Agents and Engineers | Agentic AI, Software & Agentic Engineering

Cory O'Daniel is CEO and co-founder of Massdriver, an internal developer platform and platform orchestrator for governed self-service infrastructure using Terraform, OpenTofu, and Helm. He has spent more than 20 years building teams and startups and working with cloud infrastructure. He created Bonny, an Elixir-based Kubernetes operator framework, and is a co-founder of OpenTofu.
Dan and Cory discuss what infrastructure agents need to act safely. Massdriver models environments and resource relationships so agents can query context directly, while separate agent identities and attribute-based permissions constrain their access. Cory describes a staging workflow that tests infrastructure changes through real deployments before he promotes a release to production.
Cory explains how a tested, consistent codebase supports his team's Claude Code workflow, why enforceable tooling matters more than long instruction files, and why human review still matters. He argues that engineers should build quality controls and deployment paths for domain experts who can now create software themselves, with collaboration and operational ownership still needing attention.
Full episode notes
Transcript
Chapters

(00:00) - Self-service infrastructure and the arrival of agents

(03:11) - An API built around infrastructure context

(09:03) - Agent identity and attribute-based permissions

(15:54) - A four-person team, agents, and technical debt

(23:12) - Future engineering roles and enforceable quality

(30:20) - Backlog zero and autonomy for citizen developers

(34:29) - Claude Code workflows, examples, and memory

(40:54) - Testing infrastructure changes before production

(48:00) - Reusable presets and shared provisioners

(55:06) - Terraform is easy; organizations are complex

(57:09) - Citizen developers and the future of cloud platforms

(01:00:53) - When production apps run on someone's laptop

(01:03:23) - Domain expertise, autonomy, and engineering's value

(01:10:30) - Collaboration beyond Git and code in OCI registries

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Links from the show
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Massdriver
Massdriver Architect
The Citizen Developer
Cory O'Daniel's personal website
Terraform
OpenTofu
Postgres
GraphQL
Kubernetes
attribute-based access control
test-driven development
domain-driven design
Ghostty
Checkov
Wiz
Snyk
GitOps
OCI
Elixir
Golang
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Guests
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Cory O'Daniel, CEO & Co-Founder, Massdriver
Website
LinkedIn
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Stephanie Jarmak is an AI Engineer at Omni working on multi-agent orchestration and code intelligence. She is a research affiliate for NASA's Science Explorer (SciX) and a maintainer of Gas City, an open-source orchestration builder for multi-agent coding workflows.

Dan and Stephanie discuss how she became a Gas City maintainer by learning from review agents, encoding contribution standards in skills, and building an issue-triage workflow. Automating those steps exposed new reliability problems, from failures across dependencies to excessive alerts and agents that overreact to hypothetical risks.

Their conversation connects these experiments to Stephanie's move from planetary science into search and AI engineering. They examine the appeal of building with agents, the responsibility for maintaining what those agents produce, and the mixed emotions of seeing models solve once-difficult research tasks. Personal game projects and Omni's approach to shaping her role show how her curiosity carries across both work and home.

Full episode notes

Transcript

Chapters

(00:00) - Contributing to open source with coding agents

(08:51) - Learning the review standards and becoming a maintainer

(12:58) - Automating a Gas City workflow

(21:02) - Astronomy, computers, and a different path into development

(27:40) - Working styles and responsibility for agent output

(34:46) - Production responsibility and AI skepticism

(40:12) - Human judgment and agents solving science tasks

(45:55) - Pre-mortems, silent failures, and too many alerts

(48:34) - Slack as an agent dashboard and shareable Gas City packs

(53:45) - Building games and creative projects with the kids

(59:06) - From planetary science to search and Sourcegraph

(01:09:48) - Omni and a role shaped around the person

(01:15:03) - Decision models and making automation easier

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Links from the show

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Gas City

Beads

Gas Town

Dolt

Steve Yegge

Claude Code

Codex

The Six Types of Working Genius

Terminal-Bench Science

Harbor

Slack

Suno

Forge

Scryfall

17Lands

SciX

Sourcegraph

Amp

Omni

information retrieval

pre-mortem

reinforcement learning from human feedback

Jev

⠀

Guests

-------

Stephanie Jarmak, AI Engineer, Omni

Website

LinkedIn

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Eric Ma is a Senior Principal Data Scientist at Moderna, where he leads the Data Science and Artificial Intelligence (Research) team. Previously, he conducted biomedical data science research at the Novartis Institutes for Biomedical Research and earned his doctorate in Biological Engineering from MIT. Eric is also an open-source software developer known for leading pyjanitor and nxviz and contributing to NetworkX and PyMC.

