Category: Daily Reading List

There’s a lot today about the strategy around using and rolling out AI at scale.

[blog] Mastering Gemini Computer Use : A Comprehensive Hands-on Guide. Instead of creating brittle scripts that try and parse UI elements, what if you worked with a model that could “see”? That’s computer use, and what Romin explains here.

[article] The future of engineering at Nationwide, Comcast, TD, and HPE. These are all wonderful takeaways. I’d be surprised if any large enterprise—I haven’t met one—has truly done any of this at scale, but it’s the right foundational beliefs.

[article] Markdown Is Becoming the Application Layer of AI Apps. Fascinating take. Maybe not wrong. But it’s a shift for people to put even more domain behavior into prose.

[blog] Beyond Gemini Enterprise: Google’s Hidden AI Superpower. A great model is a must-have. We’ll keep making those. But it’s about more than just an LLM, and Google’s got a unique value proposition up and down the stack.

[article] Agent Memory. Excellent deep dive into the various types of agent memory and considerations for each.

[blog] Cloud CISO Perspectives: How Google Cloud Security uses AI internally. The use of a self-reflective loop seems important here.

[article] The AI jobs debate just got messier. Sometimes the data refuses to bend to the narrative. Or, we just assume nobody knows what’s going on right now. I’m voting for the latter.

[article] Claude Code turned every engineer into three. Now companies need more product thinkers. Yes, knowing syntax or obscure domain knowledge isn’t the most valuable thing today. Instead, can you understand higher-order problems and own the journey towards the goal?

[blog] Build reliable multi-agent applications with ADK Go 2.0. Discover our new graph-based workflow engine, built-in human-in-the-loop, and dynamic orchestration. If you’re using Go for AI workloads (great choice!), this is the best way to build AI agents.

[article] Your Talent Strategy Has to Keep Up with Your AI Transformation. Be smart about how you approach a plan for new talent, and how you invest in your current staff.

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I liked some of the manager-focused pieces today, as that’s an under-served audience right now. There’s plenty of content for how individuals use AI, but much less about the impact and role of managers.

[blog] Ask an AI expert: What exactly is the full stack? The central Google team asked me some questions about full-stack AI. Here’s the result.

[article] Uber’s journey of measuring AI impact on developer productivity. I didn’t listen to the episode, but the takeaways published here are solid.

[blog] Five essential testing patterns for AI agent development. Great post from Karl. It’s easy to get AI to generate shallow tests for your codebase. Are you asking for and seeking a more comprehensive testing strategy?

[article] Where is the flattening of engineering organizations actually happening? Some of these results may surprise you. Reorganization is much more common than layoffs, and the top is flattening faster than other layers.

[article] AI Adoption Is Overloading Your Middle Managers. We need *more* investment in middle management because of the AI transition?

[blog] Paging Charity! How can engineering leaders avoid becoming Bond villains? The number one job of every manager/leader is to win at business. Not build great teams, not coach the next generation. Those things matter a ton. But you won’t get the opportunity to do those things if the team doesn’t matter.

[article] AI Tools Accelerates Coding, but Not Overall Software Delivery, GitLab Research Finds. When I see headlines like this, it’s an indicator that these teams haven’t yet done the required changes to teams and workflows.

[blog] Locally test your Cloud Run service code that writes to Google Sheets. You can’t test everything locally when dealing with cloud services, but many things you can.

[article] CEOs, CIOs clash over AI’s value. Oooh, enterprise drama. Each side probably expect different outcomes, or at least on different timelines.

[blog] Antigravtiy CLI Plugin for Claude Code. Mix models, mix harnesses, whatever. You don’t need to use one stack for everything, and it may be prohibitive to do so!

[blog] The Problem is Prompt Debt. Less prose, more firm direction. And fewer hand-written prompts, more generated.

[article] The AI era requires a different kind of experimentation. Food for thought. Have you thrown our your own playbook and assumptions? Might be time.

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Most of my “building” nowadays is for fun, for blogs, or for customer demos. But today I had to take a spreadsheet of data and enter records one-at-a-time into a web app. No thanks. Broke out the Google Antigravity CLI and took a few minutes to build a Playwright script that looped through the rows and filled out the web form. Achievement unlocked.

