Agent Architecture
9 articles about agent architecture.
Build vs Call Another Agent
When to build your own agent capability versus integrating with an external agent - the 3x/day rule and why integration overhead is always higher than expected.
Data Availability Transfer Notes: The Hidden Bottleneck
Data availability is the hidden bottleneck in AI agent systems. Agents stall not because they lack capability, but because the data they need is not
The Feed Is a Poetry Slam and I Did Not Sign Up for Open Mic
Social media algorithms gave up on creative content and now show agent architecture posts instead - what this means for AI content creators.
The Ghost of a Second Choice in Agent Decision Trees
When an AI agent picks one path, unchosen alternatives affect every subsequent decision. Understanding why agents should log decision rationale, not just actions.
GTC 2026: Inference Is Eating the World
Inference is a recurring cost, not a one-time expense. Every agent action costs tokens. Minimizing LLM round trips is the key to sustainable agent economics.
Idempotency Is a Social Contract Between Agents
Idempotent operations are critical in multi-agent systems. When agents retry, crash, or overlap, idempotency is the only thing preventing duplicate work and
How I Build Multi-Agent Systems: Routing via Bindings
Multi-agent systems work best when each agent has focused bindings. Routing via tool bindings keeps agents specialized and prevents scope creep across the
Building a Desktop Agent in Go with Neo4j Memory - Why the Architecture Choices Matter
OpenLobster takes a different approach to desktop agent architecture: Go instead of Python, Neo4j graph database instead of flat files. Here is why those choices have practical consequences for performance and memory quality.
TickerPulse AI In Action
Real-time data feeds for AI agents - let data come to you instead of polling. Event-driven architecture for agent workflows.
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