LLMs and Generative AI in the enterprise.
Inspire, develop, and guide a winning organization.
Understand the unique values and behaviors of a successful organization.
Create visible workflows to achieve well-architected software.
Understand and use meaningful data to measure success.
Integrate and automate quality, security, and compliance into daily work.
An on-demand learning experience from the people who brought you The Phoenix Project, Team Topologies, Accelerate, and more.
Learn how to enhance collaboration and performance in large-scale organizations through Flow Engineering
Learn how making work visible, value stream management, and flow metrics can affect change in your organization.
Clarify team interactions for fast flow using simple sense-making approaches and tools.
Multiple award-winning CTO, researcher, and bestselling author Gene Kim hosts enterprise technology and business leaders.
In the first part of this two-part episode of The Idealcast, Gene Kim speaks with Dr. Ron Westrum, Emeritus Professor of Sociology at Eastern Michigan University.
In the first episode of Season 2 of The Idealcast, Gene Kim speaks with Admiral John Richardson, who served as Chief of Naval Operations for four years.
DevOps best practices, case studies, organizational change, ways of working, and the latest thinking affecting business and technology leadership.
Just as physical jerk throws our bodies off balance, technological jerk throws our mental models and established workflows into disarray when software changes too abruptly or without proper preparation.
Sure, vibe coding makes you code faster—that’s the obvious selling point. But if you think speed is the whole story, you’re missing out on the juicy stuff.
The values and philosophies that frame the processes, procedures, and practices of DevOps.
This post presents the four key metrics to measure software delivery performance.
November 24, 2025
Part 4 of 4: The Four Pillars of Progressive Delivery
AWS operates across 117 availability zones in 37 regions worldwide, serving millions of customers with services ranging from simple storage to complex machine learning platforms. Every day, hundreds of autonomous teams deploy thousands of changes to this global infrastructure.
The scale is mind-boggling. How do you coordinate that level of complexity without drowning in manual processes? The answer is automation sophisticated enough to absorb the complexity while preserving human judgment for the decisions that truly matter.
In our Progressive Delivery framework, automation serves as the stabilizing force that transforms erratic technological motion into smooth, predictable progress. Just as modern vehicles use computerized systems to dampen vibrations and apply corrections without driver intervention, automation in software development absorbs the technological jerks that would otherwise ripple through systems and disrupt users.
This isn’t just about efficiency—it’s about capability. As systems become more complex and operate at greater scale, manual intervention becomes both more necessary and less feasible. No human could possibly react quickly enough to the cascading changes in a distributed system serving millions of users.
Effective automation focuses on four categories of work:
Work We Value But Don’t Enjoy Testing, deployment, monitoring, security scanning—tasks that are essential but tedious. Automating these activities frees human creativity for problem-solving and innovation while ensuring consistency and reliability.
GitHub automates their deployment pipeline so thoroughly that engineers can focus on writing code and understanding user needs rather than managing release processes. The automation handles the mechanical aspects of software delivery while preserving human judgment for feature design and user experience decisions.
Work That Requires Precision Beyond Human Consistency Financial calculations, security configurations, compliance reporting—activities where human error carries significant risk. Automation doesn’t just perform these tasks faster; it performs them more accurately and with complete audit trails.
Work That Crosses System Boundaries Integration between services, data synchronization, workflow orchestration—tasks that span multiple teams or technologies. Automation ensures information flows smoothly across organizational and technical boundaries without getting trapped in coordination bottlenecks.
Work That Operates At Inhuman Scale Real-time personalization, dynamic resource allocation, fraud detection—activities that process thousands or millions of events per second. Humans simply cannot operate at the speed and scale that modern systems require.
AWS demonstrates automation thinking at massive scale. Their core principle is eliminating “undifferentiated heavy lifting”—work that every organization needs to do but that doesn’t create competitive advantage.
Instead of each company building their own data centers, AWS automates infrastructure management and lets customers focus on their unique business logic. Instead of each team building custom deployment pipelines, AWS provides automated services that handle the common patterns while allowing customization for specific needs.
But AWS’s most sophisticated automation addresses the social challenge of coordination. When you have hundreds of autonomous teams deploying changes constantly, how do you maintain alignment and prevent conflicts?
Their answer: automated policy enforcement. Instead of manual approval processes, AWS built systems that automatically scan deployments against configurable rules. Teams maintain autonomy to deploy when they choose, but automation ensures they can’t violate safety constraints or impact other teams.