[blog] Learn Anything With My /teach Skill. Neat skill from Matt. He talks about it for Claude Code, but there’s nothing specific to that harness. Run this in your favorite environment to get a personalized teacher.

[blog] Writing Loops, Not Prompts, Explained. Skip the “write loops not prompts” hysteria. There’s a place for automating recurring work. But prompts are still part of the equation.

[paper] Developer Productivity in the Age of Generative AI: A Psychological Perspective. My colleague wrote up his Master’s Thesis on an interesting topic and it’s available here to read.

[blog] Hidden Technical Debt of AI Systems: Agent Harness. What an insightful read. I hadn’t thought about production versus training harnesses. The idea of the harness melting into the model is something we’ve had as well.

[blog] Moving Past “Demos Over Memos”: The Future of AI in Enterprise Product Development. Fair points from Jason, and I should change how I refer to this idea. We need MORE than just vibe coded demos to explain ideas, understand market fit, and build alignment.

[blog] How to apply professional design principles in AI app development. Really good. It’s easy (and I’m speaking to myself) to just accept the stylized UI that comes back from the AI tool. But this post points out the eight areas where you can push back to get a stand-out result.

[blog] Make AI Boring Again. Smart take, as always. Learn these tools, figure out the best use, and make it boring.

[blog] The Coming Divide: AI-Native or Left Behind. I get it. This one is a choice. You can choose to use AI or not. Just like you can choose to read books or not. But then own the outcome.

[blog] Optimizing cloud economics with linear elastic caching. Good thinking, useful experiment, and legitimate results.

[article] The Two-Organizations Problem. There’s the presented view of the org (via dashboards, townhalls, etc) and the lived org (how we experience it day to day). Those are not always the same.

[blog] Building in the Age of Collaborative Coding. I haven’t seen a ton written about how mature teams work together with AI agents and tools.

[blog] Demystifying A2UI: How to Make AI Agents “Speak UI” in Your App. I’m seeing more where generative UIs—giving LLMs the ability to lay out a screen based on provided components and data—make sense.

[blog] Conference talks in an AI driven world are likely to get boring, or need to dramatically change. Let’s watch presenters wait for prompt responses! That sounds super fun. Not really. We’ve got to rethink tech events to ensure they don’t turn crazy boring.

[blog] Here’s how Gemini can help you avoid jetlag. I was very skeptical of this claim. So I tried it on my upcoming trip to India. Wasn’t half bad.

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How well my favorite sports team plays should have no bearing on my happiness. Alas, that’s not the case. But, my Padres won three in a row, which partially explains my good mood this week.

[blog] Why Are Agents Buying the Same Answer Twice? That’s a darn good question. Devin wonders why we’re computing stable answers over and over again, versus storing and recalling them.

[blog] Who Wrote That Query? You need the right visibility if you’re going to troubleshoot effectively. I like that our MCP Toolbox for Databases now makes it possible to trace a SQL query back to the agent prompt.

[site] ThoughtWorks Radar – April 2026. I don’t know how I missed this back in April. But scan through what technologies are ready for adoption and trial.

[blog] Resilience Patterns Can Make Your System Less Resilient. Can you make your system worse by applying retries, circuit breakers, and fallbacks? Yes, yes you can.

[blog] Brownfield modernization with Antigravity. New stuff is fun, but we’re all going to spend most of our AI coding effort on existing systems.

[blog] Configuration belongs in a database. Maybe a hot take? But the argument here holds water with me.

[article] AI coding token costs are on track to rival human payroll. I’m not sure it’s wise to try and project current behavior too far out. We’re still figuring out these tools, models, and pricing schemes. Related.

[article] Stop Getting Good at Protocols. Get Good at Agent Experience. Be good at both? Even after reading this, I’m not sure you can be great at AX without understanding the ways to make it happen. But I get the point to not obsess over fast-changing implementations.

[article] Demand for AI-ready coders skyrockets in 5 years. So the roles are changing, not disappearing? I think everyone not invested in the doomer outcome expected this to be true. Related.

