Skills
Product Discovery
Frameworks for product discovery in developer tools: design partners, user research, personas, competitive analysis, and building for developer flow. Covers customer interview techniques, discovery processes, evaluating feature requests, and knowing when to pivot. Drawn from practitioners at LaunchDarkly, Honeycomb, and others.
- +19
Agentic Engineering
How teams build software when AI coding agents write the code: directing agents, what code review and validation become when code is nearly free, durable systems with disposable code, orchestrating many agents, keeping them safe inside an organization, and how roles change. Drawn from practitioners at HumanLayer, Sentry, Honeycomb, Google DeepMind, and others.
- +15
Tech Ethics & Responsible Engineering
Building with eyes open to unintended consequences. Covers the gap between engineering intent and real-world outcomes, responsible AI considerations, inclusive design, and the organizational practices that help teams anticipate harm before shipping. Drawn from practitioners at BBC Radio 4, Code for America, Thoughtworks, and others.
- +8
Observability & Incident Response
The practice of operational reliability: instrumentation, monitoring, SLO setup, incident response, on-call design, and day-to-day reliability operations. Covers alerting strategies, error budgets, incident management processes, and blameless postmortems. Drawn from practitioners at Honeycomb, Datadog, PagerDuty, and others.
- +18
Resilience Engineering
The organizational side of reliability: learning from incidents, sociotechnical analysis, chaos engineering philosophy, and the limits of purely technical approaches. Covers incident analysis methods, safety culture, adaptive capacity, and building organizations that learn from failure. Drawn from practitioners at Netflix, Stripe, Honeycomb, Jeli, and others.
- +17
Content from the Library
Third Loop Ep. #13, Ten Times Faster at What? with Jennifer Riggins
On episode 13 of Third Loop, the Progressive Delivery team speaks with Jennifer Riggins about why faster code doesn’t automatically mean better software. They explore how AI exposes organizational bottlenecks, why psychological safety matters, and what Spotify’s growing feature set reveals about user value. Jennifer makes the case for smaller experiments, stronger feedback loops, and keeping people at the center of delivery.
Third Loop Ep. #12, Shipping at the Speed of Understanding with Steph Hippo
On episode 12 of Third Loop, the Progressive Delivery team speaks with Steph Hippo, Platform Engineering Director at Honeycomb, about what happens when AI accelerates development beyond the pace humans can absorb. They explore safe defaults, evolving code reviews, and the feedback loops that help teams understand what they ship. Steph makes the case for reinvesting saved time in better decisions, software quality, and human connection.
Third Loop Ep. #11, Durable Systems, Disposable Code with Chad Fowler
On episode 11 of Third Loop, the Progressive Delivery team sits down with Chad Fowler to explore regenerative software and what architecture looks like when AI makes code cheap enough to continually replace. They discuss Phoenix Architecture, Pace Layers, observability, architectural constraints, and why the system itself, rather than any individual implementation, may become the real asset in an AI-native future.
