# Reflections Published articles for Reflections. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## It's Okay to Break Things: Reflections on Khan Academy's Healthy Hackathon DevFeed: [It's Okay to Break Things: Reflections on Khan Academy's Healthy Hackathon]() Original publisher: [Read original article]() Author: Khan Academy Published: 2017-03-06T23:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [Hackathon](), [Software Engineering](), [API](), [Web]() Tags: [api](), [collaboration](), [engineering](), [equity](), [hackathon](), [mozilla](), [news](), [reflections](), [software-engineer](), [web-frontend]() ### AI overview Kimerie Green reflects on participating in Khan Academy's internal Healthy Hackathon while working as a Software Engineering Fellow. She describes building Read-to-Me, an experimental project using Mozilla's Web Speech API to read Perseus widget content aloud for early learners. The project was not shipped because it needed further code review and design work, but it provided lessons about curiosity, collaboration, and software engineering. ### Source excerpt By Kimerie Green For the past few months, I have been working as a Software Engineering Fellow at ... Read more ## The circle of competence for developers DevFeed: [The circle of competence for developers]() Original publisher: [Read original article]() Author: Federico Tomassetti Published: 2026-07-26T06:34:18Z Content type: opinion Language: en Sources: [Federico Tomassetti]() Topics: [Programming](), [Code](), [Artificial Intelligence](), [Large Language Model]() Tags: [ai](), [code](), [developers](), [llms](), [programming](), [reflections]() ### AI overview The article reflects on developers' future amid rapid changes in AI-assisted programming. It argues that a core developer competence is describing system behavior precisely, while noting that programming roles and practices differ widely. ### Source excerpt In the world of programming, we are asking ourselves questions about the future of the developer--or, more importantly, about whether developers have a future at all. What is going to happen to us? This makes me think of the "circle of competence" discussed in the book The Art of the Good Life. The author argues [...] The post The circle of competence for developers appeared first on Federico Tomassetti. ## Adopting Agentic: Talks and Reflections from Our AI Engineering Event DevFeed: [Adopting Agentic: Talks and Reflections from Our AI Engineering Event]() Original publisher: [Read original article]() Author: Colin Eberhardt Published: 2026-07-15T00:00:00Z Content type: opinion Language: en Sources: [Scott Logic]() Topics: [Artificial Intelligence](), [AI Engineering](), [Software Engineering](), [Automation]() Tags: [agentic](), [ai](), [ai-engineering](), [automation](), [autonomous](), [engineering](), [event](), [reflections](), [sdlc](), [software-engineering](), [talks](), [tech]() ### AI overview This article summarizes talks and discussions from the Adopting Agentic event, focusing on how AI is affecting software engineering, individual skills and job roles, teams, organizational practices, and the software development life cycle. It also includes the author's reflections, key quotes, and session videos. ### Source excerpt A summary of the talks and discussions from our recent event, Adopting Agentic - Software Engineering for the AI Age, exploring the human and organisational impact of AI on our industry. Includes session videos, key quotes and my personal reflections on each presentation. ## Reflections on the Evolution of Data Science + AI at Microsoft and a Career Transition DevFeed: [Reflections on the Evolution of Data Science + AI at Microsoft and a Career Transition]() Original publisher: [Read original article]() Author: Casey Doyle Published: 2026-06-30T07:16:00Z Content type: opinion Language: en Sources: [Data Science at Microsoft]() Topics: [Data Science](), [Microsoft](), [Artificial Intelligence](), [Data visualization]() Tags: [ai](), [data-science](), [data-visualization](), [development](), [journey](), [microsoft](), [reflections](), [ship-of-theseus]() ### AI overview The author reflects on the evolution of Microsoft's Data Science + AI publication, their departure from Microsoft, and the career experiences that shaped their approach to communicating complex ideas for business impact. ### Source excerpt Reflections on storytelling, change, and what enduresPhoto by Joseph Barrientos on Unsplash. And so the mythical hero Theseus sailed home to Athens after defeating the Minotaur. To honor him, the Athenians preserved his wooden ship in their harbor down the centuries. As the old planks rotted, builders replaced them with identical