[blog] Ping Pong Pairing with Antigravity. Aja applies a proven technique but with AI agents instead of humans.

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We’re in process of doing our quarterly “check-ins” towards our personal goals. It’s a great moment for me to reflect and appreciate what my team has accomplished already!

[blog] How To Measure Development Productivity? Should you measure activity? Or output? Those are flawed categories, although they can have value at the team level. This post reminds us to consider desired outcomes and measure that.

[blog] Introducing computer use in Gemini 3.5 Flash. When you need/want agents that can “see” and reason across browsers and desktop, this sort of capability will be intensely valuable. Great to see it natively integrated into the Gemini Flash model.

[article] The Mom-and-Pop SaaS era has arrived. How many great ideas never got built because the cost of realizing them with software was too high? Not anymore.

[article] Lost confidence. When you can’t honestly quantify your confidence about the outcome, how do we proceed? Some really useful techniques called out here.

[article] Europe’s cloud sovereignty push may backfire. Related to the above point, I can’t predict how this goes. Doesn’t seem like it’ll go well.

[blog] Build Cross-Language Multi-Agent Team with Google’s Agent Development Kit and A2A. Cool demo, including downloadable source code. How do you make agents built in different languages work together? Here’s how.

[article] The AI Productivity Bill Comes Due in Production. The bottleneck probably moved downstream, and the work itself changes shape to be more about supervision.

[article] Kubernetes in the Age of AI. It’s a runtime for model inference, a host for agents, and probably more.

[blog] Is it thinking or is it broken? Building transparent AI chat UIs with Genkit. Is this thing on? You might ask that when waiting to see if the AI service is stuck, thinking, or something else. Here’s a pattern for showing a heartbeat.

[blog] Skills Over MCP. Can we ship the manual with the product? That’s what this working group is trying to figure out.

[article] OpenClaw and Hermes agree on what an agent is. They disagree on what controls it. Interesting. Jani helps us understand the philosophical difference between the two personal agent platforms.

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I’ve had a new blog post bouncing around in my head for a couple of weeks, and I built out some of the necessary proof-of-concept last night. Now, to block time to write the thing. That’s really the most important part of blogging, the writing.

[blog] Old Software Was Fast Because It Had No Choice. Is modern infrastructure too forgiving? Do we allocate extra headroom because we can? Instead of throwing capacity at every problem, maybe we can design smarter.

[article] Help Employees Get Better—Not Just Faster—with AI. This may change how I talk about this topic. Don’t make AI adoption just about creating AI fluency; it’s a change in how you express experience and judgement.

[blog] How to Become Ridiculously Good at Kubernetes. I like the point that average engineers know the commands while expert engineers know the failure modes.

[blog] Interactions API: our primary interface for Gemini models and agents. It’s GA, and the best way to interact with Gemini models and agents. Get built-in support for background work, state management, and more.

[blog] Don’t rely on instructions, use Agent Hooks to enforce guardrails. Straightforward point. An agent can ignore instructions, but the hook runs every time.

[blog] Securing the future of AI agents. This is from Google DeepMind, and links to a pretty great paper on how to think about agent security.

[blog] In-place pod restarts: Boosting efficiency and workload reliability in Kubernetes v1.35. This is a fairly important feature for those who don’t want massive control plane thrashing when pods restart.

[blog] How Netflix Simplified Batch Compute with Kueue. Today’s got a lot of Kubernetes content. I’m not sure why. But, it’s a great reminder of how important your underlying infrastructure really is.

[blog] How we built a Flutter-powered AI coffee shop. I find that “fun” examples of technology are often more educational than the professional ones.

[article] AI isn’t solving cybersecurity workforce woes. Let’s see. A majority of cybersecurity people feel like calling it quits, AND we don’t have enough people to even fill the open roles right now. This is fine. Everything’s fine.

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Just got home after a weekend in San Francisco with the family, and then a customer presentation at the Google office today. Our reading list has a lot about the modern SDLC and the role of agent loops.

