Tag
16 articles tagged platform engineering.
This episode examines how agentic software development changes security, platform strategy, and engineering roles. It highlights the need to move mitigation into the agent loop and standardize platform defaults. The discussion also identifies verification as a premium capability and local models as a future cost lever.
Industry leaders analyze the structural shift in AI infrastructure spending, the evolution of platform engineering into AI-native enablement, and the emerging challenges of token economics and digital sovereignty. This executive brief outlines strategic frameworks for governance, cost attribution, and compliant architecture design.
Sarah Wells discusses transforming governance into enablement, the role of platform engineering in microservices, and how AI amplifies existing engineering practices. She emphasizes the need for rigorous tests, documentation, and inclusive leadership to leverage AI safely while maintaining architectural integrity.
ThoughtWorks leaders analyze the shift from AI hype to production reality, emphasizing validation harnesses, platform governance, and the amplification of engineering practices. The discussion highlights the critical role of non-functional requirements and the evolution of engineer roles in an AI-augmented landscape.
This analysis explores the evolution of CI/CD pipelines, progressive delivery strategies, and platform engineering at scale. It examines the shift from rigid rollbacks to roll-forward hotfixes, the pragmatic application of GitOps principles, and the strategic value of hybrid SaaS and on-premise deployment models. Key insights address how AI acceleration is reshaping pipeline priorities from speed to risk mitigation.
SiriusXM's platform engineering team shares a rigorous prioritization framework for internal developer platforms, combining dynamic impact weighting, assumptions-as-code, and AI-augmented recall to align engineering output with developer needs and business OKRs.
Mercari's journey to 100% AI adoption reveals critical lessons on measurement, platform stability, and cultural enablement. The company overcame productivity dips by stitching AI telemetry with SDLC metrics, reducing friction, and shifting to spec-driven development.
FINN's CTO outlines the strategic pivot to an AI-first organization, detailing the P&L shift from headcount to token consumption, the democratization of internal software development, and the critical role of platform engineering in maintaining quality at scale.
BNY Mellon's Head of Software Engineering Strategy reveals how the bank scaled AI across 8,000 engineers by transforming the entire SDLC. Learn the 3x stress test framework, three-tier deployment model, and cultural shifts driving stability and compliance in regulated environments.
Analyzes historical software development principles through a modern enterprise lens. Explores how startup-era tactics translate to scalable architecture, platform engineering, and sustainable engineering cultures. Highlights critical context shifts, survivorship bias, and actionable frameworks for technical leadership.
An analysis of critical system engineering principles focusing on stability, scalability, and security. The discussion explores the intersection of platform engineering and the disruptive impact of AI on technical apprenticeship and observability.
SiriusXM leverages a weighted prioritization framework and an 'Assumptions as Code' repository to resolve cross-team conflicts. This strategy uses AI agents to validate product hypotheses against historical data, enabling scalable decision-making for platform engineering teams supporting diverse builder personas.
An executive analysis of shifting AI adoption from tool selection to environmental readiness. This brief outlines frameworks for measuring amplification versus augmentation, addressing the code review bottleneck, and defining new metrics for agent-driven engineering capacity.
Agentic AI is transitioning from experimental prototypes to mission-critical production infrastructure. This analysis outlines strategic frameworks for centralized platform engineering, non-deterministic risk management, and token cost optimization. Leaders must balance rapid experimentation with rigorous governance to capture competitive advantage. Early adoption remains essential for market parity.
ThoughtWorks leaders analyze the shift from AI experimentation to production, emphasizing the critical role of platform engineering, data readiness, and business-aligned governance. The discussion highlights why traditional metrics fail and how organizations must master foundational CI/CD practices to leverage agentic workflows effectively.
Analysis of why platform engineering fails due to cultural and organizational gaps rather than technical deficits. Strategies for adopting a product mindset, implementing golden paths, and leveraging AI for governance and developer experience.
.png)