new ones. Eventually, they replaced every single original piece of wood. This sparked a famous debate among philosophers: With every part replaced, is it still the same ship? Like the ship of Theseus, what endures also undergoes many changes. That idea applies not only to the Data Science + AI at Microsoft online publication you're reading now, but also to my own career journey. After two stints totaling more than 32 years at Microsoft, and more than six years leading Data Science + AI at Microsoft, I am turning the page on both chapters this month as I prepare to depart. As I mark this transition, I feel many emotions, but one that stands out most is gratitude -- for the people, opportunities, and experiences that have shaped both the work and me. Leading Data Science + AI at Microsoft (which we call DS@M internally) since its inception has been a highlight of my working life. From its initial focus on data science in early 2020 to its evolution to encompass AI starting in 2023, DS@M continues to attract an audience as it approaches 10,000 followers. For me, this is especially remarkable given some of the internal pushback that came in the time before we launched, reflecting skepticism that it was possible, much less advisable, to share our data science expertise outside the company without crossing proprietary lines. That we moved forward -- and ultimately succeeded -- was possible only because of the many authors and collaborators who believed in the idea and were willing to contribute their work. More than 340 articles later, we've amply proved we could do it, and do it well. In many ways, this work reflects the culmination of the paths th ## What Is Software, and Will LLMs Replace It? DevFeed: [What Is Software, and Will LLMs Replace It?]() Original publisher: [Read original article]() Author: Federico Tomassetti Published: 2026-06-23T08:56:06Z Content type: opinion Language: en Sources: [Federico Tomassetti]() Topics: [Large Language Model](), [Software](), [data](), [integrity](), [Software as a service]() Tags: [ai](), [business](), [chatbots](), [consistency](), [data](), [future-of-ai](), [future-of-software](), [integrity](), [interfaces](), [language-engineering](), [llms](), [mcp](), [opinion](), [patterns](), [reflections](), [saas](), [software](), [software-development](), [sql](), [structure](), [visualization]() ### AI overview The article argues that large language models are unlikely to replace software. Instead, they may provide more flexible interfaces while software's underlying structures--organized data, schemas, constraints, consistency rules, visualizations, and guided processes--remain essential. ### Source excerpt Software isn't being replaced by LLMs, it's being fronted by them, with the deterministic core (schemas, constraints, processes) staying as essential as ever. The post What Is Software, and Will LLMs Replace It? appeared first on Federico Tomassetti. ## AI Coding Feels Like Using an Unreliable Compiler DevFeed: [AI Coding Feels Like Using an Unreliable Compiler]() Original publisher: [Read original article]() Author: Federico Tomassetti Published: 2026-05-19T13:17:09Z Content type: opinion Language: en Sources: [Federico Tomassetti]() Topics: [ai-coding](), [Large Language Model](), [Compiler](), [coding](), [Development]() Tags: [ai](), [ai-coding](), [compiler](), [language-engineering](), [llm](), [programming](), [reflections](), [software-development](), [time](), [verification]() ### AI overview The article argues that current LLMs used for coding resemble unreliable compilers: their transformation of developer intent into code is not sufficiently faithful, repeatable, or reliable to trust without verification. Developers must inspect, understand, test, and often correct generated code, shifting the bottleneck from writing code to reviewing it. ### Source excerpt AI Coding Feels Like Using an Unreliable Compiler Every developer I know is asking roughly the same questions about LLMs. Yes, there are LLM-fanatics and LLM-skeptics, but most are LLM-confused: sometimes LLMs seem amazing and sometimes they seem so dumb one wonders why we are using them in the first place. So we keep asking [...] The post AI Coding Feels Like Using an Unreliable Compiler appeared first on Federico Tomassetti. ## Reflections on AI at the end of 2025 DevFeed: [Reflections on AI at the end of 2025]() Original publisher: [Read original article]() Published: 2025-12-20T08:58:29Z Content type: opinion Language: en Sources: [Antirez]() Topics: [Artificial Intelligence](), [Large Language Model](), [Chain-of-thought](), [rlvr](), [AI-assisted coding](), [Programming]() Tags: [2025](), [ai](), [chain-of-thought](), [code](), [coding](), [coding-agents](), [reflections](), [reinforcement-learning]() ### AI overview An end-of-2025 reflection on developments in AI, including changing views of LLM representations, chain-of-thought, reinforcement learning with verifiable rewards, and growing adoption of AI-assisted programming. The author presents these as observations and expectations, including the possibility that improved reinforcement learning could become a major direction in AI. ### Source excerpt * For years, despite functional evidence and scientific hints accumulating, certain AI researchers continued to claim LLMs were stochastic parrots: probabilistic machines that would: 1. NOT have any representation about the meaning of the prompt. 2. NOT have any representation about what they were going to say. In 2025 finally almost everybody stopped saying so. * Chain of thought is now a fundamental way to improve LLM output. But, what is CoT? Why it improves output? I believe it is two things: 1. Sampling in the model representations (that is, a form of internal search). After information and concepts relevant to the prompt topic is in the context window, the model can better reply. 2. But if you mix this to reinforcement learning, the model also learns to put one token after the other (each token will change the model state) in order to converge to some useful reply. * The idea that scaling is limited to the number of tokens we have, is no longer true, because of reinforcement learning with verifiable rewards. We are still not at AlphaGo move 37 moment, but is this really impossible in the future? There are certain tasks, like improving a given program for speed, for instance, where in theory the model can continue to make progress with a very clear reward signal for a very long time. I believe improvements to RL applied to LLMs will be the next big thing in AI. * Programmers resistance to AI assisted programming has lowered considerably. Even if LLMs make mistakes, the ability of LLMs to deliver useful code and hints improved to the point most skeptics started to use LLMs anyway: now the return on the investment is acceptable for many more folks. The programming world is still split among who uses LLMs as colleagues (for instance, all my interaction is via the web interface of Gemini, Claude, ...), and who uses LLMs as independent coding agents. * A few well known AI scientists believe that what happened with Transformers can happen again, and better, following d ## Reflections on OpenAI DevFeed: [Reflections on OpenAI]() Original publisher: [Read original article]() Author: Calvin French-Owen Published: 2025-07-15T15:49:56Z Content type: opinion Language: en Sources: [Calvin French-Owen]() Topics: [OpenAI](), [codex](), [Large Language Model]() Tags: [culture](), [llms](), [openai](), [organization](), [reflections](), [slack](), [work]() ### AI overview A former OpenAI employee reflects on the company's culture, rapid growth, organizational challenges, and differing experiences across research, applied, and go-to-market teams. ### Source excerpt There's a lot of smoke and noise around what OpenAI is doing, but not a lot of first-hand accounts of what the culture of working there actually feels like. Here's my view on what it was like to work there. ## 2023 in Review DevFeed: [2023 in Review]() Original publisher: [Read original article]() Author: Hugh Howey Published: 2023-12-31T00:00:00Z Content type: opinion Language: en Sources: [Una Kravets]() Topics: [CSS](), [modern web development]() Tags: [css](), [reflections](), [tech](), [year-in-review]() ### AI overview A personal review of 2023 covering stress, anxiety, depression, health challenges, travel, sewing, home ownership, career milestones, and work on CSS features. The article also reports growth for The CSS Podcast, including a redesign, a fourth season, new episodes, and audience figures. ### Source excerpt Annual year in review: 2023 edition. ## Reflections on the 'Disruptive Tech: Wasm Edition' Tour of India DevFeed: [Reflections on the 'Disruptive Tech: Wasm Edition' Tour of India]() Original publisher: [Read original article]() Author: Matt Butcher Published: 2023-07-24T12:00:00Z Content type: opinion Language: en Sources: [Fermyon - Experience the next wave of cloud computing.]