# experience Published articles for experience. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Udacity Android Basics Course Alumni Experience DevFeed: [Udacity Android Basics Course Alumni Experience]() Original publisher: [Read original article]() Author: dustin@dustn.dev (Dustin Summers) Published: 2026-09-17T04:13:15.404035Z Content type: article Language: en Sources: [Dustin Summers]() Topics: [Android]() Tags: [android](), [course](), [experience]() ### AI overview The author describes providing input on life after completing Udacity's Android Basics course and on their experience working in Android. ### Source excerpt As an alumni of the Udacity Android Basics course, they reached out for my input in life after the course and my experience working in Android. ## GNOME 51 Released With Improved Frame Scheduling, Many App Improvements DevFeed: [GNOME 51 Released With Improved Frame Scheduling, Many App Improvements]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-16T16:25:21Z Content type: news Language: en Sources: [Phoronix]() Topics: [releases](), [Wayland](), [Release notes](), [Software](), [ui](), [legacy](), [Nvidia]() Tags: [desktop](), [desktop-linux](), [driver](), [experience](), [faster](), [improvements](), [legacy](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [notes](), [nvidia](), [offline](), [open-source-graphics](), [other](), [phoronix](), [phoronix-test-suite](), [protocols](), [release](), [release-notes](), [settings](), [software](), [time](), [ubuntu](), [ubuntu-benchmarks](), [ubuntu-hardware](), [ui](), [wayland](), [workstation]() ### AI overview GNOME 51 has been released with improved frame scheduling and desktop responsiveness, new Wayland protocol support, removal of legacy NVIDIA EGLStreams driver support, and updates to several GNOME applications and settings. ### Source excerpt Right on schedule and in time for appearing in the likes of Ubuntu 26.10 and Fedora Workstation 45, the GNOME 51 desktop is officially released... ## Receiving feedback as an intern at Khan Academy DevFeed: [Receiving feedback as an intern at Khan Academy]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-10-26T22:00:00Z Content type: opinion Language: en Sources: [Khan Academy]() Topics: [Code review](), [engineering-culture](), [Development]() Tags: [code-review](), [culture](), [engineering](), [experience](), [infrastructure](), [intern](), [news]() ### AI overview David Wang reflects on receiving code review feedback as an intern at Khan Academy. He describes the distinction between code critiques and character critiques, and explains Khan Academy's view of feedback as an ongoing, positive investment in colleagues' development. ### Source excerpt By David Wang When my first piece of code was reviewed at Khan Academy, my mentor Dylan prefaced ... Read more ## New Trailer Reveals Project Hail Mary: Journey Among The Stars Gameplay DevFeed: [New Trailer Reveals Project Hail Mary: Journey Among The Stars Gameplay]() Original publisher: [Read original article]() Author: James Tocchio Published: 2026-09-02T14:47:20Z Content type: news Language: en Sources: [UploadVR]() Topics: [Android XR](), [Meta]() Tags: [2026](), [android-xr](), [engineering](), [experience](), [launch](), [meta](), [platforms](), [skills](), [vr-gaming]() ### AI overview A new trailer offers the first extended look at gameplay for Project Hail Mary: Journey Among the Stars, a mixed reality experience developed with Andy Weir. Players take the role of Ryland Grace and work with Rocky to diagnose failing ship systems and protect the mission. ### Source excerpt A new trailer reveals gameplay of Project Hail Mary: Journey Among The Stars, a mixed reality experience launching on Quest, Pico, and Android XR this fall. ## Senior Engineer ≠ Years of Experience DevFeed: [Senior Engineer ≠ Years of Experience]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-08-24T06:01:00Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [Software Engineering](), [Development](), [engineering-culture]() Tags: [effective](), [engineering](), [experience](), [learning](), [mistakes](), [software]() ### AI overview This opinion argues that years of software engineering experience do not reliably measure engineering ability. Repeated habits, including poor design, avoiding tests, and overengineering, can become more entrenched over time, while continuous learning, experimentation, feedback, and willingness to change are presented as stronger indicators of effectiveness. ### Source excerpt "I've been doing this for 15 years, so I already know." ## Droidcon Orlando 2026 Recap - Tadeas Kriz DevFeed: [Droidcon Orlando 2026 Recap - Tadeas Kriz]() Original publisher: [Read original article]() Published: 2026-08-18T00:00:00Z Content type: article Language: en Sources: [Touchlab | Enterprise Mobile Innovation & Development]() Topics: [Kotlin Multiplatform](), [Kotlin](), [Android](), [iOS](), [Coroutines](), [Concurrency]() Tags: [2026](), [android](), [community](), [coroutines](), [demo](), [droidcon](), [experience](), [ios](), [kotlin](), [kotlin-interpreter](), [kotlin-multiplatform](), [multiplatform](), [recap](), [speaking]() ### AI overview A recap of Droidcon USA in Orlando, covering the conference venue, talks, and a demo of Kotlin Multiplatform Hot Reload. The author explains that file changes were propagated to an application running on Android and iOS, while Kotlin Interpreter work continues. ### Source excerpt Droidcon USA moved to Orlando this year. Tadeas recaps his experience attending and speaking at the new venue. ## Roadmap decisions rather than dates. DevFeed: [Roadmap decisions rather than dates.]