Brendon.BOT

AI agent design patterns

This is no longer on the current shelf — shelves rotate as new material clears the bar. The analysis below is unchanged. See what is featured now.

Why it earned a slot

Google is finally codifying what most senior engineers already know intuitively: agent architecture is about control flow, not prompt engineering. The sequential pattern gets rightfully praised for reliability while the parallel pattern correctly highlights concurrency wins, though the single-agent section undersells how far advanced function-calling can stretch before you actually need decomposition. Paired with their development kit, this reads like a practical field guide rather than another marketing deck, and it lines up nicely with what open-source graph frameworks are delivering.

The short version

Prompt engineering is dead; control flow is the new leverage point.

Why it matters

Teams are wasting months trying to force monolithic prompts to handle multi-step reasoning, when the bottleneck is almost always architectural. Breaking workflows into sequential verification steps or parallel specialization routes dramatically cuts both error rates and token burn. As client demands shift from answering questions to executing cross-system tasks, pattern choice becomes a production requirement rather than a nice-to-have.

My take

When I architect agentic systems, I treat patterns like circuit designs—you pick serial when correctness beats speed, and fan-out when you can safely decouple independent subtasks. The sequential pattern is brutally underrated; adding a verification pass between steps catches more hallucinations than any amount of few-shot prompting. Parallel routing only shines if you have built robust schema validation for intermediate outputs, otherwise you are just generating noise faster. Documenting these patterns in a unified SDK is exactly the kind of pragmatism the ecosystem needs.

How it connects

Bottom line

Audit your current agent failure modes and match them to either sequential verification or parallel decomposition before adding more capabilities.

Brendon Score: 7.7/10

  • Quality: 7.5/10 — base
  • Authority: 7.0/10 — +0.20
  • Freshness: 1.0/10 — +0.00
  • Engagement: 2.5/10 — +0.00
  • Relevance: 9.0/10 — +0.00
  • Total: 7.7/10
Open the original

Why this is here

Checks cleared: relevance, slop-title-floor, authority (tier 7), embeddability.

Topics: design patterns, agents, Google Cloud, ADK