Chaotic Commits | Software, AI, and Uncomfortable Truths

Joanne Skiles
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The podcast that says the thing everyone in the room is thinking but nobody puts in the post-mortem. Chaotic Commits covers software engineering, AI, cloud architecture, and engineering leadership (not that sanitized LinkedIn version, the real one). Architecture decisions that almost broke everything. Management lessons learned the hard way. The bigger questions about who gets to build the future and what that actually means. New episodes every week. Hosted by Dr. Joanne Skiles, AWS Community Builder, engineering leader, and speaker at AWS re:Invent, AWS Summits, GHC, and more.

  1. feat: I built a cyberpunk cat RPG to teach production AI architecture

    20 分鐘前

    feat: I built a cyberpunk cat RPG to teach production AI architecture

    I built a cyberpunk cat RPG where you play a TabbyWarrior or a SphinxRogue fighting through Neo-Pawsburg in 2087, and right next to the game, you can watch the real production AI architecture executing live underneath it. I built this for AWS Summit LA because I got tired of watching people's eyes glaze over at architecture diagrams. This episode walks through the five reliability patterns that actually decide whether an AI agent survives production: grounding the model with retrieval before it speaks, retries and idempotency without breaking randomness, a hard boundary where the model proposes and the system disposes, structured observability from the first Lambda invocation, and state that lives in a database instead of a prompt. Then I tell you about the seven hundred dollar mistake I almost made. "Serverless" does not mean free at idle, and I found that out the expensive way with OpenSearch Serverless's pricing floor, one day before AWS fixed the exact problem I'd already engineered around. If you've ever needed a straight answer on what "the AI just calls an API" is actually hiding, or you build agentic AI systems and want the reliability patterns without the marketing, this one's for you. None of this is because AI is uniquely broken. It's because an AI agent is a distributed system, and distributed systems have rules. Topics: AI agent architecture, AWS Bedrock, Step Functions, distributed systems, serverless pricing, observability, RAG, idempotency, AI reliability patterns, production AI systems

    18 分鐘
  2. feat: embed a stranger in your codebase

    7月3日

    feat: embed a stranger in your codebase

    I read the AWS forward deployed engineering announcement on a Tuesday morning. Palantir has been doing this for over a decade. And guess what? OpenAI does it, also Anthropic does it. A billion dollars from AWS means this is now the default way enterprise AI gets adopted at scale. But here's the question nobody asks in the sales meeting: when a vendor's engineer ships code to your production system and then goes back to their company, who owns that code on day one thousand? This episode isn't "is forward deployed engineering good or bad." It's about the incentive structure. A forward deployed engineer is optimizing for platform adoption, renewal milestones, and a good case study. Your team needs a system that's still legible in three years. Those are different goals. And if you don't name that mismatch before the engagement starts, your team will be the ones writing the postmortem. I also cover the four questions I'd ask before signing. Not a framework. Just what I'd actually say in the room. If you've ever inherited code from someone who wasn't building for your team's future, this one's for you. Topics: forward deployed engineering, enterprise AI adoption, vendor management, engineering leadership, accountability, technical debt, AWS, AI platform, Palantir Links Substack: https://chaotictoejam.substack.comBluesky: https://bsky.app/profile/chaotictoejam.bsky.social

    25 分鐘
  3. feat: invented the do-while loop (already existed)

    6月26日

    feat: invented the do-while loop (already existed)

    My teammate and I had been at the whiteboard for most of the morning. Three pages filled, two markers gone, cap on one of them missing since 9:30. We had built a loop structure that runs at least once before checking its condition. We were proud of it. We walked to our tech lead's desk and presented what we'd built. "You mean a do-while?" In unsupervised isolation, I had co-invented the do-while loop. It has existed since approximately the Eisenhower administration. This is about what happens when smart engineers work without vocabulary. Not without intelligence, without the index. The connection between a problem and the named construct that solves it. Senior engineers don't think harder. They pattern-match faster because someone built that index for them. We cover the history of parallel independent discovery, what engineering mentorship actually looks like versus leaving junior engineers at a whiteboard, and why vibe coding produces the same failure at scale: correct logic, more code than necessary, because nobody knew the name of what they were building. If you have ever worked hard to open a door that had a handle on it, this one's for you. Topics: engineering mentorship, junior engineers, early career, do-while loop, programming fundamentals, vibe coding, AI-generated code, engineering vocabulary, pattern recognition, Lockheed Martin, technical onboarding

    20 分鐘
  4. maintain: you can't vibe trust

    6月19日

    maintain: you can't vibe trust

    An interview candidate asked me what makes our product safe from someone vibe coding a competitor. The honest answer was: nothing stops them. This episode is the full version of that answer. Vibe coding gets you a version of the thing: code that works under the conditions you tested, for users you imagined. What it doesn't get you is understanding. In consumer software, that gap is survivable. In healthcare, finance, and regulated domains, it can cost people their lives. I walk through three companies that found out the hard way: Theranos, Zenefits, and Silicon Valley Bank. I make the argument that the more dangerous failure isn't the outsider who skips the domain. It's the incumbent that stops maintaining it. Domain knowledge you stopped practicing isn't a moat. It's a story you tell about yourself. If you build software in a regulated industry, or lead a team that does, this one is for you. Topics: vibe coding, AI-generated code, engineering leadership, domain expertise, regulatory compliance, responsible AI, technical debt, software engineering ethics

    21 分鐘
  5. feat: I know they're just pixels, but can't you be nice?

