The hottest Software Delivery Substack posts right now

And their main takeaways
Category
Top Technology Topics

Why aren't AI productivity gains higher?

Engineering Enablement • 18 implied HN points • 19 Mar 26
🕹 Technology Software Delivery
  1. AI does make writing code faster, but coding is only a small part of an engineer’s work, so those speedups only move the overall output a little.
  2. Speeding up code creation exposes or creates downstream bottlenecks — things like code reviews, validation, and handoffs haven’t kept up, so saved time often gets consumed later.
  3. Adoption and impact are limited by social friction, immature tools, skill gaps, and missing implicit context in codebases, so real gains require better workflows, documentation, and team alignment.

Fear of bugs is worse than the bugs themselves!

Wisdom over Waves • 159 implied HN points • 16 Nov 23
🕹 Technology Software Delivery
  1. Fear in software delivery negatively impacts metrics like deployment frequency, lead time for changes, time to restore service, and change failure rate.
  2. Introducing processes due to fear can slow down innovation and reduce efficiency, leading to delays in deployments and unnecessary quality gates.
  3. Delays in software delivery caused by fear can result in increased work in progress, introduction of bugs, lower deployment frequency, longer mean time to resolve, and a negative impact on DORA metrics.

In Quality, the secret sauce is feedback!

Wisdom over Waves • 79 implied HN points • 11 Jan 24
🕹 Technology Software Delivery
  1. Quality in software is about fast and fabulous delivery without compromising on quality.
  2. Defining quality can be subjective, meeting customer needs they may not even know they have.
  3. Feedback is the secret sauce to understanding customer needs, with practical tips like frequent releases, attentive listening, and exploring multiple feedback layers.

RDEL #17: How does your engineering team type indicate team performance?

Research-Driven Engineering Leadership • 0 implied HN points • 06 Nov 23
🕹 Technology Software Delivery
  1. Different types of engineering teams show different performance patterns on key performance indicators, such as software delivery performance, operational performance, and user-centricity.
  2. User-centric teams prioritize delivering user needs, leading to high organizational performance and job satisfaction, but they can be prone to burnout.
  3. Balanced teams, with a sustainable approach to technology use, show the lowest rate of burnout and enable enduring teamwork.
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