# Work Published articles for Work. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Working Remotely DevFeed: [Working Remotely]() Original publisher: [Read original article]() Author: Khan Academy Published: 2017-10-02T22:00:00Z Content type: opinion Language: en Sources: [Khan Academy]() Topics: [Job]() Tags: [engineering](), [news](), [remote](), [remote-work](), [time](), [web-frontend](), [work]() ### AI overview Scott Grant reflects on working remotely after moving from Silicon Valley to Kingston, Ontario. He explains how remote work expands access to technology jobs outside major hubs and discusses the discipline and routine needed to work effectively. ### Source excerpt By Scott Grant When my wife and I left Silicon Valley in sunny California to return to my ... Read more ## Khan Academy: a new employee's primer DevFeed: [Khan Academy: a new employee's primer]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-07-20T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [Job]() Tags: [developer](), [developers](), [education](), [engineering](), [news](), [onboarding](), [organization](), [people](), [startup](), [web-frontend](), [work]() ### AI overview Riley Shaw describes the onboarding experience after joining Khan Academy's developer team. The article highlights advance communication, supportive team messages, an assigned onboarding mentor, and early one-on-one time with a manager. ### Source excerpt By Riley Shaw I recently joined the developer team at Khan Academy. Since arriving I've been surprised by ... Read more ## Time Management at Khan Academy DevFeed: [Time Management at Khan Academy]() Original publisher: [Read original article]() Author: Khan Academy Published: 2016-07-25T22:00:00Z Content type: opinion Language: en Sources: [Khan Academy]() Topics: [To-Do](), [Job]() Tags: [email](), [engineering](), [learn](), [management](), [meetings](), [news](), [team](), [time-management](), [web-frontend](), [work]() ### AI overview Khan Academy employees share approaches to managing their time, including weekly Trello to-do lists, scheduling uninterrupted work around meetings, and organizing tasks around energy and responsiveness needs. ### Source excerpt By Multiple Everyone at Khan Academy received a plea recently: I'm hoping to organize a blog post that ... Read more ## OpenAI research examines how workers incorporate AI tasks beyond their usual occupations DevFeed: [OpenAI research examines how workers incorporate AI tasks beyond their usual occupations]() Original publisher: [Read original article]() Published: 2026-09-16T09:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [ChatGPT]() Tags: [ai](), [chatgpt](), [global-affairs](), [openai](), [report](), [research](), [tasks](), [work](), [workflow]() ### AI overview OpenAI Economic Research analyzes more than 1.5 million work-related ChatGPT messages to examine whether workers repeatedly use AI for tasks outside their usual occupations. The findings suggest that some cross-occupation tasks become recurring parts of workers' AI use and that work design matters alongside access to AI tools. ### Source excerpt New OpenAI Economic Research shows how workers use AI beyond traditional roles and which new activities become recurring parts of their work. ## The 7 Essential Parts of Your Online Presence DevFeed: [The 7 Essential Parts of Your Online Presence]() Original publisher: [Read original article]() Author: Manish Shivanandhan Published: 2026-09-15T21:07:31Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [Website]() Tags: [job-search](), [linkedin](), [open-source](), [personal](), [portfolio](), [profile](), [social-media](), [work]() ### AI overview This article explains seven parts of a strong online presence, beginning with a professional profile and personal website. It emphasizes consistency, clear descriptions of problems solved and outcomes achieved, and using a personal website to present work, case studies, and contact information. ### Source excerpt Your online presence often gives potential employers, clients, partners, and recruiters their first impression of you. It's likely what they see before they ever meet you. They search your name, read ## Making the Internet a Bit Less Sh\*t: Inside Resn's Digital Experiences DevFeed: [Making the Internet a Bit Less Sh\*t: Inside Resn's Digital Experiences]() Original publisher: [Read original article]() Author: resn Published: 2026-09-14T11:30:10Z Content type: article Language: en Sources: [Codrops]() Topics: [Web](), [Internet]() Tags: [articles](), [brand-experiences](), [breakthrough-energy](), [collaboration](), [creative-studio](), [creative-technology](), [digital-experiences](), [global](), [interactive-websites](), [internet](), [projects](), [remote](), [resn](), [savor](), [squarespace-foundations](), [studio-agency-spotlight](), [technology](), [tracing-art](), [web](), [web-design](), [work]() ### AI