# Ai Architecture And System Design
All Ai Architecture And System Design notes →1. Architectural Thinking
Introduces the pattern-catalog framing for the rest of this part: how to evaluate an agentic architecture pattern against determinism, cost, latency, and blast-radius trade-offs rather than picking the newest framework default.
2. Planner–Executor Pattern
Formalizes the planner–executor pattern — a planning component that decomposes a goal into a full upfront plan, and a separate executor that carries out each step — with applicability criteria, concrete failure modes, and how it composes with the rest of the pattern catalog.
3. Supervisor Pattern
Formalizes the supervisor pattern introduced in Multi-Agent Systems as a reusable architectural pattern, covering when a central supervisor agent outperforms peer-to-peer coordination and where it becomes a bottleneck.
4. Orchestrator–Worker Pattern
Covers the orchestrator-worker pattern for fan-out/fan-in task decomposition, including worker failure isolation, partial-result aggregation, and when it is preferable to a supervisor-style hierarchy.
5. Router Pattern
The canonical treatment of the router pattern -- classifying an incoming request and dispatching it to exactly one specialized handler, tool, or sub-agent -- covering the three real ways to build the classification step, confidence-based fallback, and the structural line that separates a router from a supervisor.
6. Blackboard Pattern
Covers the blackboard architecture - a shared, structured workspace multiple specialist agents read and write to opportunistically - and where it beats explicit message-passing for loosely-coupled multi-agent collaboration.
7. Event-Driven Pattern
Covers building agent systems on an event bus rather than direct request/response calls, including event schema design, at-least-once delivery handling, and idempotent agent reactions to replayed events.
8. Memory-Centric Pattern
Covers architectures where long-term and episodic memory (not the planner) is the primary coordination substrate for agent behavior, including memory write policies and staleness/consistency trade-offs.
9. Human Approval Pattern
Covers designing human-in-the-loop checkpoints for high-risk agent actions - approval gates, timeout/escalation policy, and how to keep the pattern from becoming a rubber-stamp bottleneck.
10. Agent Mesh Pattern
Covers a decentralized mesh of peer agents that discover and negotiate with each other directly, contrasted with the centralized orchestrator/supervisor patterns earlier in this catalog, and the discovery/trust problems a mesh introduces.
11. Pattern Selection Framework
Closes the catalog with a decision framework - a scorecard across coordination overhead, failure isolation, latency, and observability - for choosing among the patterns covered in this part for a given problem shape.
1. AI Copilot Architecture
Walks through the reference system design for an in-product AI copilot - context assembly from the host application, streaming responses, and the guardrails that keep suggestions scoped to what the user is actually doing.
2. Coding Agent Platforms
Covers the system design of a coding agent platform (codebase indexing, sandboxed execution, diff review workflow) at the depth expected in an L6/L7 system design interview.
3. Research Agents
Covers the architecture of a research agent that plans multi-step web/document retrieval, cites sources, and self-critiques for completeness before returning a synthesized answer.
4. Customer Support Agents
Covers the system design of a customer-support agent - ticket triage, knowledge-base grounding, escalation to a human, and the metrics (deflection rate, CSAT) that define success.
5. Enterprise Knowledge Assistants
Covers designing an enterprise-wide knowledge assistant over heterogeneous internal sources (wikis, tickets, code, Slack), including access-control-aware retrieval so answers respect document permissions.
6. Autonomous Operations Agents
Covers agents that take autonomous remediation actions in production systems, including the safety envelope (dry-run mode, blast-radius limits, automatic rollback) required before granting write access.
7. AI SRE Platforms
Covers the system design of an AI SRE platform end to end - alert ingestion, correlation, root-cause hypothesis generation, and runbook execution - as the natural extension of the observability-investigation agent built earlier in this book.
8. AI Platform Architecture
Covers the enterprise-wide reference architecture tying together the gateway, registry, and multi-model infrastructure from Part 04 of Production Agent Systems into a single platform diagram suitable for an architecture review.
9. Global AI Infrastructure
Covers multi-region deployment of AI infrastructure - data residency constraints, cross-region model failover, and latency budgets for a globally distributed agent platform.
10. Cursor: Architecture Case Study
An external, engineering-blog-grounded analysis of Cursor's likely architecture — Merkle-tree-synced codebase indexing, the Tab fast path for inline edit prediction, and the agent-mode tool-calling loop for multi-file changes — read as public inference, not disclosed internals.
11. Claude Code: Architecture Case Study
A documentation-grounded analysis of Claude Code's architecture — the gather/act/verify agentic loop against a real filesystem and shell, the allow/deny/ask tool-permission model, and subagent delegation with isolated context — distinguishing Anthropic's own documented mechanics from reasonable architectural inference.
12. GitHub Copilot: Architecture Case Study
An external, engineering-blog-grounded analysis of GitHub Copilot's evolution from a low-latency inline completion service into an asynchronous, multi-model coding agent platform — and why the safety envelope changes shape along with it.
13. Perplexity: Architecture Case Study
An external, engineering-blog-grounded analysis of Perplexity's real-time research-agent architecture -- live web retrieval instead of a static corpus, citation grounding as a hard output constraint, and answer synthesis under a tight latency budget.
AI Architecture & System Design
A book-shaped table of contents for AI Architecture & System Design: the cross-cutting agent pattern catalog and full enterprise system-design case studies at L6/L7 interview depth. Book 5 of the AI Systems Engineering series.