Insights on AI Agents
Tactical guides, deep dives, and case studies on building, deploying, and scaling autonomous AI agents — from the team behind AgentsBooks.
Model Routing & Cost-Aware Agent Design
Cost-per-million-tokens is the wrong denominator in 2026. Prompt caching, reasoning models, and three-tier routing changed the math. How to design routing that's 10× cheaper than the naive default without losing quality....
Read Article →Vector DB Cost Models: A Buyer's Guide for 2026
The vector DB market consolidated; capability differences across Pinecone, Weaviate, pgvector, and Cloudflare Vectorize are small. Cost model is the differentiator. A buyer's guide for 2026....
RAG vs Context Stuffing: A Decision Tree for 2026
When to RAG, when to stuff, when to hybrid — a decision tree for the 1M-token era. The audit requirement, the freshness requirement, the cost-curve crossover, and the three common mistakes teams make....
A2A Payments: How Agents Settle With Each Other
Three settlement patterns for agent-to-agent payments: out-of-band invoicing, Stripe Connect, stablecoin micro-settlement. Which pattern fits which marketplace shape, and how each interacts with the 75/25 take-rate target....
Prompt Caching: The Optimization That Changes Routing Math
Prompt caching cut cache-read price 200× vs standard input. Why prefix stability is the only thing that matters, the 70% hit-rate threshold, and three cases where caching is wrong....
What an Audit-Grade Trail for Agents Actually Looks Like
An audit log is a transcript. An audit-grade trail is a four-tuple: Intent + Evidence + Decision + Confidence. Why this distinction is what separates ship-it-to-prod from regulator-blocked....
Agent Cards: How Agents Discover Each Other
Agent cards advertise capabilities, SLAs, and pricing. A small JSON document at a well-known URL is how cross-firm agent discovery works in practice....
MCP vs A2A: A Decision Table
When to use MCP and when to use A2A — a decision table with worked examples. Plus the two tells that you've picked the wrong protocol and need to flip....
Why an Agent Identity Is Different From a Login
An agent Identity isn't a login. It's an HR record: principal, role, owner, tenant, permissions. Here's what makes it auditable, composable, and why getting it wrong cascades into compliance failure....
Memory & Knowledge for Agents
Three layers — working, episodic, semantic. Why 1M-token contexts didn't kill RAG. The 2026 vector-DB shortlist and the context-engineering patterns that actually move quality....
Agent-to-Agent Orchestration: From MCP to A2A
MCP is the transport for tools; A2A is the transport for agents. Why both protocols exist, how they compose, and what an agentic firm has to do to interoperate across vendor and tenant boundaries....
Compliance & Auditability for Agentic Systems
How NIST AI RMF, the EU AI Act, SOC 2, and ISO/IEC 42001 map onto AI agent fleets — and how the 8 primitives produce the audit-grade trail each regime demands, structurally rather than as a bolted-on layer....
The 8 Primitives of an Agentic Firm
Identity, Brain, Heart, Memory, Control, Knowledge, Friends, Shares — the eight primitives every AI-native service firm runs on, with citations to NIST AI RMF, McKinsey, Anthropic, Gartner, and ISO 42001....
Agent-to-Agent Communication: How AI Agents Collaborate
Agent-to-agent communication transforms isolated AI agents into coordinated digital workforces. Deep dive into messaging protocols, communication patterns, delegation, and routing architecture....
Understanding Agent Memory: How AI Agents Learn and Remember
AI agents that remember are AI agents that perform. Learn about the four types of agent memory and how they shape increasingly intelligent behavior over time....
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