    6月12日

    feat: I know they're just pixels, but can't you be nice?

    My seven-year-old was trash-talking a Pokémon trainer. The way a seven-year-old does. And I stopped him: "I know they're just pixels, but can't you be nice?" That simple moment led to a much bigger question: What are we practicing when we interact with AI systems, chatbots, NPCs, voice assistants, and virtual characters? In this episode of Chaotic Commits, we explore what Tamagotchis, ELIZA, Roombas, Alexa, ChatGPT, and modern AI systems can teach us about human behavior, AI ethics, transparency, and the habits we build when interacting with technology. The question isn't whether AI has feelings. It's what we're practicing when we interact with increasingly human-like systems. Topics: AI ethics, artificial intelligence, ChatGPT, human-AI interaction, AI transparency, anthropomorphism, responsible AI, human-in-the-loop systems, software engineering, engineering leadership, AI design, and behavioral psychology.

    27 分鐘
  6. raise e: the line that logged everything

    6月5日

    raise e: the line that logged everything

    It's 8:30 PM, and I'm lying in my four-year-old's bed playing Spiderman when the text comes in. "yoo, we are logging all of tenant config in prod logs has secrets in plain text." Not test secrets. Not staging. All of the secrets. Production. In the logs. This episode is the story of that night: what raise e actually does in Python, why a valid exception handler became a production security incident, and what "log scrubbing" actually means when your logs are in a SIEM, a compliance archive, and systems your vendor manages. We cover secret rotation when you're two incidents deep in forty-eight hours, and your customers are involved. The thing I keep coming back to: logging is an architectural decision, not a default. Most teams find out they never made that decision when they're staring at a screen at 10 PM, calculating how long tenant API keys have been sitting in plain text. If you've been on-call, worked through a security incident, or built anything that handles customer secrets, this one is for you. What you log is a decision. Own it before someone else finds it. Topics: production incident, secrets in logs, Python exception handling, raise e, incident response, log scrubbing, API key leak, SIEM, compliance, on-call engineering, backend security, logging best practices, engineering leadership, tenant security

    18 分鐘
  7. scope: undefined

    5月29日

    scope: undefined

    A manager once told me, "If you get the work done, they will want more." He meant it as advice (and was a little sarcastic too). He was wrong about what to do with it. He wasn't wrong about the dynamic. This episode is about what happens when capable engineers become the workaround. The script you run once to fix prod becomes the script you're running for 300 users two weeks later. The emergency process becomes the permanent process. Eventually, the organization concludes that we don't need the system. We have you. In this episode, I talk about scope creep at the individual level, not the project level. It's what happens because you're good at your job and you keep saying yes. But to escape, you need to know how to hold the line without just saying no. You have to build a "no" that sticks. If you've ever walked out of a meeting wondering how you became someone's permanent workaround, this is for you. Topics: engineering leadership, scope creep, technical debt, engineering culture, career advice, software engineering, setting boundaries, organizational debt, engineering management

    20 分鐘
  8. (bonus) cache miss: the search for something google won't let you find

    5月26日 ·  附贈內容

    (bonus) cache miss: the search for something google won't let you find

    I want to tell you about the last time I actually enjoyed using Google. I don't remember exactly when it was. That's kind of the point. At I/O 2026, Google announced an AI-first search experience. Instead of links, you get a synthesized answer. Conversational. Efficient. And I think we just killed something important. This episode is about three connected things nobody is saying out loud: what we lose when search becomes a conversation, why the dead internet theory isn't paranoid anymore, and what AI training has to do with killing the incentive that made the open web worth building in the first place. If the AI draws its knowledge from the web, and the web stops having a reason to produce original knowledge, the whole system starts eating itself. If you've ever followed a link from a link from a link at midnight and ended up somewhere you didn't know you needed to be, this one's for you. Topics: AI search, Google I/O, dead internet theory, knowledge discovery, open web, AI training data, search engine optimization, AI accountability, transparent AI systems

    15 分鐘
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簡介

The podcast that says the thing everyone in the room is thinking but nobody puts in the post-mortem. Chaotic Commits covers software engineering, AI, cloud architecture, and engineering leadership (not that sanitized LinkedIn version, the real one). Architecture decisions that almost broke everything. Management lessons learned the hard way. The bigger questions about who gets to build the future and what that actually means. New episodes every week. Hosted by Dr. Joanne Skiles, AWS Community Builder, engineering leader, and speaker at AWS re:Invent, AWS Summits, GHC, and more.

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