This week on Ship It Weekly, GitHub Actions can now run eligible Linux jobs on AWS as well as Azure, so allowlists and Entra Conditional Access policies that only trust Microsoft ranges can break. The Brotli decoder bug (CVE-2026-111497) landed on CISA's exploited list, and it reaches past Node.js to Python Brotli, Bun, Envoy, Istio, a Go port and .NET. A campaign called Gheist is using stolen GitHub tokens to push ci-sync branches that print Actions secrets past log masking, then delete the run. And attackers are dropping AGENTS.md files into Downloads folders to hijack AI coding agents.

The thread: each one is an inventory question. Which services decompress Brotli, which allowlists assume CI runs on Azure, which OIDC trust policies accept any branch, and which laptops have started an agent in Downloads?

In the lightning round: GitHub Actions workflow lockfiles are generally available, Railway disclosed a breach of its internal systems, Tailscale 1.104.4 fixes four security bulletins, and Datadog moved its US1 status page to its own Status Pages product.

The human closer, from Bill Duncan: "Twenty minutes in, you haven't started diagnosing anything. You've been doing archaeology." Write down who owns it before the pager asks.

Highlights

• GitHub Actions on AWS: why the same job can pass, then fail

• Sync runner IP ranges from GitHub's meta API, not one cloud's

• Brotli: a decoder bug your HTTP stack may run for you

• Gheist: what private repos and OIDC trust let through

• AGENTS.md in Downloads: an instruction file is code now

• Service catalogs and the "what depends on me?" question

Links

GitHub Actions multi-cloud compute: https://tsn.io/fJkLJ

Node.js October security releases (Brotli): https://tsn.io/BvZBU

Brotli CVE-2026-111497, affected libraries (Wiz): https://tsn.io/HJuKS

.NET out-of-band security updates: https://tsn.io/j0Xwf

Gheist steals GitHub Actions secrets (Wiz): https://tsn.io/nunEs

AI agents hijacked via the Downloads folder (Forever Security): https://tsn.io/qnwuc

Actions workflow lockfiles GA: https://tsn.io/M84uA

Railway security disclosure: https://tsn.io/21t0j

Tailscale security bulletins: https://tsn.io/GvZxR

Who Owns This? (Bill Duncan): https://tsn.io/LFrzc

SRE Weekly #540: https://tsn.io/O8tpO

This week's On Call Brief: https://tsn.io/HqfCP

More episodes and show notes: https://tsn.io/NqkdP

On Call Brief: https://tsn.io/Gpz2d

LMGT Awards: https://tsn.io/lAERA

This is a guest conversation episode of Ship It Weekly, separate from the weekly news recaps.

In this Ship It Conversations episode, I talk with Darko Fabijan about what starts breaking after the pull request when AI writes more of the code, what should sit between an AI agent and production, and why his answer is more automation.

Darko is the CEO of SuperPlane and co-founder of Semaphore, the CI/CD platform. At SuperPlane, he's working on how to give AI agents write access to production in a controlled way.

We start with what AI-generated code does to delivery. Pull requests are bigger and more frequent, reviewers can't keep up, and Darko points to a Faros AI report that shows defects and incidents going up. He describes AI as alien technology that dropped from the sky, landing in processes built for people who review code eight hours a day.

His main hypothesis is a deterministic layer between AI agents and production, with scoped access that goes through approval. I bring up the rubber stamping problem with human approvals, and his reply is that humans hallucinate too. So he wants a risk score on every change. Renaming a bucket scores low. Deleting an S3 bucket or an RDS instance scores red.

Then we get into the glued-together ops tooling most teams run on. Darko doesn't think anything is wrong with it. When I ask how SuperPlane differs from Argo Workflows or n8n, he says he wants agents and humans on the same plane, and he'd onboard an agent like a new engineer: give it an identity, let it look around, and show it what it can do. We also cover team-scoped agents, compliance at AI speed, and docs where every line traces back to what produced it.

