Architecture Governance for AI Code Generation
A practical guide for engineers and PMs who want AI coding agents to move fast without breaking architecture decisions, module boundaries, ownership, and long-term system quality.
Engineering Manager / Technical Lead
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11 articles
A practical guide for engineers and PMs who want AI coding agents to move fast without breaking architecture decisions, module boundaries, ownership, and long-term system quality.
A practical guide to Auth0 Client ID Metadata Documents, Auth for MCP, on-behalf-of token exchange, and secure agent access patterns for modern web apps.
A practical guide to using OpenFGA for fine-grained authorization in SaaS apps, MCP servers, workflow agents, and agent orchestrators.
AI agents feel like they can touch every system. The practical answer is not more trust in the model, but database roles, row-level policies, semantic layers, tool scopes, approval gates, and audit trails.
The current evidence does not support trusting model size alone for secure code generation. Secure agentic coding needs threat modeling, constrained tools, scanners, evals, and human approval gates.
There is no truly bulletproof system prompt. But there is a practical engineering standard for making prompts far more robust across Sonnet, Haiku, GPT, and reasoning-style models.
Most AI code review bots fail for a simple reason: they optimize for visible comments instead of reviewer trust. This guide pulls together current benchmarks, practitioner reports, product limitations, and design patterns for building a code review agent that is fast, quieter, less biased, and less hallucination-prone.
A practical roadmap for software engineers who want to move from toy chatbots to production-grade AI agents, with the right study order, common gaps, and portfolio projects.
A practical service-level deployment guide for AI SaaS teams: Docker image design, GitHub Actions builds, Helm packaging, ArgoCD handoff, External Secrets, IRSA, and release hardening.
Walk through building a minimal MCP server in Go that authenticates users via Auth0 using OAuth 2.0, JWT verification, and the MCP Go SDK.
A comprehensive, multi-level deep dive into testing and quality assurance for modern AI-powered systems — from static web apps to agentic pipelines and MCP servers — using LiteLLM, LangWatch, Agno, AgentOS, and the Claude Agent SDK.
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