() Original publisher: [Read original article]() Published: 2026-08-11T14:00:00Z Content type: opinion Language: en Sources: [Will Larson - Irrational Exuberance]() Topics: [Development](), [Passkeys](), [resiliency](), [User Experience](), [Mobile](), [Web]() Tags: [development](), [experience](), [implementation](), [mobile](), [phishing](), [resiliency](), [web]() ### AI overview The article argues that product roadmaps should prioritize decisions and execution constraints rather than fixed dates. It uses the development and rollout of passkey support at Imprint as an example, describing implementation behind a feature flag, staged web release, feedback iteration, and expansion to native mobile experiences. ### Source excerpt One thing that bothered me about Imprint's product after joining was our lack of passkey support. Passkey support is a rare opportunity to increase resiliency to phishing attacks while simultaneously reducing login friction. If it's good for our members, our partners, and our product, it felt like something we should have already shipped. Nonetheless, it was hard to get it onto the roadmap alongside everything else we were working on. To dig into passkeys, I started sketching out the implementation as a side quest. Some iterations later, I had something implemented behind a disabled feature flag for team review. At that point, most problems had a concrete solution implemented, and the remaining issues were messy intersections between passkey implementation and user experience. Issues remained, but the tangible implementation made tradeoffs explicit, and we were able to work through them. Soon thereafter, we launched passkeys to a small group in our web experience, iterated on feedback, finalized the details, and brought those details forward to our native mobile experiences as well. It never got onto the roadmap, but it did ship. Our passkey release planted a seed for me, but it required another experience to fully germinate. We had a discussion about hitting a date for a product extension we're developing. Our conversation kept anchoring on the idea that pulling in a date was dependent on pushing out dates for other projects. Presenting two conflicting projects as requiring timeline tradeoffs wouldn't have caused me to blink an eye five years ago, but in this conversation it inspired a sort of instinctual revolt: with modern development techniques, I believe very few projects are essentially constrained by execution bandwidth. Some are constrained by approvals, others are constrained by cross-team and cross-functional handoffs, and many are constrained by missing decisions, but almost none should be constrained purely on time. Shifting blocks of time across project ## Why Amp Became Sebastian's Default Coding Harness DevFeed: [Why Amp Became Sebastian's Default Coding Harness]() Original publisher: [Read original article]() Author: Freek Van der Herten (freek@spatie.be) Published: 2026-08-11T10:30:28Z Content type: opinion Language: en Sources: [freek.dev - all blogposts]() Topics: [coding](), [User Experience]() Tags: [agents](), [ai](), [coding](), [developer-experience](), [experience](), [harness](), [mcp](), [tools](), [user-experience](), [verification]() ### AI overview Sebastian explains why Amp became his default coding harness, emphasizing user experience over model churn and describing AGENTS.md changes that reduced overzealous verification during everyday coding. ### Source excerpt Sebastian explains why Amp became his default coding harness, and why user experience now matters more to him than model churn. He also shares the AGENTS.md tweaks that reduced overzealous verification during day-to-day coding. Read more ## Does a PhD Pay Off? DevFeed: [Does a PhD Pay Off?]() Original publisher: [Read original article]() Author: Daniel Lemire Published: 2026-07-24T20:13:57Z Content type: opinion Language: en Sources: [Daniel Lemire]() Topics: [Learning](), [Machine learning]() Tags: [career](), [career-progression](), [cost](), [experience](), [industry](), [jobs](), [learning](), [machine-learning](), [tech-industry](), [university](), [work]() ### AI overview This opinion examines whether pursuing a PhD pays off financially and professionally. It argues that the historical earnings advantage is concentrated among people who become professors, while delayed earnings and career progression create substantial opportunity costs. It notes that machine learning may be an exception because PhDs are often expected for some industry roles. ### Source excerpt Every week, I discuss with people who