We finish on where to start. Darko says read-only first: he pretends to be super stupid, asks a lot of dumb questions, and says "onboard me." For the first write operations, he'd pick loops you can measure with a number, like latency, GitHub Actions speed or CVE count, tested on a copy of production or staging first.

The big takeaway: AI didn't break software delivery. It showed how much of it still runs at human speed. Darko's answer is more automation, with a deterministic layer and a risk score between AI and production.

Highlights

• What breaks after the pull request when AI writes more of the code

• A deterministic layer between AI agents and production

• Rubber stamping, and a risk score for every change

• Onboarding an AI agent like a new engineer

• The dam and the river: compliance at AI speed

Links

Darko Fabijan on LinkedIn: https://tsn.io/DySr5

Darko Fabijan on X: https://tsn.io/xJGhN

SuperPlane: https://tsn.io/o08yM

Semaphore: https://tsn.io/jiHmd

Faros AI's Acceleration Whiplash report: https://tsn.io/5ZCR3

Argo Workflows: https://tsn.io/oyTYF

n8n: https://tsn.io/nloFF

More episodes and show notes: https://tsn.io/NqkdP

On Call Brief: https://tsn.io/Gpz2d

LMGT Awards: https://tsn.io/lAERA

This is a guest conversation episode of Ship It Weekly, separate from the weekly news recaps.

In this Ship It Conversations episode, I talk with Jinger Meilani about Tabletop Retro, her way of turning an engineering retrospective into a tabletop role-playing game, and why a little silliness gets teams to give honest answers.

Jinger is a Senior Software Engineer in DevOps at Mountain. She says Tabletop Retro brings together three things she loves: world building, psychological safety on teams, and engineering enablement.

We start with why she reinvented the retro at all. She was bored of them, and even the themed ones got rote. At a previous company, the team rotated who ran the retro, and her turn landed around Halloween, so she built a story around the team. She calls the result retro plus plus plus. The usual formats and outcomes are all still there, inside a story.

A lot of it comes down to silliness. Jinger compares it to hiding vegetables in a fruit smoothie: it disarms people, and she gets honest answers, sometimes while everyone thinks they're talking about something else. That's also why she won't run one during a fire. People have to feel comfortable before they'll speak their truth, so the flame-breathing dragon can wait.

Then we get into how one is built. A Tabletop Retro is a series of chapters, and each chapter holds part of the story and at least one activity. Players fill out character sheets, and each in-game race maps to a technical archetype, like a Goliath for a high-level systems thinker or a gnome for a tinkering automation engineer. Afterward the team talks through what those picks say about their strengths and weaknesses. She presents it like a storybook, in Lucidchart or Canva over Zoom.

Characters cut both ways. For some people, an orc is permission to say what they'd never put on a retro board, because it's not really how they feel. They're just an orc. Others find role-play intimidating, so she reads the room: improv for an outgoing teammate, a line on screen for someone else, or no speaking part at all. If you want to try one, start with the questions, not the world. Where is the team unaligned? When does communication break down? Then keep the setting small. Kids trick-or-treating is plenty.

The big takeaway: a Tabletop Retro is still a retro, and Jinger holds it to a higher bar. If everyone has fun and tells you something honest, and then nothing changes, it failed. Someone still has to do the work.

Highlights

• Why she calls it retro plus plus plus

• Hiding vegetables in a fruit smoothie

• Why you don't run one during a fire

• Chapters, character sheets and technical archetypes

• "I'm just an orc," and why role-play makes some people nervous

• Reading the room: improv, on-screen lines, or no lines at all

• Start with the questions, then keep the world small

• Fun with no follow-through is a failed retro

Links

Tabletop Retro, Jinger's framework: https://tsn.io/wXdtL

Jinger Meilani on LinkedIn: https://tsn.io/xn8Jr

Jinger's IaCConf talk, Designing IaC Interfaces That Work for Humans, AI Agents, and Whatever Comes Next: https://tsn.io/5b4DM

More episodes and show notes: https://tsn.io/NqkdP

On Call Brief: https://tsn.io/Gpz2d

LMGT Awards: https://tsn.io/lAERA