[article] Why we’re bullish on loops. Agents are capable of running longer, and doing more complex work. So kicking off agents that can prompt agents is a viable approach in some cases.

[article] The Case Against Building Your Own Agent Platform. Right now? You’ll likely build something incomplete or incorrect for what agents need. That’s ok, it’s a fluid market. Don’t prematurely over-platform your stack.

[article] 3 Forces Are Redefining the Transition from Manager to Leader. Advice from 2012 needed a refresh. Here’s a very good look at what it means to evolve into an organizational leader.

[blog] Scaling the Next Generation of Global Innovation: How Google Supports Top Startups Around the World. We’ve got one of the most successful startup accelerators that you’ve never heard of. Startups know it, but we’re doing some work to help others aware of it too.

[blog] AI Sped Up Coding Faster Than It Sped Up Delivery. It’s the handoffs. Always the handoffs. Think about cycle time and flow in order to identify bottlenecks faster.

[article] Autonomous Long-Running Coding Agents. Go from prompts, to goals. This makes your verifiers or evaluators even more important. I really liked this overview of the new workflow.

[blog] The New Software Lifecycle. More here on the new developer workflow. It also has a useful image showing the rapid transition from autocomplete to autonomous agents.

[article] What is GLM-5.2? Z.ai targets coding agents. Here’s a very impressive open model that’s getting some serious traction already.

[blog] Building the agentic enterprise. Terrific look at what really changes for enterprises who pursue agents, and what to expect on the journey.

[blog] From Feature Branches to Agent Branches ft. Antigravity. This developer likes how we used git worktrees in Antigravity to simplify context switching.

[article] Doubling the productivity of your engineering team using AI. That’s the dream. Very strong takeaways in this recap of a podcast interview.

[article] Backporting bug fixes is dead, Project Valkey now sends in the bots. Desperation can lead to productive implementations of AI. For example, keeping a handle on bug fixes or PRs in open source projects isn’t sustainable for most human maintainers.

[article] IT operating models remain unfit for the AI era, CEOs say. The first step is recognizing it. The second is being courageous enough to risk fixing it.

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It’s a US holiday tomorrow, so I’ll see you all back here on Monday.

[blog] The Death and Rebirth of Programming. Great post. It’s a helpful assessment of what’s really changed, and why resisting won’t stop it.

[article] What the Top 1% of Engineering Teams Do Differently with AI. It comes down to different org structures, tools investment, and engineering discipline.

[article] The reason AI coding isn’t working on your team. I’m probably giving you whiplash if you’re reading today’s list from top to bottom. Don’t write off an LLM because your one-shot example didn’t work. Setup and embrace the harness.

[article] The Architecture of Focus. I liked this. Can’t seem to find time for deep work and focus? Redesign your environment. Anyone can do it.

[blog] CNCF and SlashData Report Confirms India as One of the Largest Cloud Native Communities with 2.25 Million Developers. The India tech community—cloud or otherwise—is excellent. I’ll be back there in July.

[blog] A2UI + MCP Apps: Combining the best of declarative and custom agentic UIs. I don’t think I knew about MCP Apps. Now I do, and how you might use these alongside A2UI to deliver more dynamic interfaces in agent workflows.

[blog] The Key to Confidence. Telling yourself “I can do this” may give a burst of confidence, but lasting confidence comes from experience.

[article] Cursor, GitLab and Zed agree GitHub is breaking. They disagree on how to rebuild it. There’s been a rumble for months that GitHub’s days could be numbered as everyone default choice. Now, viable competitors emerge.

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Many of today’s pieces touched on accountability and ownership when AI plays a part in generation. Super important topic as we move past just the “create stuff” phase of agentic AI.

[article] The Sign-Off Layer Is Becoming the Real Engineering System. The idea here is that AI made generation cheaper, but not ownership. Excellent post.

[article] When Purpose Backfires. Don’t lead with purpose if your team is hampered by thwarted impact. When (unnecessary) bureaucracy gets in the way, your burn out those powered by purpose.

[blog] The Open Source Maturity Spectrum. Thoughtful analysis by Steve. Corporate open source is rarely altruistic, and I’m saying that as the person who leads Google’s open source programs office! For many of us, it’s a strategic lever.