overview Resn is a boutique creative studio founded in 2004 that creates brand, content, and digital experiences for global brands and emerging innovators. The article introduces the studio's remote, international team, history, creative approach, and selected recent work, including an interactive online experience for Squarespace's brand guidelines. ### Source excerpt A look at how Resn combines brand, content, technology and a healthy disregard for boring websites to create digital experiences people actually want to explore. ## Generating running routes with GPT-6 Astra and ChatGPT Work DevFeed: [Generating running routes with GPT-6 Astra and ChatGPT Work]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-12T23:56:42Z Content type: opinion Language: en Sources: [Simon Willison](), [Simon Willison's Weblog]() Topics: [ChatGPT](), [Large Language Model](), [GeoJSON](), [Code](), [d3]() Tags: [agent](), [ai](), [ai-2-235](), [chatgpt](), [chatgpt-204](), [code](), [d3](), [d3-15](), [generative-ai](), [generative-ai-1-981](), [geospatial](), [geospatial-85](), [gpt](), [gpt-6-astra](), [gpt-6-astra-9](), [llms](), [llms-1-947](), [map](), [openai](), [openai-463](), [python](), [skills](), [skills-15](), [work]() ### AI overview The article describes using ChatGPT Work with GPT-6 Astra to generate 5K and 10K running routes from OpenStreetMap data, producing an embedded visualization and downloadable GPX and GeoJSON files. It also criticizes the lack of visibility into the generated Python code and the loss of that code after thread compaction. ### Source excerpt Here's a neat thing I had ChatGPT Work with GPT-6 Astra (Max) do this morning: I live at . Figure out 5K and 10K running routes from me that loop from my house. Use OSM data. It worked for 27 minutes and produced exactly what I'd asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here's that 5K route: When I asked it how it had created the route, it replied: I used Nominatim to locate the address and Overpass to download local OpenStreetMap roads and trails, then calculated the loops locally. Frustratingly, the actual code it ran and exact details of what it did weren't visible to me in the ChatGPT UI. I see this lack of transparency is an anti-feature. By the time I thought to ask for a copy of the Python code it had used, ChatGPT was unable to provide it. This appears to be because the thread had been compacted. I think any LLM system that uses compaction needs to both preserve the pre-compacted text and make that text available via agent tool calls, to protect against this kind of problem. As for displaying the map to me, that used the visualize skill. It created a file called /workspace/el-granada-5k-share.html to embed directly into the ChatGPT UI. Here's a copy of that HTML, which starts like this:

El Granada harbor loop

5.1 km
Map data © OpenStreetMap contributors
) Original publisher: [Read original article]() Author: Peter Lawrey (noreply@blogger.com) Published: 2026-09-12T07:32:17Z Content type: opinion Language: en Sources: [Vanilla Java]() Topics: [Job](), [Learning](), [Artificial Intelligence](), [Code]() Tags: [ai](), [career](), [code](), [job](), [learning](), [opinion](), [work]() ### AI overview An opinion article about progressing in a career by creating growth opportunities within a current role. It recommends teaching others, understanding users and systems, improving quality and efficiency, taking responsibility for outcomes, and focusing on work that AI cannot easily automate. ### Source excerpt When you start a new role, many challenges are placed on you. Once you have been in a role for a while, you may feel like you aren't learning as much, your career isn't progressing, and you wonder what job you might move to next. Having been in that situation many times, my suggestion is that rather than waiting to be given challenges or the next role, you take the opportunity to challenge yourself to grow in your current role. This doesn't mean accepting a role with too little growth, but rather see if there are opportunities to grow while you have some capacity, if you drive them. For example, imagine the roles you would wish to have, how much of that could you be doing now without being asked, possibly in your own time? I am not suggesting doing more unpaid work, rather extending the work you have to benefit your career. Ways to extend your current role to help you grow Teach others. Often, you don't really understand something until you have had to explain it to someone else. Understand the people using your work. Broaden your understanding of the people or systems using what you are producing. How can what you're doing be more efficient, high-quality, more valuable to the end users, and easier to maintain? Take responsibility for a larger part of an outcome. Instead of only producing