Tags: [article](), [automatically](), [automation](), [best-practices](), [code](), [docs](), [guide](), [maintenance](), [patterns](), [real-world]() ### AI overview This guide describes eight ways teams use Mintlify automations to maintain documentation, including syncing docs with code changes, generating changelogs, auditing SEO, checking grammar and broken links, translating content, enforcing style, and auditing accessibility. It explains how workflows can read a codebase, apply defined logic and prompts, and open pull requests with updates. ### Source excerpt A use-case-driven guide to automating documentation maintenance with Mintlify, featuring automations code snippets for eight real-world automation patterns. ## 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 ## Replay '25, day two: Big announcements, real-world wins, and Durable Execution DevFeed: [Replay '25, day two: Big announcements, real-world wins, and Durable Execution]() Original publisher: [Read original article]() Author: Tim Imkin Published: 2025-03-06T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [SDK](), [Replication](), [migration](), [Google Cloud Platform (GCP)](), [airflow](), [Self-hosted](), [Spring Boot](), [Java](), [observability](), [Testing]() Tags: [airflow](), [announcements](), [community](), [google-cloud](), [implementation](), [java](), [migration](), [observability](), [orchestration](), [real-world](), [technology]() ### AI overview Day two of Replay '25 covered Temporal product announcements, including a pre-release Ruby SDK, Nexus general availability, namespace replication, worker versioning APIs, migration tooling, Temporal Cloud on Google Cloud, and new security and operations tools. The article also reports case studies and technical sessions on workflow orchestration, self-hosting, Spring Boot integration, observability, scaling, and testing. ### Source excerpt Catch up on day two of Replay '25 in London, featuring big announcements from Temporal, real-world success stories across telecom, finance, and technology sectors, and practical insights into durable system execution. ## 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. ## Designing software with AI DevFeed: [Designing software with AI]() Original publisher: [Read original article]() Author: Mike Published: 2023-06-14T03:36:00Z Content type: tutorial Language: en Sources: [Dev Details]() Topics: [Artificial Intelligence](), [Software](), [coding](), [App](), [prompt](), [prompting](), [service](), [ChatGPT](), [Code Challenge](), [client]() Tags: [ai](), [analytics](), [application](), [chatgpt](), [coding](), [guide](), [mapping](), [practical](), [prompt](), [prompting](), [real-world](), [service](), [software]() ### AI overview Part 2 of a practical series showing how to use AI as a collaborator when designing software. The article uses a URL shortener as a practical example and demonstrates how ChatGPT 3.5 guides problem-context and use-case discussions, with ChatGPT 4 producing better results in a test run. ### Source excerpt Part 2 of a practical example of using AI for coding ## Annotated JSON-LD Structured Data Examples DevFeed: [Annotated JSON-LD Structured Data Examples]() Original publisher: [Read original article]() Author: andrew@nystudio107.com (Andrew Welch) Published: 2019-05-29T12:00:00Z Content type: tutorial Language: en Sources: [nystudio107 | Articles on modern web development.]() Topics: [json-ld](), [Structured-data](), [JSON](), [Google Search](), [Content Management System]() Tags: [annotation](), [article](), [cms](), [data](), [examples](), [insights](), [json](), [json-ld](), [plus](), [real-world](), [structured](), [want](), [wild]() ### AI overview This article presents annotated, real-world JSON-LD structured data examples. It explains how schema.org vocabularies express context and connections, recommends selecting explicit best-fit schema types supported by Google, and introduces node identifiers for referencing schemas without unnecessary repetition. ### Source excerpt Want to see a some real-world examples of JSON-LD Structured Data "in the wild"? This article has that, plus annotation. ## An Annotated webpack 4 Config for Frontend Web Development DevFeed: [An Annotated webpack 4 Config for Frontend Web Development]() Original publisher: [Read original article]() Author: andrew@nystudio107.com (Andrew Welch) Published: 2018-10-23T13:40:00Z Content type: tutorial Language: en Sources: [nystudio107 | Articles on modern web development.]() Topics: [Webpack](), [Web Development](), [Front end](), [Tooling]() Tags: [build](), [complete](), [complex](), [development](), [example](), [frontend](), [help](), [here-s](), [insights](), [modern](), [need](), [production](), [real-world](), [sophisticated](), [tooling](), [web-development](), [webpack](), [websites]() ### AI overview A tutorial presenting an annotated, real-world production webpack 4 configuration for modern frontend web development. It explains why the author adopted webpack and compares it with alternatives such as Laravel Mix, vue-cli, and Neutrino. ### Source excerpt As web development becomes more complex, we need tooling to help us build modern websites. Here's a complete real-world production example of a sophisticated webpack 4 config ## NP-hard does not mean hard DevFeed: [NP-hard does not mean hard]() Original publisher: [Read original article]() Published: 2017-12-29T13:30:23Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Algorithms, Complexity](), [Algorithms](), [Programming]() Tags: [algorithm](), [algorithms](), [boolean](), [completeness](), [complexity-theory](), [logic](), [mario](), [mathematics](), [np-completeness](), [np-hard](), [problems](), [real-world](), [regular-languages](), [solve](), [time]() ### AI overview This article explains that NP-hardness is a worst-case mathematical property, not a claim that a problem is always difficult for humans or algorithms. Using Super Mario as an example, it shows how game levels can encode boolean logic and why solving the game in full generality would encompass hard computational problems, while ordinary real-world levels may still be solvable efficiently. ### Source excerpt When NP-hardness pops up on the internet, say because some silly blogger wants to write about video games, it's often tempting to conclude that the problem being proved NP-hard is actually very hard! "Scientists proved Super Mario is NP-hard? I always knew there was a reason I wasn't very good at it!" Sorry, these two are unrelated. NP-hardness means hard in a narrow sense this post should hopefully make clear. After that, we'll explore what "hard" means in a mathematical sense that you can apply beyond NP-hardness to inform your work as a programmer. ## Composible Architecture: A real-world example. DevFeed: [Composible Architecture: A real-world example.]