[blog] Atlassian’s DESIGN.md is here: what we learned testing portable design context in practice. We shared this standard a bit ago, and Atlassian shares some of the good and bad of their experience.

[blog] Announcing the Agentic Resource Discovery specification. Another open source spec, this time from Google, GitHub, NVIDIA, and others. It’s about make it easier to discover and consume agentic resources.

[blog] Using Agents, Keeping Agency. Good one from Devin on the decision layer, and keeping agency in a world of agents. You still own the result, regardless of how the work was created.

[article] Tech debt, process gaps keep firms in AI ‘pilot purgatory,’ study finds. Lots of untapped AI value held back by internal operational weaknesses.

[article] Vibe coding can build your pipeline. It can’t explain it six months later. Another piece that reminds us that institutional memory is important. Adding that to persistent specs or other logs is going to be critical to understand past decision.

[blog] How to Track AI Agent Lineage and Manage State in Code Repositories. I like how Jason’s been thinking about this. Are git commits enough to understand what happened over time? Or are we missing other metadata about the session that generated the code, along with other lineage information?

[article] Agentic coding and persistent returns to expertise. AI can know how to build, but it needs us to know what to build. Some interesting research here from Anthropic.

[blog] The Hidden Powerhouse: Demystifying the BigQuery Storage Write API. Super dive into this more high performing API that makes it easier and faster to load data into your data platform.

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I do this daily list for three reasons: personal discipline, self-learning, and sharing with others. In that order. If I just did it for learning and sharing knowledge with others, I could talk myself into skipping a day or two. But making it a “required” part of my day actually takes one decision off my plate. Do you have things you do just to build discipline?

[blog] More Than Syntax. Are developers still wrapping their identities in languages and frameworks? If so, nowadays is it less about being syntax experts and more about the community and using certain tools as a preferred way of solving problems?

[blog] The Knowledge Source: Reliable Product Docs for AI Agents via MCP. Helen leads our Google Cloud “Information Experience” team and shares how our technical docs are evolving with the times. Good insights.

[blog] AI demands more engineering discipline. Not less. What a piece. Agents are good at coding now, which means we need to ensure even more engineering rigor.

[article] AI Is Rewriting the Economics of Outsourcing. Can someone do standardized work faster than you? Maybe that’s not true anymore. This article has some useful framing for how to think about it now.

[article] The Subsidy Ended: What Tool-Using Agents Actually Cost. Smart point here. The cost of agentic work hasn’t really changed. The meter became visible.

[article] How does GenAI change when and how teammates talk to each other? Has AI changed our interaction patterns with our peers? Yes. Looks like routine questions go to LLMs, and we go to humans for context-specific expertise.

[blog] Building a Visualizer for Antigravity Agentic Development Sessions. Neat. AI tools make it simpler to build tools to help us understand what our tools are doing.

[blog] A fool’s folly with local AI models. With some craziness around US models, everyone’s hot on open/local models again. Regarding local, there are caveats (especially around resources) that you need to factor in.

[youtube-video] I am done with Golang. While I (really) enjoy reading and watching things that complement our products, I also seek out critical feedback. Prime is unhappy with our consideration of generics, and anything that spoils this straightforward language.

[blog] 10 Indispensable Prompts Our Team Refuses to Build Without. Use, modify, or ignore the prompts you see from others. But all of them can be informational.

[article] SpaceX to acquire Cursor for $60B in stock, days after blockbuster IPO. Already signaled months ago. But probably feels cheap today after SpaceX’s rocket ship IPO.

[blog] How to turn a 180% commit boost into shipped software. Check out this data and analysis by Karl. If you don’t invest in downstream automation, all the AI coding frenzy goes for naught.

[article] AI Coding Agents Get a Stack Overflow of Their Own. Creative product expansion, I’ll give it that!

[blog] How I learned Go in a Day with Antigravity 2.0 and How You Can Do the Same. No one deeply learns anything right away. But the barrier to entry to using different programming languages has literally never been lower.

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