a piece of work, help define what success means, consider alternatives, check whether it works in practice and learn from what happens afterwards. Say you are working heavily with AI. Explore all the ways it currently fails, rather than sticking to what it does safely. Anything AI does easily now will be increasingly automated, and there probably isn't a future in that. Instead, focus on what AI can't do and where you add value. That is likely to be in demand. Consider two approaches to using AI to write for illustration: 2,000 words of content on a subject (or 200 lines of code @ ~10 words per line). You could prompt it for an answer of about 2,500 words and then edit out anything ## Put Redis data and engineering guidance to work in ChatGPT Work DevFeed: [Put Redis data and engineering guidance to work in ChatGPT Work]() Original publisher: [Read original article]() Author: Olga Lopaci Published: 2026-09-11T00:00:00Z Content type: release Language: en Sources: [Redis Blog]() Topics: [Developer Tools](), [AI Chat](), [AI Bots]() Tags: [agent-skills](), [chatgpt](), [codex](), [engineering](), [observability](), [rag](), [redis](), [review](), [security](), [skills](), [tech](), [work]() ### AI overview Redis launched a development plugin for ChatGPT Work and Codex that supplies current Redis guidance for writing, reviewing, and troubleshooting code. It also describes connecting Redis data to ChatGPT Work's Data agent for plain-language exploration and investigation. ### Source excerpt Redis has launched a development plugin that brings current Redis engineering guidance into ChatGPT Work and Codex. It helps teams write, review, and troubleshoot Redis code without switching between documentation and development tools. Alongside Ope... ## (Re)introducing Developer Story DevFeed: [(Re)introducing Developer Story]() Original publisher: [Read original article]() Author: Philippe Beaudette Published: 2026-09-10T18:01:54Z Content type: news Language: en Sources: [Stack Overflow Blog]() Topics: [Programming](), [Code](), [Large Language Model](), [datasets]() Tags: [career](), [community](), [company](), [cv](), [datasets](), [developer](), [identity](), [llms](), [news](), [privacy](), [profile](), [programming](), [se-stackoverflow](), [se-tech](), [skills](), [work]() ### AI overview Stack Overflow is reintroducing Developer Story, a profile feature designed to showcase developers' careers, specialties, contributions, and technical identity. The article also introduces Stack Identity, a broader vision for verified proof of developer work, with privacy controls and integrations for verified contributions from other sites. ### Source excerpt For the past few years, we've been looking at ways to bring a little more of the individual developer back to Stack. ## 47,000 job listings reveal the engineering roles that AI is creating DevFeed: [47,000 job listings reveal the engineering roles that AI is creating]() Original publisher: [Read original article]() Author: Jennifer Riggins Published: 2026-09-10T13:09:28Z Content type: news Language: en Sources: [The New Stack]() Topics: [Machine Learning & Artificial Intelligence](), [AI Development](), [Machine learning]() Tags: [ai](), [ai-engineering](), [ai-strategy](), [andela](), [engineering](), [jobs](), [machine-learning](), [post](), [skills](), [sponsor-andela](), [sponsored](), [sponsored-post](), [tech-careers](), [work]() ### AI overview Andela's analysis of 47,000 Fortune 500 engineering job postings identifies emerging AI-related roles formed by combining established skill sets. The article argues that organizations should use AI to delegate suitable work while retaining human expertise and specialization. ### Source excerpt Every major transformation in tech has led to roles merging, then new ones emerging. Friction between developers and operations drove The post 47,000 job listings reveal the engineering roles that AI is creating appeared first on The New Stack. ## Blizzard union workers ratify historic contract covering 1,900 employees DevFeed: [Blizzard union workers ratify historic contract covering 1,900 employees]() Original publisher: [Read original article]() Author: Chris Kerr Published: 2026-09-09T12:59:56Z Content type: news Language: en Sources: [gamedeveloper]() Topics: [Microsoft](), [Generative AI](), [Xbox]() Tags: [ai](), [company](), [generative](), [layoff](), [microsoft](), [news](), [remote](), [teams](), [work](), [xbox]() ### AI overview Blizzard union workers ratified a contract covering 1,900 employees. The agreement includes generative AI usage safeguards, wage increases, hybrid and remote-work benefits, layoff protections, severance, and recall rights. ### Source excerpt Union members have secured guardrails around generative AI usage, layoff protections, remote and hybrid work benefits, and more. ## GPT-6 Astra: The next generation