want to get a PhD. For years, I have been advising people not to pursue a PhD. It may come as a surprise to some. You would expect people with a PhD to earn more money. Individuals who complete doctorates tend to have higher cognitive abilities and greater ... Continue reading Does a PhD Pay Off? ## Conversation design: How to make your AI Agent communicate like your team DevFeed: [Conversation design: How to make your AI Agent communicate like your team]() Original publisher: [Read original article]() Author: Fred Walton Published: 2026-06-18T16:55:07Z Content type: article Language: en Sources: [The Intercom Blog]() Topics: [AI Agent](), [Artificial Intelligence](), [Support]() Tags: [agent](), [ai](), [ai-agent](), [ai-agent-blueprint](), [ai-automation](), [communication](), [context](), [customer](), [customer-experience](), [customer-service](), [customers](), [designer](), [experience](), [process](), [responses](), [structure](), [support](), [teams](), [trust](), [voice]() ### AI overview This article explains how conversation design helps an AI Agent communicate consistently with a support team. It covers voice, tone, response structure, adapting language to customer context, and designing smooth handoffs to human support representatives. An Intercom example reports that a warmer opening message increased CSAT from 72.8% to 78.4%. ### Source excerpt If nobody on your team owns how your AI Agent communicates, it defaults to sounding like an LLM. Conversation design is the discipline that fixes that. ## You never stop cultivating taste DevFeed: [You never stop cultivating taste]() Original publisher: [Read original article]() Author: Loredana Crisan Published: 2026-06-08T16:26:36.446000Z Content type: opinion Language: en Sources: [Figma Blog]() Topics: [Learning](), [Artificial Intelligence](), [Tool]() Tags: [ai](), [creative](), [design](), [experience](), [learning](), [legibility](), [product-design]() ### AI overview This commentary argues that mastering a creative craft requires more than tools or technical skills. It emphasizes cultivating a distinctive point of view through practice, mentorship, feedback, and intentional decisions, especially in product design. ### Source excerpt Having the right tools can only take you so far. To become a master of your craft, you need to hone a point of view. ## Replay '26: My introduction to Temporal DevFeed: [Replay '26: My introduction to Temporal]() Original publisher: [Read original article]() Author: Jap Singh Published: 2026-05-21T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [Development](), [Hackathon](), [Artificial Intelligence](), [rate-limiting](), [Orchestration](), [Go Language](), [Java](), [Python]() Tags: [ai](), [company](), [conference](), [experience](), [hackathon](), [orchestration](), [rate-limiting](), [software](), [temporal-voices](), [vibe-coding]() ### AI overview A new Temporal employee recounts attending Replay '26 during their first week at the company. The article highlights developer discussions about AI-heavy workflows, rate limiting, enterprise use cases, clinical-trial monitoring, and workshops in Java, Go, and Python. ### Source excerpt Jap Singh joined Temporal and found himself at Replay '26 in his first week. His experience changed his view on the company. ## My experience at PyCon US 2026 DevFeed: [My experience at PyCon US 2026]() Original publisher: [Read original article]() Author: Pamela Fox (noreply@blogger.com) Published: 2026-05-20T05:41:47Z Content type: opinion Language: en Sources: [Pamela Fox]() Topics: [Python](), [MCP](), [MCP Server](), [Tutorial]() Tags: [2026](), [conference](), [experience](), [mcp](), [mcp-server](), [python](), [tutorial]() ### AI overview A personal recap of PyCon US 2026 describing the author's tutorial on building MCP servers, including its preparation, delivery to 84 attendees, and use of coding agents, agent frameworks, FastMCP, and Keycloak. ### Source excerpt I'm writing this post on the flight back from PyCon US 2026 in Long Beach, California. It was my second time attending PyCon, and it was a fantastic conference - a cornocopia of Python knowledge, but more importantly, a coming-together of developers across the Python ecosystem. I'll recap my PyCon US 2026 experience in this post, both what I contributed and what thousands of others contributed. First, a big old disclaimer: part of my job as a developer advocate at Microsoft is to attend conferences like PyCon, so I was able to expense my travel and spend my work days on my PyCon contributions. But that's also why I picked my job, as it gives me the excuse to do things that I'd want to do anyway, like attending the largest gathering of Python devs in the world. My tutorial Since I've been spending so much time on Model Context Protocol (MCP) in the past year, I submitted an idea to the PyCon CFP to run a tutorial walking developers through the process of building their first MCP server. I was thrilled that the tutorial was accepted, but nervous since I'd never delivered a tutorial at a PyCon before. Fortunately, I was able to test it out with the SF Python meetup