Here’s what seems contradictory but actually makes perfect sense: automation enables greater autonomy, not less. By automating the predictable and constrained aspects of work, you free human judgment to focus on the creative and strategic aspects.
Consider Disney’s approach to theme park attractions. They automate the precise timing of ride vehicles, lighting effects, and safety systems. This automation enables creative teams (Imagineers) to focus on storytelling, guest experience, and artistic innovation without worrying about the mechanical precision required for safe operation.
The same principle applies in software delivery. When deployment, testing, monitoring, and security scanning are automated, developers can focus on understanding user needs and crafting solutions rather than managing infrastructure complexity.
The most sophisticated automation doesn’t just replicate human processes—it creates entirely new capabilities that weren’t possible with manual approaches.
Continuous Feedback Loops Automated systems can collect and analyze user behavior data at scales impossible for human observation. This enables real-time optimization and personalization that adapts continuously based on actual usage patterns.
Netflix’s recommendation system exemplifies this. No human team could analyze viewing patterns for hundreds of millions of users and generate personalized suggestions in real-time. The recommendation automation doesn’t just make human work faster—it creates capabilities that only exist at machine scale.
Predictive Risk Management Automated monitoring can detect patterns that predict failures before they occur, enabling preventive action rather than reactive responses. This transforms system reliability from damage control to proactive optimization.
Dynamic Resource Allocation Cloud platforms automatically scale infrastructure based on demand patterns, optimizing both performance and cost in ways that would be impossible with manual management.
Effective automation amplifies human capabilities rather than replacing human judgment. The goal isn’t to eliminate people from the process—it’s to eliminate toil so people can focus on high-value activities.
Humans Excel At:
Automation Excels At:
Progressive Delivery leverages both strengths. Humans define the strategies, policies, and success criteria. Automation executes consistently while providing feedback that informs human decision-making.
Begin by identifying automation opportunities in your current workflow:
Repetitive Manual Tasks What do your teams do multiple times per day that follows predictable patterns? Start there—even simple automation of routine tasks can free significant time for strategic work.
Cross-Team Coordination What information needs to flow between teams or systems? Automating these handoffs reduces coordination overhead and eliminates information bottlenecks.
Quality Gates What checks and validations currently require human intervention? Many quality assurance activities can be automated while maintaining or improving accuracy.
Feedback Collection What user behavior or system performance data could inform better decisions if you collected and analyzed it systematically?
The key is starting small and building capability iteratively. Each automation success creates the foundation for more sophisticated automation.
Organizations that master automation can operate at scales and speeds that their competitors cannot match. They can maintain quality while moving faster, reduce costs while improving capabilities, and adapt to changing conditions while maintaining reliability.
But automation without the other three A’s becomes brittle and counterproductive:
Progressive Delivery automation isn’t about replacing human workers—it’s about eliminating human toil. Every manual task you automate frees human creativity for the problems that matter most: understanding user needs, designing better experiences, and solving novel challenges.
As AI capabilities continue expanding, the automation opportunities will multiply exponentially. Organizations that develop strong automation capabilities now will be best positioned to leverage these advancing technologies.
The question isn’t whether automation will transform your industry—it’s whether you’ll be leading that transformation or scrambling to catch up.
Over this four-part series, we’ve explored how abundance, autonomy, alignment, and automation work together to enable Progressive Delivery:
None of these elements work in isolation. They reinforce and enable each other, creating organizational capabilities that are greater than the sum of their parts.
The companies that master this balance—abundant resources focused through autonomous teams aligned around user value and supported by sophisticated automation—will define the future of software delivery.
This concludes our four-part series on the pillars of Progressive Delivery. For the complete framework and detailed case studies, see Progressive Delivery: Build The Right Thing For The Right People At The Right Time by James Governor, Kim Harrison, Heidi Waterhouse, and Adam Zimman (IT Revolution Press, November 2025).
Managing Editor at IT Revolution working on publishing books and guidance papers for the modern business leader. I also oversee the production of the IT Revolution blog, combining the best of responsible, human-centered content with the assistance of AI tools.
No comments found
Your email address will not be published.
First Name Last Name
Δ
Part 4 of 4: The Four Pillars of Progressive Delivery AWS operates across 117…
The following is an excerpt from the book Vibe Coding: Building Production-Grade Software With GenAI,…
Part 3 of 4: The Four Pillars of Progressive Delivery Disney's theme parks feature…
