Architecture · Platforms · AI-Native Systems
Architecture for systems that have to work in the real world.
Practical thinking, open-source tools, architecture models, and experiments for engineers and technology leaders building complex software systems.
Explore production-minded guidance across software architecture, platform engineering, distributed systems, engineering strategy, and emerging AI systems.
By Jacob George — technology leader and software architect.
Start with a problem
Useful architecture starts with the decision you need to make.
Browse by the kind of system or engineering problem you are working through, then move from explanation to implementation and evidence.
When AI can take action
How should models propose tool actions without becoming the authority that executes them?
Explore governed autonomyWhen signals disagree
How can distributed systems build confidence from independent evidence without mistaking repeated noise for truth?
Explore evidence-driven resilienceWhen engineering has to scale
How do architecture, platforms, and engineering strategy reduce friction without creating another layer of bureaucracy?
Browse architecture insightsExplore by topic
Find something useful for the system you are building
The site spans architecture and technology leadership broadly. AEG and SHIELD are flagship original work, not the boundary of the site.
Practical Resource
Govern AI tool execution instead of trusting model output
`aeg-intent-gate` is a small TypeScript approval gate for AI tool calls, MCP tools, and human-in-the-loop workflows.
Models can propose actions, while policy and approval remain outside model reasoning. Executors receive only commands that crossed the governance boundary.
Intent Gate Lifecycle
Model output is treated as intent.
Independent policy decides authority.
Only approved scope reaches the tool.
Original Architecture Work
Models for evidence and authority
Two independent models explore different boundaries that become important as software grows more adaptive and autonomous.
Featured Insights
Ideas for architecture that is changing now
Selected writing across AI-assisted engineering, platforms, architecture, and agentic systems.
The AI-Native Engineering Platform
A practical reference architecture for engineering platforms that must serve both human developers and AI agents—without giving either a shortcut around identity, policy, evidence, or production controls.
Self-Evolving Coding Agents: When AI Starts Learning From Its Own Engineering Work
Coding agents are beginning to move beyond one-off assistance toward systems that can learn from previous engineering work. That could change not only developer productivity, but how we think about software architecture, governance, and engineering knowledge itself.
Platform Engineering 2.0
Platform Engineering 1.0 built paved roads for developers. Platform Engineering 2.0 is becoming the control plane through which humans and AI agents build, deploy, operate, and govern software.