group a few days before, and their feedback helped me streamline the tutorial experience immensely. I delivered the tutorial at PyCon to a packed room: 84 people, all seats filled, bright and early at 9AM on Wednesday morning, the first slot of the week-long conference. We started off the tutorial with an icebreaker, which included attendees inventing their own meaning for "MCP". Of course, my not-so-secret goal was for them to get to know their neighbor, to encourage pair debugging during the exercises. I alternated between slides and exercises in the 3.5 hours tutorial, trying to give attendees enough background knowledge while also giving them the time to get hands-on. We started off with attendees using MCP servers, via both coding agents (Copilot/Claude Code) and agent frameworks (Pydantic AI, Langchain ## From MySQL to CockroachDB at Groww: A Staged Production Migration DevFeed: [From MySQL to CockroachDB at Groww: A Staged Production Migration]() Original publisher: [Read original article]() Author: Sourav De,Vittal Pai,Paresh Saraf Published: 2026-03-11T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [CockroachDB](), [migration](), [Database Migration](), [MySQL](), [Replication](), [Concurrency](), [Cloud]() Tags: [architecture](), [cloud](), [cockroachdb](), [concurrency](), [customers](), [data](), [database-migration](), [distributed](), [experience](), [financial](), [india](), [latency](), [migration](), [mysql](), [parallel](), [production](), [replication](), [scale](), [sql](), [strategy]() ### AI overview This article describes Groww's staged production migration from a managed MySQL cloud instance to CockroachDB. It explains how MOLT supported staged data movement, continuous replication, verification, near-zero downtime, limited application changes, and rollback planning. ### Source excerpt Groww is India's #1 stock broker with 16 million active users and $11 billion in market cap. ## Stream of Consciousness Driven Development DevFeed: [Stream of Consciousness Driven Development]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2026-02-18T16:33:08Z Content type: opinion Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [Development](), [Specifications](), [Markdown]() Tags: [concepts](), [development](), [experience](), [markdown](), [pairing](), [specifications]() ### AI overview The author describes a pairing technique for conceptually complex specification work: write the problem, discussion, rejected approaches, proposed solution, and rationale in a Markdown file before changing the specification. This helps partners understand the reasoning and agree on an approach, though the author reports having tried it only once. ### Source excerpt This is something I just tried out last week but it seems to have enough potential to be worth showing unpolished. I was pairing with a client on writing a spec. I saw a problem with the spec, a convoluted way of fixing the spec. Instead of trying to verbally explain it, I started by creating a new markdown file: NameOfProblem.md Then I started typing. First the problem summary, then a detailed description, then the solution and why it worked. When my partner asked questions, I incorporated his question and our discussion of it into the flow. If we hit a dead end with the solution, we marked it out as a dead end. Eventually the file looked something like this: Current state of spec Problems caused by this Elaboration of problems What we tried that didn't work Proposed Solution Theory behind proposed solution How the solution works Expected changes Other problems this helps solve Problems this does *not* help with Only once this was done, my partner fully understood the chain of thought, and we agreed it represented the right approach, did we start making changes to the spec. How is this better than just making the change? The change was conceptually complex. A rough analogy: imagine pairing with a beginner who wrote an insertion sort, and you want to replace it with quicksort. You need to explain why the insertion sort is too slow, why the quicksort isn't slow, and how quicksort actually correctly sorts a list. This could involve tangents into computational complexity, big-o notation, recursion, etc. These are all concepts you have internalized, so the change is simple to you, but the solution uses concepts the beginner does not know. So it's conceptually complex to them. I wasn't pairing with a beginning programmer or even a beginning specifier. This was a client who could confidently write complex specs on their own. But they don't work on specifications full time like I do. Any time there's a relative gap in experience in a pair, there's solutions that are concep ## Two Engineers, One Mentoring Story: Why Both Sides Win DevFeed: [Two Engineers, One Mentoring Story: Why Both Sides Win]() Original publisher: [Read original article]() Author: Mila Kirova Published: 2026-01-27T14:05:40Z Content type: opinion Language: en Sources: [FreeAgent]() Topics: [Learning](), [Rails](), [Ruby]() Tags: [blog](), [career-progression](), [careers](), [culture](), [development](), [experience](), [insights](), [mentoring](), [rails](), [ruby]() ### AI