Production-AI-Agent-Architektur-Playbook Production AI Agent Architecture Playbook

Eine 8-Seiten-Referenz für Engineering-Leader, die KI-Agenten für echte Workloads prüfen. Kein "Was ist ein LLM"-Füller — nur die Muster, Fehlerbilder und Entscheidungs-Frameworks, die Demos von Production trennen. An 8-page reference for engineering leaders evaluating AI agents for real workloads. No "what is an LLM" filler — just the patterns, failure modes, and decision frameworks that separate demos from production.

  • Architekturmuster, die 1.000+ tägliche Runs überstehen (Router-Planner-Executor, ReAct, Reflexion) Architecture patterns that survive 1,000+ daily runs (Router-Planner-Executor, ReAct, Reflexion)
  • Tool-Design, State und Memory-Regeln, die stille Regressionen verhindern Tool design, state, and memory rules that prevent silent regressions
  • Tests, Cost-Control, Monitoring und Human-in-the-Loop vs. Human-on-the-Loop Testing, cost control, monitoring, and human-in-the-loop vs human-on-the-loop
  • Weiterleitbar an CTO/Head of Eng, um Build vs. Hire zu rechtfertigen Forward-able to your CTO/Head of Eng to justify build vs hire

A production AI agent is one that serves real users with an SLO, has a cost ceiling somebody owns, has a defined blast radius for mistakes, and emits enough telemetry that you would notice if it broke at 3 AM. This 8-page playbook covers the patterns, failure modes, and decision frameworks for getting there — written for engineering leaders evaluating agents for real workloads, not for a tutorial audience.

The playbook covers the four production thresholds, the Router-Planner-Executor split, state and memory rules, tool design that survives traffic, four-layer testing, monitoring with cost kill-switches, the difference between human-in-the-loop and human-on-the-loop oversight, and a build-vs-hire decision matrix.

For the public counterpart see also: the production AI agent architecture guide and build vs buy AI agents.

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Möchten Sie durchgehen, wie das auf Ihren Agenten anwendbar ist? Want to walk through how this applies to your agent?

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Was drin ist What's inside

SEITE 1 PAGE 1

Was "Production-Agent" wirklich bedeutet What "production agent" actually means

Die vier Production-Schwellen: SLOs, Cost-Limit, Blast-Radius, Observability. Die meisten Agenten scheitern leise an einer davon. The four production thresholds: SLOs, cost ceiling, blast radius, observability. Most agents fail one of these silently.

SEITE 2PAGE 2

Router-Planner-Executor-MusterRouter-Planner-Executor pattern

Warum die Aufteilung in schnelles Routing, deliberates Planning und Tool-Execution gewinnt — bei Kosten und Reliability.Why splitting fast routing, deliberate planning, and tool execution across model tiers wins on cost and reliability.

SEITE 3PAGE 3

State- und Memory-RegelnState and memory rules

Episodisch, semantisch, prozedural. Default: kein Memory. Erst hinzufügen, wenn ein konkreter User-Use-Case es verlangt.Episodic, semantic, procedural. Default to no memory. Add it only when there's a concrete user-facing reason.

SEITE 4PAGE 4

Tool-Design, das Traffic überlebtTool design that survives traffic

Idempotente Side-Effects, graceful failures (is_error:true), enge Schemata, "ein Verb pro Tool"-Regel.Idempotent side effects, graceful failures (is_error:true), tight schemas, and the "one verb per tool" rule.

SEITE 5PAGE 5

Tests vor ProductionTesting before production

Golden Tasks, Snapshot-Assertions, Cost-Budget-Assertions, Offline-Eval mit gemockten Tools, wöchentliches Shadow-Review.Golden tasks, snapshot assertions, cost-budget assertions, offline evals with mocked tools, weekly shadow review.

SEITE 6PAGE 6

Monitoring und Cost-ControlMonitoring and cost control

Was pro Turn zu loggen ist, Kill-Switches, Anomaly-Budgets, die Metriken, die Regressionen vor den Usern fangen.What to log per turn, kill-switches, anomaly budgets, and the metrics that catch regressions before users do.

SEITE 7PAGE 7

Human-in-the-Loop vs. Human-on-the-LoopHuman-in-the-loop vs human-on-the-loop

Wann der Mensch synchron freigibt, wann asynchron beobachtet — und wie man von HITL zu HOTL migriert.When the human approves synchronously, when they monitor asynchronously, and how to migrate from HITL to HOTL.

SEITE 8PAGE 8

Build vs. Hire EntscheidungsmatrixBuild vs hire decision matrix

Wann aufbauen, wann freelancen, wann warten. Plus: wie man beide Pfade evaluiert.When to staff up, when to hire a freelancer, when to wait. Plus how to evaluate either path.