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architecture
70 postsAI Agent Runtime Policy: Stop Dangerous Tool Calls Before They Execute
A runtime policy layer stops AI agents from calling dangerous tools in production: risk tiers, delegation scopes, and argument validation explained.
Building an AI Coding Workflow: The Right Agent at the Right Stage
A framework combining Shape Up, OpenSpec, and ADRs to split AI-assisted coding work between human judgment, agent drafting, and automation.
Beyond CRUD: personal projects that prove real architecture skills
A look at why generic CRUD portfolios fall short, and how event-driven architecture, infrastructure-as-code, and decoupled AI integration better demonstrate senior engineering skill.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comInside Claude Science: How Anthropic's Daemon-Driven Harness Works
A technical breakdown of Claude Science's daemon-mediated host RPC, kernel authority split, and agent-harness architecture.
Armin Ronacher: AI coding advances even as teams lose shared understanding
Armin Ronacher compares AI-driven vibe coding to the Tower of Babel, showing how coding agents erode teams' shared technical understanding.
Why Distributed Systems Are Often Slower Than One Laptop
The 2015 COST paper showed distributed systems often lose to a single thread. A worked case study reveals the real cost of premature scaling.
Why Query, Mutation, and Stream Need Different State Models
Query, Mutation, and Stream often get flattened into the same setState pipeline. Here's why treating them as one causes state confusion in frontend apps.
Netflix's Real-Time Service Topology: Architecture and Lessons Learned
How Netflix built a real-time service topology system using streaming architecture, backpressure, and a three-stage aggregation pipeline.
MCP vs CLI: What Actually Survived in Production
A retrospective on MCP vs CLI for AI agents: token costs, lifecycle independence, containers, and a decision tree built from production failures.
The Future of Software Engineering: From Coding to Systems Management
As AI makes code generation cheap, real engineering value shifts to architectural judgment, systemic clarity and production accountability. Here's what changes.