overview FreeAgent engineers Carme and Mila discuss their three-year mentoring relationship, including how Carme strengthened her Ruby and Rails knowledge through guided study, practical exercises, and increasingly self-directed learning. ### Source excerpt We are Carme and Mila, both software engineers at FreeAgent, where we collaborate as mentee and mentor. In this blog we interview each other about our mentoring relationship. We're hoping that our experience is universal and sharing our insights will be useful to anyone who is interested in mentoring. If you like what you read, [...] ## What are billing credits? How billing credits improve cashflow and user experience DevFeed: [What are billing credits? How billing credits improve cashflow and user experience]() Original publisher: [Read original article]() Author: Joshua D'Costa Published: 2025-11-30T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Software as a service](), [User Experience](), [API]() Tags: [billing](), [customer-experience](), [customers](), [experience](), [forecasting](), [pricing](), [saas]() ### AI overview This tutorial explains billing credits as prepaid account value deducted as customers use a product. It covers prepaid, promotional, and refund-as-credit models, along with credit valuation, top-ups, expiration or rollover policies, ledger tracking, and customer-facing display. It describes how credits can support SaaS cash flow, spending visibility, forecasting, and customer experience. ### Source excerpt Learn what billing credits are, how credit-based pricing works, and how billing credits improve SaaS cash flow, forecasting, and customer experience. ## Astro 5.16 DevFeed: [Astro 5.16]() Original publisher: [Read original article]() Author: Matthew Phillips Published: 2025-11-20T00:00:00Z Content type: release Language: en Sources: [The Astro Blog]() Topics: [Astro](), [SVG](), [Command-line interface](), [Developer experience](), [Optimization](), [AI-assisted coding]() Tags: [agent](), [ai-agents](), [astro](), [cli](), [copilot](), [cursor](), [developer-experience](), [experience](), [optimization](), [svg]() ### AI overview Astro 5.16 introduces experimental SVG optimization through SVGO, interactive shortcuts for the preview server, and developer-experience improvements. It also improves automation by helping AI-assisted development tools bypass interactive prompts when configuring Astro integrations. ### Source excerpt Astro 5.16 brings experimental SVG optimization with SVGO, interactive CLI shortcuts, and improved developer experience across the board. ## Find the right mentor DevFeed: [Find the right mentor]() Original publisher: [Read original article]() Published: 2025-07-03T00:00:00Z Content type: opinion Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Code](), [Python](), [C]() Tags: [c](), [career](), [experience](), [hashmap](), [internals](), [mentor](), [python](), [startup]() ### AI overview A personal account of learning from an experienced system programmer who challenged the author to understand Python data structures and their implementation details. The article recommends finding mentors who encourage deep technical understanding. ### Source excerpt Original Tweet - https://x. com/sarmag77/status/1952147743935521188 Something similar happened to me when I was working at a startup right out of college... ## A decade in the tech industry DevFeed: [A decade in the tech industry]() Original publisher: [Read original article]() Published: 2025-05-30T00:00:00Z Content type: opinion Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Development](), [Ruby](), [Ruby on Rails](), [Angular]() Tags: [angular](), [career](), [development](), [experience](), [ruby](), [ruby-on-rails](), [tech]() ### AI overview A personal reflection on completing a decade in the technology industry, covering the author's first job after college, early software employment in India, startup work, changing career opportunities, and the technologies that were prominent at the start of the author's career. ### Source excerpt I just realised that I completed a decade in the tech industry this month. 17th May 2015, was my joining date in my first ever big boy job... ## The right way to interview DevFeed: [The right way to interview]() Original publisher: [Read original article]() Published: 2025-05-27T00:00:00Z Content type: opinion Language: en Sources: [Gaurav Sarma's Blog]() Topics: [bug](), [Job]() Tags: [bias](), [bug](), [career](), [experience](), [hiring](), [interview](), [pair](), [technical-interview]() ### AI overview The article argues that technical interviews should primarily use bug-squashing or pair-programming exercises, allowing interviewers to observe how candidates reason, respond to mistakes, challenge hypotheses, and work in practice. It also notes that these interviews require more preparation and may introduce subjective judgment and interviewer bias, while data-structures-and-algorithms questions can provide a more objective signal. ### Source excerpt Original Tweet - https://x. com/sarmag77/status/1938429909338362348 The best kind of interview is the bug squash or pair programmer round where both the interviewer and the candidate team up to solve a common problem... ## My experience using Junie for the past few months DevFeed: [My experience using Junie for the past few months]() Original publisher: [Read original article]() Author: Julien Published: 2025-05-11T11:38:55Z Content type: opinion Language: en Sources: [Thoughts, stories and ideas.]