# practices Published articles for practices. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Staying Technical as a Technical Program Manager DevFeed: [Staying Technical as a Technical Program Manager]() Original publisher: [Read original article]() Author: Dean Hume Published: 2026-02-18T11:39:39Z Content type: opinion Language: en Sources: [Dean Hume]() Topics: [Development](), [coding](), [engineering-culture](), [Raspberry Pi](), [Scripting]() Tags: [code](), [development](), [engineering](), [game-development](), [habits](), [hardware](), [learn](), [practices](), [scripting](), [skills](), [technical](), [technical-leadership]() ### AI overview A Technical Program Manager shares practical habits for staying technically sharp while managing programs, including occasional coding, writing technical content, following technology blogs, and building hands-on side projects. ### Source excerpt Learn practical ways Technical Program Managers can stay technical - daily habits, internal engineering practices, and hands-on routines that keep skills sharp while leading programs at scale. ## Prioritizing production-ready code over speed DevFeed: [Prioritizing production-ready code over speed]() Original publisher: [Read original article]() Published: 2025-06-11T00:00:00Z Content type: opinion Language: en Sources: [Gaurav Sarma's Blog]() Topics: [systems]() Tags: [career](), [practices](), [production](), [tech]() ### AI overview The author reflects on initially valuing rapid development over practices such as testing, monitoring, and CI/CD. They argue that taking time to productionize code reduces later refactoring and is ultimately less stressful and more effective. ### Source excerpt When I was new to the tech world and didn't have much experience with production systems, my main focus was to build fast. That was the way I would measure how good a developer is... ## WISE: Skyscanner's Bayesian AB experimentation library and decision engine DevFeed: [WISE: Skyscanner's Bayesian AB experimentation library and decision engine]() Original publisher: [Read original article]() Author: Skyscanner Engineering Published: 2024-04-25T06:22:08Z Content type: article Language: en Sources: [Stories by Skyscanner Engineering on Medium]() Topics: [experiments](), [Library](), [Python](), [Statistics]() Tags: [ab-testing](), [analytics](), [bayesian-statistics](), [data-science](), [engineering](), [experiment](), [experimentation](), [practices](), [statistics](), [test]() ### AI overview This article describes WISE, Skyscanner's centralized Bayesian A/B experimentation Python library and decision engine. It explains how Skyscanner uses randomized controlled experiments and why WISE was built to reduce manual analysis, standardize methodologies, and improve consistency in experimentation practices. ### Source excerpt By Dhanush Kishore, with Jose Parreño, May Alexander, Robert Shepherd, and the Skyscanner experimentation squad At Skyscanner, product decisions are driven by experimentation. As a global leader in travel, with 110 million users every month, we rely on a data-driven approach to growing and improving our product. Product managers, engineers, and data scientists run hundreds of experiments on our in-house AB experimentation platform, Dr Jekyll, to help make decisions about what features to ship for travelers and partners. When a team develops a new feature, the next step is to run a randomized controlled experiment. Every eligible user is randomly assigned either to the test variant B, where they interact with the new feature, or to the control variant A. After running the experiment for a certain duration, we test key metrics in variant B against variant A to determine whether the feature will be beneficial if rolled out to all users. This ensures that we follow an objective, scientifically rigorous approach to making product decisions. Although we already had a strong experimentation culture and an excellent experimentation platform, we identified the following needs as we scaled our experimentation program: Reduce manual effort in analyzing experiment results: While our experimentation platform, Dr Jekyll, reported test results for various metrics in an experiment, our data analytics team had to spend a considerable amount of time interpreting the results and making a decision on what variant to ship, which was becoming a bottleneck to scaling our experimentation program Need for standardization: Different teams at Skyscanner used different approaches to AB experimentation, and inconsistencies in methodologies meant it was difficult to compare results and share learnings across teams Consistency in adherence to experimentation best practices: While many teams maintained high standards of statistical rigor, others required additional support in designing and interpr ## Ways to Decrease Performance: Velocity Tracking DevFeed: [Ways to Decrease Performance: Velocity Tracking]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2023-07-15T06:00:00Z Content type: opinion Language: en Sources: [Tobias Mende]() Topics: [Agile](), [Software Engineering]() Tags: [agile](), [article](), [critical](), [measuring](), [metrics-practices-ways-to-decrease-performance-developer-productivity-engineering-excellence](), [performance](), [practices](), [story-points](), [teams](), [velocity]() ### AI overview This opinion article examines velocity tracking and estimation in Agile software teams. It explains how teams use story points, velocity trends, and burndown charts, then begins discussing how these practices can harm performance, including the limitations of human estimation. ### Source excerpt Ways to Decrease Performance: Velocity Tracking This is the first article of my series, "Ways to Decrease Performance", which intends to trigger critical reflection on common "Agile" practices, that is, practices that I see many "agile" teams doing. ## Crucial developer practices: Decoupling deployments and releases DevFeed: [Crucial developer practices: Decoupling deployments and releases]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2021-11-27T12:02:00Z Content