in intelligence for work DevFeed: [GPT-6 Astra: The next generation in intelligence for work]() Original publisher: [Read original article]() Published: 2026-09-09T11:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [computer-use](), [coding](), [Software Engineering](), [Latency]() Tags: [api](), [chatgpt](), [codex](), [coding](), [computer-use](), [developer](), [engineering](), [gpt](), [latency](), [model](), [openai](), [product](), [software-engineering](), [work](), [workflows]() ### AI overview GPT-6 Astra is presented as a model for business work, with computer-use capabilities, coding support, and use within existing applications and workflows. ### Source excerpt Meet GPT-6 Astra, OpenAI's most capable model for business, with advanced reasoning, computer use, and stronger writing and design judgment. ## Loop engineering: stop prompting, start looping DevFeed: [Loop engineering: stop prompting, start looping]() Original publisher: [Read original article]() Author: Anthony Viard Published: 2026-09-08T16:00:00Z Content type: article Language: en Sources: [Postman Blog]() Topics: [Loop Engineering](), [AI Agent](), [AI-assisted coding](), [API]() Tags: [2026](), [agent](), [agentic](), [agents](), [ai](), [ai-agents](), [ai-coding](), [api](), [api-testing](), [blog](), [code](), [coding-agents](), [developer](), [engineering](), [general](), [guide](), [idea](), [loops](), [model](), [post](), [postman-cli](), [tool](), [verify](), [work]() ### AI overview This article explains loop engineering as a way to improve AI coding agent reliability. Instead of relying on a single prompt, the system repeatedly generates code, runs it against a real API or other source of truth, verifies the result, and decides whether to stop or continue. The article distinguishes this outer verification loop from the inner ReAct tool-use cycle and presents a reproducible setup for allowing an agent to correct its own mistakes. ### Source excerpt Stop prompting your AI agent, start looping. A guide to loop engineering: wire a real API call in as the oracle so generated code stops guessing. The post Loop engineering: stop prompting, start looping appeared first on Postman Blog. ## Report: FuturLab lays off devs without informing team leads or managers DevFeed: [Report: FuturLab lays off devs without informing team leads or managers]() Original publisher: [Read original article]() Author: Chris Kerr Published: 2026-09-08T13:23:06Z Content type: news Language: en Sources: [gamedeveloper]() Topics: [Development]() Tags: [cancellation](), [company](), [developer](), [news](), [project](), [report](), [statement](), [work]() ### AI overview FuturLab laid off seven employees after cancelling a non-PowerWash-related project that had been in development for two to three years. Sources alleged that affected workers were left without assignments and that managers and team leads were not informed about the layoffs. The company later described the situation as part of a restructuring process. ### Source excerpt Sources have also accused the Powerwash Simulator developer of obfuscating the truth by asking staff to refer to those laid off as 'the leavers.' ## Introducing ChatGPT Images 2.5 DevFeed: [Introducing ChatGPT Images 2.5]() Original publisher: [Read original article]() Published: 2026-09-08T11:30:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [API]() Tags: [api](), [chatgpt](), [codex](), [feature](), [generate](), [generation](), [gpt](), [images](), [latency](), [mobile](), [models](), [product](), [speed](), [web](), [work](), [workflows]() ### AI overview ChatGPT Images 2.5 is a new image model with sharper details, more precise multi-turn editing, improved reference-photo fidelity, richer textures, and up to 50% lower generation latency than Images 2.0. The release adds creative controls in ChatGPT and introduces GPT-Image-2.5 Flare and Sunburst in the API. ### Source excerpt ChatGPT Images 2.5 helps turn your ideas, sketches, and reference photos into more personalized, polished images that better reflect your ideas. ## Measuring real-time performance per dollar under continuous load: CostBench's first end-to-end results DevFeed: [Measuring real-time performance per dollar under continuous load: CostBench's first end-to-end results]() Original publisher: [Read original article]() Author: Tom Schreiber; Lionel Palacin Published: 2026-09-08T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [AI, ML & Data Engineering](), [Amazon Redshift]() Tags: [analytics](), [architecture](), [benchmark](), [bigquery](), [clickhouse](), [cloud](), [cost](), [data](), [performance](), [real-time](), [serverless](), [streaming](), [systems](), [tracing](), [work]() ### AI overview CostBench benchmarks the cost and performance of real-time cloud data warehouses under continuous ingestion and query load. It compares ClickHouse Cloud with Snowflake, BigQuery, and Redshift Serverless, reporting better end-to-end performance per dollar for ClickHouse Cloud in the tested workload. ### Source excerpt CostBench puts cloud data warehouses under continuous load. Across the complete path from fresh data to fast answers, ClickHouse Cloud delivers 412-1,996x better performance per dollar. ## Weekly Wacky Question: What Constitutes a Meal? What Constitutes an Active User? DevFeed: [Weekly Wacky Question: What Constitutes a Meal? What Constitutes an Active User?]