() Topics: [junie](), [Artificial Intelligence](), [IntelliJ IDEA](), [coding]() Tags: [agent](), [ai](), [coding](), [development](), [experience](), [intellij](), [jetbrains](), [junie](), [kotlin]() ### AI overview A personal review of using JetBrains Junie over several months. The author describes Junie's Code and Ask modes, IntelliJ-based IDE integration, terminal command option, pricing, and distinctions from other JetBrains AI products. They value its IntelliJ integration, Kotlin support, and test-first focus, but criticize its slowness and limited ability to accept only part of a proposed solution. ### Source excerpt Junie is one of the best coding agent I've been trying out so far. Very well integrated with IntelliJ, great for Kotlin, and the test first focus makes it quite good at coming out with good results. However, I do miss the capability to only accept part of a solution and it can be very slowwwwww. ## I've operated petabyte-scale ClickHouse® clusters for 5 years DevFeed: [I've operated petabyte-scale ClickHouse® clusters for 5 years]() Original publisher: [Read original article]() Author: Javi Santana Published: 2025-04-01T00:00:00Z Content type: opinion Language: en Sources: [Tinybird]() Topics: [clickhouse]() Tags: [clickhouse](), [clusters](), [experience](), [production](), [scale](), [the-data-base]() ### AI overview A practitioner shares lessons from operating ClickHouse at scale, including wins, failures, and production experience. ### Source excerpt What I learned operating ClickHouse at scale: the wins, the failures, and the lessons that only come from production experience. ## AI & Software Engineering: Time for optimism DevFeed: [AI & Software Engineering: Time for optimism]() Original publisher: [Read original article]() Author: Kaushik Gopal Published: 2025-03-09T22:22:02Z Content type: opinion Language: en Sources: [Kaushik Gopal's Site]() Topics: [Artificial Intelligence](), [Software Engineering](), [AI-assisted coding](), [Learning](), [Tool](), [Kotlin]() Tags: [ai](), [ai-for-code](), [code](), [engineering](), [experience](), [kotlin](), [software-engineering]() ### AI overview This opinion article argues that software engineers should view AI as a tool for learning and increasing their value, rather than focusing primarily on fears of job replacement. It emphasizes human judgment about what and how to build, while describing AI as useful for code generation and accelerated learning. The author gives an example of using Google's Notebook LM with an article and official Kotlin documentation to clarify Coroutine Dispatcher concepts in about 30 minutes instead of an estimated 2-3 hours. ### Source excerpt Many software engineers (myself included, not long ago) have been anxious about AI replacing our jobs. It's a natural concern. But I've been diving deep into using AI for software engineering. I've had a realization: We should stop worrying about job losses. Start seeing AI as a tool to make us more valuable. The key? Use AI for learning, not just code generation. Relying solely on AI for code generation is the trap. The truly valuable skill is judgment.1 The judgment to decide what to build and how to build it.2 AI excels at the actual building (code generation). Embrace this. It's inevitable. Most future code will be written|generated with AI. The good news? AI is amazing for learning. Some examples ### I think back to my undergraduate days. A concept didn't click? It meant a bike ride to the library. I'd search for textbooks, pull references, and try to piece it all together. Assuming the books were even available. Guess what I often did? I didn't bother. Today, I'd just pull up my phone and look it up. The internet was a game-changer for students. AI is the next game-changer for all of us willing to learn. A more recent example: I'm doing an upcoming Fragmented episode on an article that my friend Colin3 wrote on Coroutine Dispatcher use. I understood about 75% on the first pass. But a few gaps remained, especially around how they related to Coroutine fundamentals. I needed to brush up. Without AI, my process would have been: Open a bunch of articles and docs. Read each one thoroughly. Synthesize the information mentally. Connect the dots with the article. Time: 2-3 hours, plus significant mental bandwidth. With AI: Uploaded Colin's article and official Kotlin docs to Google's Notebook LM. Asked targeted questions, addressing my knowledge gaps directly. Time: 30 minutes to reach a firm understanding. What would have taken 2-3 hours took about 30 minutes.4 And I understood the concepts better. AI is your opportunity to level up. Learn faster. Position yourself to [Next page]()