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•
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Platform Engineering
Explore all content tagged with "Platform Engineering" across insights, frameworks, and resources.
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All Platform Engineering
insights
AI Is Becoming a Full-Stack CTO Problem: Context, Compute Placement, and New Risk Boundaries
AI execution is moving closer to where data and users live (consumer devices, managed platforms), while AI programs are stalling without trusted context and facing fast-rising security and regulatory...
•3 min read•
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insights
The AI Context Layer Is the New Battleground: Why Open Lakehouse Tables and Platform Predictability Decide AI ROI
AI pilots are stalling less on model capability and more on the “context layer”: governed, interoperable data (often via open lakehouse tables like Iceberg) plus operational platforms that make that...
•3 min read•
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insights
AI Is Scaling Faster Than Trust: Why CTOs Need an “AI Trust Stack” Now
AI is moving from experimentation to operational embedding (SRE, analytics, and autonomous agents), and the limiting factor is shifting from scale to trust: governance, security, auditability, and...
•3 min read•
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insights
Agent Ops Arrives: Benchmarks, Guardrails, and the End of Vibes-Based AI Adoption
Engineering organizations are moving from experimenting with AI agents to operationalizing them with benchmarks, workflow integration, and explicit human-in-the-loop controls.
•2 min read•
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insights
AI Becomes the Enforcement Layer: From Engineering Docs to Runtime Guardrails
Engineering organizations are turning AI into an enforcement layer: standards, security, and reliability controls are being embedded directly into pipelines and runtime systems, rather than living as...
•3 min read•
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insights
The New AI Ops Stack: Model Routing, Telemetry Context, and Infrastructure Efficiency
AI programs are shifting from single-model adoption to “AI operations” as a discipline: routing across multiple models, tightening safety controls, and rebuilding observability plus infrastructure...
•3 min read•
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insights
AI Agents Are Becoming Production Systems, So Treat Them Like SRE-Owned Software
AI agent adoption is shifting from demos to operational systems, forcing CTOs to treat agents as production software with SRE-grade telemetry, security controls, and cost-aware model routing.
•3 min read•
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insights
Mid Week Summary: Agent Operations, Model Routing, and Regulation Pressure Across the Stack
The week’s pattern: “agentic” is getting real, and ops is the tax
•5 min read•
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insights
Agentic AI Is Forcing a New Control Plane: Persistent Runtimes, Tool Governance, and Incident Response
Agentic AI is moving from stateless prompts to long-running workflows with persistent compute, tool execution, and enterprise governance.
•4 min read•
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insights
Agentic AI Is Becoming a Data and Policy Problem (Not a Model Problem)
AI programs are shifting from model selection to system control: routing requests across models, governing agent tool access (especially writes), and upgrading data layers for consistency and...
•4 min read•
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insights
AI for Media: A CTO Playbook for Production, Archives, and Personalization
AI for media: a CTO playbook for production, archives, and personalization
•14 min read•
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insights
Agentic AI Enters Production: Tracing, Data, and Provenance Become Platform Primitives
Agentic AI is moving into production, forcing teams to adopt new platform primitives (agent tracing, approval steps, replayable sessions) and to treat data quality, security, and provenance as core...
•3 min read•
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