() Original publisher: [Read original article]() Author: Bo French Published: 2026-09-06T12:00:48Z Content type: opinion Language: en Sources: [Atomic Object]() Topics: [Software](), [coding]() Tags: [atomic-accelerator](), [developers](), [software](), [work]() ### AI overview The article describes a "Weekly Wacky Question" activity in which software consultants discuss playful hypothetical questions. It explains that the questions prompt problem framing, scope definition, clarification, and consideration of edge cases--habits associated with software development and consulting work. ### Source excerpt Crikey! What a sight we have here! We have a flock of software consultants at a common meeting ground for them in their ecosystem, the communal whiteboard. Many moons ago, this was not a particularly common meeting ground for them, but now it's a place of rigor and banter and full of life. They seem [...] The post Weekly Wacky Question: What Constitutes a Meal? What Constitutes an Active User? appeared first on Atomic Spin. ## The economics of agent scale: tokens, ROI, and building platforms for AI-first teams (Part 2) DevFeed: [The economics of agent scale: tokens, ROI, and building platforms for AI-first teams (Part 2)]() Original publisher: [Read original article]() Author: Eira May Published: 2026-09-03T07:40:00Z Content type: article Language: en Sources: [Stack Overflow Blog]() Topics: [AI Bots](), [ai observability]() Tags: [agent](), [agentic](), [agentic-ai](), [agents](), [ai](), [ai-agents](), [business](), [cost](), [developers](), [engineering](), [engineering-leadership](), [google](), [infrastructure](), [leaders-of-code](), [model](), [observability](), [php](), [platform](), [platform-engineering](), [podcast](), [scale](), [science](), [tooling](), [work]() ### AI overview A podcast discussion on operating AI agents at scale, focusing on token efficiency, cost governance, context management, and platform tooling and observability. ### Source excerpt Andi Gutmans, head of Agentic Data Cloud at Google, returns for the second half of his Leaders of Code conversation to talk through the cost and infrastructure side of agentic development. ICYMI, part one covered judgment, code review, and data activation. ## Hemut: Building the Internet of Freight on Real-Time Data DevFeed: [Hemut: Building the Internet of Freight on Real-Time Data]() Original publisher: [Read original article]() Author: Tim Graczewski Published: 2026-08-27T20:23:15Z Content type: article Language: en Sources: [Confluent: Data in motion]() Topics: [data](), [real-time](), [Confluent Cloud](), [Streaming](), [Artificial Intelligence](), [Network](), [Software](), [Cloud](), [Operating system]() Tags: [2025](), [2026](), [ai](), [business](), [ceo](), [cloud](), [confluent](), [confluent-cloud](), [cost](), [data](), [efficiency](), [erp](), [network](), [production](), [real-time](), [real-time-data-streaming](), [software](), [streaming](), [supply-chain](), [work]() ### AI overview Hemut uses Confluent Cloud and real-time data streaming to provide an AI-native operating system for trucking carriers and brokers. Its platform combines ERP and TMS capabilities to automate tasks, improve fleet efficiency, reduce operating costs, and support the company's vision of an Internet of Freight. ### Source excerpt Hemut uses Confluent, real-time data streaming, and AI to automate trucking operations, improve fleet efficiency, and build the Internet of Freight. ## How to Work With Your Client's Next (Or Previous) Developer DevFeed: [How to Work With Your Client's Next (Or Previous) Developer]() Original publisher: [Read original article]() Author: Eric Karkovack Published: 2026-08-25T11:20:05Z Content type: article Language: en Sources: [Speckyboy Design Magazine]() Topics: [client](), [Processes]() Tags: [developer](), [developers](), [freelance-business](), [freelance-career](), [freelance-design](), [how-to](), [payment](), [wordpress](), [wordpress-agency](), [work]() ### AI overview This article offers practical advice for managing website handoffs between a client's current and incoming developers. It recommends staying professional, documenting processes, responding promptly, avoiding conflict, and ensuring outstanding payments are settled before transferring site assets or access. ### Source excerpt Website handoffs