() Original publisher: [Read original article]() Published: 2016-03-27T00:00:00Z Content type: article Language: en Sources: [Adam Bard]() Topics: [Flask](), [REST API](), [Library](), [Routing (disambiguation)](), [JSON]() Tags: [api](), [architecture](), [flask](), [json](), [library](), [real-world](), [rest-api](), [routing]() ### AI overview A technical discussion of composable architecture in a Flask-Restful REST API, focusing on reqparse validation and the use of reusable validator functions to keep special-case handling out of general-purpose parsing code. ### Source excerpt I am the primary maintainer of a significant REST API written using Flask-Restful. Flask-Restful is a pretty full-featured library for creating REST frameworks with Flask. It features everything you need to manage routing to class-based resources, a library for marshalling objects to JSON format, and reqparse, an argparse-inspired library for writing input parsers. ## React in the Real World DevFeed: [React in the Real World]() Original publisher: [Read original article]() Author: Tor Arne Kvaløy Published: 2014-12-15T12:36:31Z Content type: opinion Language: en Sources: [Finn.no]() Topics: [React](), [Front end](), [migration](), [JavaScript](), [jQuery](), [Webpack]() Tags: [bugs](), [front-end](), [javascript](), [migration](), [react](), [real-world](), [webpack]() ### AI overview An experience report from FINN oppdrag about migrating front-end functionality from JSP/jQuery to React. The article says the migration reduced code size for equivalent functionality, improved code clarity, and resulted in fewer bugs, while allowing React and legacy code to coexist during incremental migration. ### Source excerpt At FINN oppdrag, a year ago we came to realize that our front-end code, written in JSP/jQuery, had become so large and complex that it affected our ability to produce features. We spent more time making sure the DOM manipulations were correct and did not break, than actually creating value for our users. So we agreed that we needed a front-end framework to simplify our development and after looking into Ember and Angular we decided to go for React, recently open sourced by Facebook. Our attraction to React was based on its promise of providing components with encapsulated state, fast automatic DOM manipulations, and the ability to render on the server. Migration We started by porting some functionality that already existed, and our first discovery was that the lines of codes needed to make the exact same functionality was almost reduced by half. Secondly, the code became clearer and easier to understand. And thirdly, as a combination of the reduced lines of code, the cleaner code and no manual DOM manipulations, we got less bugs. Since then all new features have been written with React, and when we are requested to make modifications to functionality written in the old code, we rewrite them to use React. When migrating large pages to React we start from the inside, the deepest DOM nodes, and let it gradually grow till the whole page is reactified. This often happened through several iterations and deployments, as React and the old JSP/JQuery can quite peacefully coexist. Bundles With React, HTML is represented as JavaScripts, so the JavaScript bundles will contain all the HTML, and hence grow as the pages grow. Instead of having a bundle for each page (very small), or having a bundle for the whole site (very big), we found a middle way where we have bundles based on roles, in our use cases contractor and owner. A possible improvement on this is loading JavaScript on demand with technologies like webpack. Flux So if React is our first great discovery, the Flux patter ## Going to Chicago, Postgres Open DevFeed: [Going to Chicago, Postgres Open]() Original publisher: [Read original article]() Author: Dimitri Fontaine PostgreSQL Major Contributor; Author Published: 2014-08-29T12:26:00Z Content type: article Language: en Sources: [Dimitri Fontaine]() Topics: [PostgreSQL](), [Tutorial](), [Extension](), [SQL](), [ui]() Tags: [developers](), [extensions](), [postgresql](), [practical](), [real-world](), [sql](), [tutorial](), [user-interface]() ### AI overview The author announces plans to host a PostgreSQL extensions tutorial and a developer talk at Postgres Open 2014 in Chicago. The tutorial will cover extension packaging and practical use cases with real-world data, while the talk will discuss common table expressions and window functions. Another tutorial will address PostgreSQL-based approximate search, suggestions, and autocompletion. ### Source excerpt Next month, Postgres Open 2014 is happening in Chicago, and I'll have the pleasure to host a tutorial about PostgreSQL Extensions Writing & Using Postgres Extensions, and a talk aimed at developers wanting to make the best out of PostgreSQL, PostgreSQL for developers: The tutorial is based on first hand experience on the PostgreSQL Extension Packaging System both as a user and a developer. It's a series of practical use cases where using extensions will simplify your life a lot, and each of those practical use case is using real world data (thanks to pgloader). ## Linear Programming and Healthy Diets -- Part 1 DevFeed: [Linear Programming and Healthy Diets -- Part 1]() Original publisher: [Read original article]() Published: 2014-06-02T09:00:27Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Optimization](), [Combinatorial optimization](), [Mathematics](), [Programming](), [Computer science]() Tags: [combinatorial-optimization](), [duality](), [linear-programming](), [mathematics](), [nutrition](), [operations-research](), [optimization](), [primal](), [programming](), [real-world]() ### AI overview This introductory tutorial explains linear programming as a central problem in combinatorial optimization. It models choosing quantities of oranges, milk, and broccoli to minimize food costs while meeting nutritional constraints, including recommended levels of water, calcium, and vitamin C. ### Source excerpt Optimization is by far one of the richest ways to apply computer science and mathematics to the real world. Everybody is looking to optimize something: companies want to maximize profits, factories want to maximize efficiency, investors want to minimize risk, the list just goes on and on. The mathematical tools for optimization are also some of the richest mathematical techniques. They form the cornerstone of an entire industry known as operations research, and advances in this field literally change the world.