() Topics: [wasm]() Tags: [india](), [reflections](), [wasm]() ### AI overview Reflections on the 'Disruptive Tech: Wasm Edition' tour of India. ## Taro's 2023 Reflections on YouTube Growth, Career Content, Events, and AI DevFeed: [Taro's 2023 Reflections on YouTube Growth, Career Content, Events, and AI]() Original publisher: [Read original article]() Author: Rahul Pandey Published: 2023-07-11T13:21:01Z Content type: opinion Language: en Sources: [Alex Chiou]() Topics: [Users](), [AI Chat](), [Mobile](), [Testing](), [Tech Lead]() Tags: [advice](), [ai](), [events](), [instagram](), [meta](), [mobile](), [reflections](), [tech-lead](), [test-coverage](), [testing](), [users]() ### AI overview The author reflects on Taro's 2023 progress, including a plateau in YouTube subscribers, growth in active platform users, successful events, increased Q&A activity, and selected content about Instagram mobile apps, testing, and a Taro-trained chatbot. ### Source excerpt We're back with the best of the best over the past 6 months ## The Responsibility of Tech: Reflections from Grace Hopper Celebration DevFeed: [The Responsibility of Tech: Reflections from Grace Hopper Celebration]() Original publisher: [Read original article]() Author: Nida Pervez Published: 2021-11-11T15:33:52Z Content type: opinion Language: en Sources: [Groupon Engineering -- Medium]() Topics: [Development](), [Google](), [Artificial Intelligence]() Tags: [conference](), [ethics](), [google](), [product-development](), [reflections](), [tech](), [tech-industry](), [women-in-tech]() ### AI overview A reflection on Grace Hopper Celebration sessions about ethics, responsibility, gender inequality, and disability in technology. The author considers how technology companies and product teams should support women and take responsibility for the effects of their work. ### Source excerpt The end of September was marked by one of the most exciting events for women in technology: Grace Hopper Celebration of Women in Computing (GHC). For those who do not know, GHC is a yearly conference that highlights women's contributions/involvement in different aspects of the tech industry. In a field that is overwhelmingly dominated by men, it's important to acknowledge the feats of women which otherwise might be drowned out. The week-long conference is packed with speakers, panels, interactive sessions, networking events, and a career fair. In my college days most of my attention admittedly was on the career fair -- but this year I had the opportunity to attend virtually through Groupon, a platinum sponsor of the conference. This year's theme was #DareTo, and I saw that play out in many of the talks, but the sessions that impacted me the most dared me to take responsibility for tech I produced. Three talks that especially left an impression on me were Dr.Timnit Gebru's keynote, Integrating Ethics and Responsibility in the Product Development Cycle by Kathy Pham, and Disability is an Opportunity for Innovation by Haben Girma. Each speaker speaks on the effect of taking responsibility (or lack thereof) for one's technological feats. Dr.Gebru's talk highlighted how large tech corporations can take advantage of freedom for the sake of technological "advancement". In her talk, Gebru explained in detail about her dismissal from the co-lead position of Google's ethical AI team. There were two main aspects to this song that I understood. One being the sexism she faced and the other was the blatant unethical behavior of Google. Gebru addresses the inequality between men and women in the workforce at Google and highlighted that she was fired for doing the right thing, whereas many of her male counterparts could do ethically wrong things and still get by. As a company that is an Emerald sponsor (highest degree of sponsorship) of GHC, she asked what kind of message does that ## Reflections on software performance DevFeed: [Reflections on software performance]() Original publisher: [Read original article]() Author: Nelson Elhage Published: 2020-02-03T01:00:00Z Content type: opinion Language: en Sources: [Nelson Elhage]() Topics: [Software](), [coding]() Tags: [blog](), [performance](), [reflections](), [software]() ### AI overview A reflection on lessons learned from building and using performant software. The article argues that performance is a feature that affects how software is perceived and used, and that making tools faster enables users to pursue tasks more frequently and in new ways. ### Source excerpt At this point in my career, I've worked on at least three projects where performance was a defining characteristic: Livegrep, Taktician, and Sorbet (I discussed sorbet in particular last time, and livegrep in an earlier post). I've also done a lot of other performance work on the tools I use, some of which ended up on my other blog, Accidentally Quadratic. In this post, I want to reflect on some of the lessons I've learned while writing performant software, and working with rather a lot more not-so-performant software. ## Why Signal argues that federated messengers cannot remain competitive as software ecosystems evolve DevFeed: [Why Signal argues that federated messengers