between developers can get awkward. Learn how to stay professional, get paid before transferring assets, and share logins, licenses, and access without creating risk. The post How to Work With Your Client's Next (Or Previous) Developer appeared first on Speckyboy Design Magazine. ## When non-devs open PRs DevFeed: [When non-devs open PRs]() Original publisher: [Read original article]() Author: Anton Zaides Published: 2026-08-25T06:01:00Z Content type: opinion Language: en Sources: [Manager.dev]() Topics: [Pull Request](), [Development](), [Linear](), [Artificial Intelligence]() Tags: [ai](), [article](), [code](), [jira](), [linear](), [reviews](), [work]() ### AI overview An opinion article examines the challenges and potential benefits of allowing non-engineers, including product managers and designers, to open pull requests on a software codebase. It discusses review responsibility, boundaries, scaling concerns, and reduced communication cycles, while citing Linear usage data about non-engineer code contributions and AI feature use. ### Source excerpt What to watch out for when letting non-engineers open PRs on your codebase ## Introducing the Admin plugin for ChatGPT Work and Codex DevFeed: [Introducing the Admin plugin for ChatGPT Work and Codex]() Original publisher: [Read original article]() Published: 2026-08-25T00:00:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [codex](), [Authorization](), [Monitoring](), [Slack]() Tags: [ai-adoption](), [analytics](), [chatgpt](), [codex](), [enablement](), [microsoft-teams](), [monitor](), [monitoring](), [onboarding](), [reduce](), [slack](), [tools](), [update](), [work](), [workflow]() ### AI overview OpenAI introduces an Admin plugin for ChatGPT Work and Codex that lets administrators analyze workspace usage, manage members and permissions, adjust limits, and handle requests in one conversation. It also supports recurring checks and workflows that route approvals to Slack or Microsoft Teams while keeping changes within existing roles and permissions. ### Source excerpt Use the Admin plugin for ChatGPT Work and Codex to analyze workspace usage, manage members and permissions, adjust limits, and act on admin requests. ## Anger, Anxiety and Agency DevFeed: [Anger, Anxiety and Agency]() Original publisher: [Read original article]() Author: Armin Ronacher Published: 2026-08-24T00:00:00Z Content type: opinion Language: en Sources: [Armin Ronacher]() Topics: [Artificial Intelligence](), [context]() Tags: [agents](), [ai](), [emotion](), [thoughts](), [work]() ### AI overview The author argues that anxiety and uncertainty are more constructive responses than anger to AI and agents' effects on the technology industry. They discuss concerns about changing professional skills, how productivity gains may be distributed, and tensions between companies and large AI labs. ### Source excerpt Sean Goedecke wrote a post arguing that you should never be angry at work -- a post with which I strongly agree. Anger can be a useful signal, but being angry at work rarely improves the situation. More often, it makes life worse for the people around you, many of whom have no more power over the source of your anger than you do. I did learn that lesson, but it did not come naturally. One thing in particular that I learned is that in a company there is a shared vision, and if you don't agree with it and are not in a position to change it, you should not start a mutiny, not even a small-scale one. Nothing good comes from that. In the discussion around that topic, one of the most upvoted comments on the Lobsters thread asked a question I had to think about quite a bit: How can you work in tech right now and not be angry? In the context of the thread, this was clearly also about AI and agents. For me, the emotions I would expect in tech vis-a-vis these new developments are disorientation and anxiety, but not anger. Anxiety as an emotion does not require someone to blame. Right now, I find it reasonable to feel anxious about an uncertain future. Who knows what our professions will turn into and what kind of world my kids will find themselves in when they enter the workplace? And if you've been in the industry for a long time, will the skills you've spent years acquiring still matter? But anger is different from anxiety because anger needs to be directed somewhere. The feeling of anger suggests that somebody or something is doing something to you. Who are you going to be angry at and why are you angry in the first place? One narrative that is pretty pervasive is that if AI will usher in productivity gains, those gains are going to benefit companies rather than employees. And well at least someone at Meta wants that. Yet I also find that plenty of people in leadership positions express doubt about AI. They see that an increasing share of their costs is being funneled direc [Next page]()