Articles
Single Agent Patterns
A deep dive into the software architectures and execution loops powering autonomous AI agents.
Single Agent Patterns: Reason and Act Loop
An exploration of the fundamental ReAct pattern: interleaving explicit reasoning traces with environment actions to build adaptive agent control loops.
Read Article →Single Agent Patterns: Plan-Then-Execute
An analysis of the Plan-Then-Execute pattern: separating complex goal decomposition from task execution to maintain long-horizon coherence.
Read Article →Single Agent Patterns: Search over Actions
An exploration of tree and graph search strategies: generating alternative action paths, evaluating states, and backtracking to solve search-like goals.
Read Article →Single Agent Patterns: Reflection and Self-Correction
An exploration of verbal reinforcement loops: evaluating candidate outputs, storing errors in episodic memory, and executing grounded retries.
Read Article →Multi-Agent Patterns
Exploring collaborative frameworks, team dynamics, and context delegation in multi-agent environments.
Multi-Agent Patterns: Orchestrator-Worker
An in-depth analysis of the Orchestrator-Worker pattern: decomposing goals centrally and delegating subtasks to context-isolated workers.
Read Article →Multi-Agent Patterns: Peer Debate and Ensembling
An exploration of consensus topologies: how interactive debate and non-interactive ensembling aggregate model instances to cancel out errors.
Read Article →Multi-Agent Patterns: Role-Based Teams
An exploration of process discipline: how mirroring human organizational workflows and communicating via artifacts prevents conversational drift.
Read Article →Multi-Agent Patterns: Conversational Multi-Agent
An exploration of group chat topologies: how sharing a single conversation history enables dynamic workflows, steering, and human-in-the-loop collaboration.
Read Article →Multi-Agent Patterns: Handoff
An exploration of dynamic routing: how specialized agents hand off control via routing tools to keep prompts and toolsets focused and reliable.
Read Article →Memory and State Patterns
Exploring cognitive architectures, checkpointing, and dynamic context engineering.
Memory Patterns: Context Window Management
An in-depth analysis of context window engineering: managing token constraints, trajectory compaction, and observation truncation to prevent drift.
Read Article →Memory Patterns: Episodic External Memory
An exploration of database state persistence: how agents embed and retrieve past session details using vector similarity to achieve continuous learning.
Read Article →Memory Patterns: Structured and Procedural Memory
An exploration of facts and skills: how separating database semantic facts from executable procedural skills minimizes coding overhead.
Read Article →Memory Patterns: Shared Memory and Blackboards
An exploration of scope topologies: how connecting agents via a central database repository balances context isolation and common ground.
Read Article →Memory Patterns: Checkpointing and Resumability
An exploration of execution durability: how persistent state snapshots save token overhead, ensure error recovery, and support human steering.
Read Article →Protocols & Specifications
Articles covering the standards, frameworks, and developer tools for agentic integration.
What is the x402 protocol?
An introduction to the open, application-level payment protocol that revives the HTTP 402 Payment Required status code for secure stablecoin micro-payments.
Read Article →What is Universal Commerce Protocol?
An introduction to the open standard designed to facilitate interoperable, agentic commerce, explaining how AI agents can discover and purchase products dynamically.
Read Article →Integrating UCP: The Python SDK
A technical guide on how to leverage the Python SDK to construct product models, process checkout flows, and build e-commerce tools conforming to UCP specifications.
Read Article →What are agentic interfaces?
An introduction to the world of agentic interfaces; the highways that power agentic communication.
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