wardley-mapsFeatured
Platform Engineering Evolution: From Custom Scripts to Self-Service
A Wardley map showing the evolution of platform engineering capabilities, from basic scripts to sophisticated developer platforms.
•5 min read•
...
🏷️
Platform Engineering
Explore all content tagged with "Platform Engineering" across insights, frameworks, and resources.
RSS FeedSort by:
114 items1 featured
Featured
All Platform Engineering
insights
From Copilots to Governed Agents: Why Metadata and Service Topology Just Became AI Infrastructure
AI is shifting from code generation copilots to agentic systems that execute scoped tasks, while data platforms and infra teams are building the governance and “system maps” (metadata, service...
•3 min read•
...
insights
The New Agentic Stack: Cost, Reliability, and Governance Are Becoming the Differentiators
AI agents are rapidly becoming a production workload, forcing a new CTO playbook: optimize token/tool spend, build internal agent platforms, and pair scale with governance, reliability, and...
•3 min read•
...
insights
The New AI Stack Shift: Governed Agentic Execution (Not Just Better Models)
AI agents are becoming first-class production workloads—and the differentiator is shifting from model choice to governed execution: sandboxed runtimes, identity-aware access to enterprise systems,...
•3 min read•
...
insights
From AI Tools to an AI Operating Model: Outcomes, Guardrails, and Workflow Automation
AI adoption is shifting from ad-hoc tooling to an outcome-driven operating model: teams are standardizing AI in the dev workflow (PRs, automation), defining success metrics and guardrails, and...
•3 min read•
...
insights
Mid Week Summary: Operational Resilience, Compliance Tooling, and the New Reality of AI-Accelerated Security
The week’s pattern: “AI everywhere” is forcing grown-up operating systems
•5 min read•
...
insights
The Reliability Era of AI Agents: Sandboxed Execution, Guardrails, and Measurable Outcomes
AI is entering its “reliability era”: companies are building agentic capabilities with deterministic guardrails, sandboxed execution, and explicit success metrics—treating AI as a governed platform...
•3 min read•
...
insights
AI by Default Means Platform by Necessity: The New CTO Stack (GPUs, Vectors, and Governance)
Teams are transitioning from “trying AI” to running AI as a first-class production workload: building shared AI platforms, optimizing GPU utilization, embedding vector search into core data systems,...
•3 min read•
...
insights
From AI Demos to Real-Time Agentic Platforms: Streaming + Vector Search + Governance Become One Stack
AI delivery is shifting from isolated copilots to always-on, real-time, governed “agentic + RAG” systems—forcing CTOs to treat data streaming, vector search, schema governance, and automated security...
•3 min read•
...
guides
Team Topology Designer guide: a practical Team Topologies designer tool for 10 to 100 engineers
Team Topology Designer guide: team topologies designer tool for 10 to 100 engineers
•14 min read•
...
insights
AI Is Entering Its “Production Optimization” Phase: Faster Inference, Clearer Patterns, Stronger Governance
AI is moving from experimentation to production optimization: teams are simultaneously optimizing inference throughput, standardizing AI-enabled engineering workflows, and choosing between RAG and...
•3 min read•
...
insights
From AI Pilots to AI Ops: The Rise of Production AI Engineering and Agentic Platforms
AI is moving from experimentation to disciplined operations: teams are investing in production-grade AI engineering skills, adopting agent/tool-calling patterns, and reshaping operations and...
•3 min read•
...
insights
Agentic AI Is Becoming a Platform Problem (Not a Feature)
Engineering orgs are rapidly standardizing “agentic AI” as a first-class production workload—building internal agent platforms, adding CI/CD for data+AI pipelines, and tightening the operational...
•3 min read•
...
Want to contribute?
Have experience to share? We welcome contributions from technical leaders.
Learn how to contribute