type: article Language: en Sources: [Tobias Mende]() Topics: [feature flags](), [Deployment](), [releases](), [systems](), [Risk](), [Testing]() Tags: [continuous](), [continuous-deployment-software-development-software-craft](), [decoupling](), [deployments](), [developer](), [feature-flags](), [practices](), [risk](), [test](), [testing]() ### AI overview The article explains why growing systems should decouple deployments from releases. It focuses on release toggles, a type of transient feature flag that lets developers change application behavior at runtime, gradually roll out changes, roll them back, and test in production without breaking the system. ### Source excerpt Crucial developer practices: Decoupling deployments and releases When systems are small and the risk of introducing defects when changing its behaviour is low, these changes can happen during deployment. However, when systems grow, the behaviour becomes more complex and more people are working on the system, it is essential to decouple behaviour changes, the releases, from deployments. ## How to Reduce Layout Reflow When Using Web Fonts DevFeed: [How to Reduce Layout Reflow When Using Web Fonts]() Original publisher: [Read original article]() Published: 2021-09-09T09:00:00Z Content type: tutorial Language: en Sources: [Material.io - Material Design]() Topics: [Font](), [User Experience](), [Web]() Tags: [applying](), [best](), [best-practices](), [experience](), [fonts](), [how-to](), [layout](), [loading](), [practices](), [reduce](), [user](), [user-experience](), [using](), [web](), [web-fonts]() ### AI overview This article explains how applying font-loading best practices can reduce layout reflow when using web fonts and improve the user experience. ### Source excerpt Applying best practices for font loading can help improve the user experience ## Threat Modeling as Code DevFeed: [Threat Modeling as Code]() Original publisher: [Read original article]() Author: Adam Published: 2019-01-23T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [engineering-culture](), [Code](), [standard]() Tags: [code](), [delivery](), [engineering](), [practices](), [productivity]() ### AI overview This commentary explores representing threat models as code and aligning threat modeling with established engineering practices. It argues that converting threat-modeling analysis into code and selecting suitable code representations can increase delivery consistency and productivity, while requiring upfront effort. ### Source excerpt Exploring threat models as code. ## Threat Modeling Thursday: 2018 DevFeed: [Threat Modeling Thursday: 2018]() Original publisher: [Read original article]() Author: Adam Published: 2018-07-12T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Security](), [Architecture & Design]() Tags: [attacks](), [blackhat](), [engineering](), [framework](), [platforms](), [practices](), [security](), [security-engineering](), [series](), [social-media](), [talk](), [techniques]() ### AI overview The author asks readers what they want covered in the Threat Modeling Thursday series and in a Black Hat talk on threat modeling in 2018. The talk will address evolving attacks, system properties, attack techniques, social media threats, and keeping security engineering and threat modeling practices current. ### Source excerpt Help me help you. ## Frontend Dev Best Practices for 2017 DevFeed: [Frontend Dev Best Practices for 2017]() Original publisher: [Read original article]() Author: andrew@nystudio107.com (Andrew Welch) Published: 2017-01-03T21:14:00Z Content type: article Language: en Sources: [nystudio107 | Articles on modern web development.]() Topics: [Front end](), [Development](), [Web](), [Boilerplate](), [Chrome]() Tags: [2017](), [adopting](), [best](), [best-practices](), [chrome](), [consider](), [developer](), [exploring](), [frontend](), [google](), [https](), [insights](), [practices](), [search](), [serp](), [web](), [you-re]() ### AI overview A 2017 guide for frontend web developers recommends adopting one new technology, methodology, or design pattern in each project. It also recommends deploying new websites with HTTPS and HTTP/2. ### Source excerpt If you're a frontend web developer, here are some best practices you might consider exploring or adopting in 2017 ## Software engineering practices DevFeed: [Software engineering practices]() Original publisher: [Read original article]() Author: Graham King Published: 2015-06-19T02:08:49Z Content type: article Language: en Sources: [Graham King]() Topics: [Software Engineering](), [Development]() Tags: [code](), [documentation](), [engineering](), [legacy](), [practices](), [software](), [software-engineering](), [test]() ### AI overview A collection of software engineering practices drawn from notes at an XTC meetup, covering maintainable code, testing, source control, iterative development, domain understanding, automation, and coherent abstractions. ### Source excerpt Timeless wisdom for crafting better code: Essential software engineering practices. ## Logging best practices DevFeed: [Logging best practices]() Original publisher: [Read original article]() Author: Marek Published: 2013-12-30T23:00:00Z Content type: opinion Language: en Sources: [Marek Majkowski]() Topics: [Logging](), [systems](), [debugging](), [Linux Kernel]() Tags: [best-practices](), [debugging](), [linux-kernel](), [logging](), [logs](), [opinion](), [practices]() ### AI overview An opinionated guide to logging in larger systems. It distinguishes critical startup errors, debug messages, and access logs, and recommends treating critical failures separately while keeping logging volume and verbosity manageable. ### Source excerpt Logging best practices Every serious program has some kind of logging infrastructure. Sometimes it's trivial (); sometimes it's sophisticated and highly configurable. Unfortunately, many programs use logging inconsistently. The logging infrastructure is usually grown organically and not thought through. Many programs repeat the same mistakes with regard to logging. Let's take some time to talk about logging in larger systems.