Dan and Eric discuss Eric's rapidly changing practice of agentic data science, centered on Marimo Pair and reproducible Python notebooks. Eric demonstrates an analysis of protein activity and stereoselectivity data, explains why canonical sources and inline environment metadata matter, and shows how agents make ambitious custom visualizations more approachable even when a live demo fails. The conversation then turns to design documents, testable specifications, repository conventions, and the attention-management practices Eric uses to keep agent work from becoming a context-switching trap.

Full episode notes

Transcript

Chapters

(00:00) - Why Eric's data science workflow changed so quickly

(05:49) - Marimo Pair puts agents inside the notebook

(07:19) - Reproducing a protein-engineering paper

(10:45) - Why enzyme stereoselectivity matters

(13:20) - Canonical data sources and portable environments

(18:08) - Exploring activity and selectivity with interactive plots

(27:47) - Finding promising regions for protein engineering

(30:24) - From heat maps to a 3D protein viewer

(35:54) - Learning from agent traces and preserving intent

(47:13) - Opinionated structure for agent-written code

(52:25) - Managing attention across agentic tasks

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Links from the show

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Marimo

Marimo Pair

OpenCode

cmux

Machine-Directed Evolution of an Imine Reductase for Activity and Stereoselectivity

cloudscraper

Polars

Plotly

PEP 723

uv

3Dmol.js

anywidget

Protein Data Bank

PyMOL

The Arrow of Intent

Hermes Agent

Obsidian

⠀

Guests

-------

Eric Ma, Senior Principal Data Scientist, Moderna

Website

LinkedIn

GitHub

X

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Andrew Zigler is a GTM Engineer at LinearB and the host of Dev Interrupted, a twice-weekly podcast and newsletter about AI-native development and agentic orchestration. A classicist by training, he previously taught in Japan, built e-learning platforms, and worked in developer relations at Mattermost.

Dan and Andrew discuss how shared workflows and memory can help turn individual AI gains into team improvements. Andrew explains his Mise en Place planning methodology and how he uses Beads to translate ideas into connected tasks, while keeping human collaboration in tools such as Asana and Confluence.

They examine why clear specs reduce rework without removing the need for iteration, how CI/CD and code review may adapt to agentic development, and what Andrew’s personal agent setup has changed about his work and learning.

Full episode notes

Transcript

Chapters

(00:00) - Introduction and the gap between individual and team gains

(06:15) - Open source when agents become the users

(10:09) - A personal agent stack built on simple primitives

(17:37) - Mise en Place and planning before coding

(21:58) - Connecting Beads to team workflows

(26:10) - Why task graphs help agents maintain context

(35:57) - Shared specs and human alignment

(43:26) - Agile iteration with faster prototypes

(44:52) - CI/CD and independent code review

(52:12) - Humanities, learning, and managing agents

(58:00) - Changing skills and software interfaces

(01:02:25) - Fixing feedback loops and sharing the stack

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Links from the show

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Beads

Beads Rust

Mise en Place

Andrew’s dotfiles

Dev Interrupted

LinearB

Tailscale

Agent Gateway

systemd

WireGuard

DuckDB

Wispr Flow

Dolt

Gas Town

Steve Yegge

Jeffrey Emanuel

Robots Ate My Homework

NumPy

pandas

The Diamond Age

Snow Crash

agile

continuous integration

progressive web app

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Guests

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Andrew Zigler, GTM Engineer, LinearB; Host of Dev Interrupted

Website

LinkedIn

X

GitHub

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Julien Verlaguet is Founder and CEO of SkipLabs, the company building Skipper, a closed-loop coding agent. He created Skip, a reactive programming language, and led the design of Hack, the language Meta developed to run its code base at scale.

In this episode, we discuss what the job of programming language designers becomes when AI agents write most of the code. This includes the design decisions in the language and tooling when agents are the principal user.

We also discuss: - How Julien refocused SkipLabs towards AI - What it would take for AI to be able to fully replace engineers - The use of formal methods with LLMs

Full episode notes

Transcript

Chapters

(00:00) - A closed-loop coding agent

(04:30) - Reactive programming and technical debt

(08:40) - Why SkipLabs moved toward AI tooling

(11:07) - Incremental tools and low-latency feedback

(14:20) - Reactive collections versus Buck and Make

(21:06) - Language design in the age of LLMs

(31:01) - When human coding still matters

(34:16) - Working with four to six agents

(41:04) - Why code quality still needs judgment

(49:48) - The hidden cost of AI-generated tests

(56:24) - The junior engineer dilemma

(01:04:27) - Formal methods and LLM verification

(01:13:35) - A bumpy road toward a brighter future

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Links from the show

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Skipper

SkipLabs

Skip

Hack

reactive programming

incremental computation

Buck

SQLite

Coq

Rocq

Lean

Curry-Howard correspondence

formal methods

model checking

Emacs

Bun

⠀

Guests

-------

Julien Verlaguet, Founder and CEO, SkipLabs

Website

LinkedIn

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Follow the podcast

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