cannot remain competitive as software ecosystems evolve]() Original publisher: [Read original article]() Published: 2016-05-10T00:00:00Z Content type: opinion Language: en Sources: [Signal Blog]() Topics: [Open Source](), [centralization](), [Protocol (disambiguation)](), [Security](), [User experience (UX)](), [Software]() Tags: [centralization](), [communication](), [developer](), [ecosystem](), [open-source](), [reflections](), [security](), [software](), [ux]() ### AI overview Open Whisper Systems reflects on how changing platforms, networks, security threats, and user expectations affect software development. The article argues that federating an application-layer messenger makes change difficult and that a federated messenger may not remain competitive as the ecosystem evolves. ### Source excerpt At Open Whisper Systems, we've been developing open source "consumer-facing" software for the past four years. We want to share some of the things we've learned while doing it. As a software developer, I envy writers, musicians, and filmmakers. Unlike software, when they create something, it is really done -- forever. A recorded album can be just the same 20 years later, but software has to change. Software exists as part of an ecosystem, and the ecosystem is moving. The platform changes out from under it, the networks evolve, security threats and countermeasures are in constant shift, and the collective UX language rarely sits still. As more money, time, and focus has gone into the ecosystem, the faster the whole thing has begun to travel. All of this means that the set of expectations users have for social and communication features are evolving rapidly. Anyone building software today knows that it is not possible to stand still. Read more... ## Générer le script DDL programmatiquement avec Hibernate 4.x DevFeed: [Générer le script DDL programmatiquement avec Hibernate 4.x]() Original publisher: [Read original article]() Author: brice.dutheil@gmail.com (Brice Dutheil) Published: 2015-08-07T15:26:51Z Content type: tutorial Language: fr Sources: [The Coffee Workshop]() Topics: [Code](), [SQL](), [Framework](), [modules]() Tags: [classes](), [code](), [framework](), [hibernate](), [jpa](), [reflections](), [scanner](), [sql](), [structure]() ### AI overview This tutorial presents programmatic generation of DDL scripts for applications using Hibernate 4.x with non-trivial configurations. It explains passing annotated classes and packages explicitly and using Reflections to scan JPA-annotated classes when hibernate4-maven-plugin is insufficient. ### Source excerpt Si par hasard votre base donnée est gérée par un véritable DBA, donc avec des scripts SQL. Mais que vous utilisez hibernate pour mapper les tables avec une configuration non triviale, modules bien découpés, package annotés, etc.... Les utilitaires comme hibernate4-maven-plugin ne suffisent plus. ## Annotation Processing 101 DevFeed: [Annotation Processing 101]() Original publisher: [Read original article]() Author: Hannes Dorfmann Published: 2015-01-10T09:00:00Z Content type: tutorial Language: en Sources: [Hannes Dorfmann]() Topics: [Java](), [Compiler](), [Code]() Tags: [annotation-processor](), [blog](), [compiler](), [files](), [generate](), [how-to](), [java](), [reflections]() ### AI overview This tutorial explains Java annotation processing, including how it works at compile time, what annotation processors can generate, and what they cannot change in existing classes. It then begins a step-by-step implementation of a simple processor. ### Source excerpt In this blog entry I would like to explain how to write an annotation processor. First, I am going to explain to you what annotation processing is, what you can do with that powerful tool and finally what you cannot do with it. In a second step we will implement a simple annotation processor step by step. ## Andy Pavlo Reflects on His Job Search and Building H-Store DevFeed: [Andy Pavlo Reflects on His Job Search and Building H-Store]() Original publisher: [Read original article]() Author: Andy Pavlo Published: 2013-08-26T16:19:22Z Content type: opinion Language: en Sources: [Andy Pavlo - Carnegie Mellon University]() Topics: [Job](), [Databases](), [Website](), [Oracle-VM-VirtualBox]() Tags: [blog](), [database](), [job](), [job-search](), [reflections](), [virtualbox](), [website]() ### AI overview Andy Pavlo reflects on his academic job search and describes how becoming the primary contributor to H-Store helped him develop a focused research story, build a project website, and document his work. ### Source excerpt Andy starts writing a blog and reflects on the recent job search. People will sing songs about this day for years to come.