Boyd Stowe
Solutions Engineering at Tacnode
Boyd Stowe leads solutions engineering at Tacnode. With two decades of experience helping enterprises adopt new database paradigms, he previously worked at Couchbase and IBM. He writes about real-time data architecture, production deployment patterns, and the practical considerations of migrating from composed stacks to unified platforms.
Posts by Boyd (15)
![Agent Coordination: How Multi-Agent AI Systems Work Together](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1 1"%3E%3C/svg%3E)
Agent Coordination: How Multi-Agent AI Systems Work Together
Agent coordination is what determines whether multiple AI agents produce coherent results or expensive chaos. Here's how coordination strategies, communication protocols, and fault tolerance actually work — and what breaks in production.
Boyd Stowe|Mar 5, 2026Foreign Data Wrappers: S3, Iceberg & Delta Lake
Foreign data wrappers let you query Parquet on S3, Iceberg tables, and Delta Lake catalogs with standard SQL and zero data movement. Complete setup guide.
Boyd Stowe|Feb 26, 2026Enterprise Integration Patterns for Streaming and AI Architectures [2026]
Publish-subscribe, content-based routing, CDC, event sourcing — the patterns haven't changed, but the architectures have. How each enterprise integration pattern applies in modern streaming, event-driven, and AI agent systems.
Boyd Stowe|Feb 22, 2026Vector Quantization: Compress Vectors 4–32x Without Losing Accuracy
Scalar, product, and binary quantization — how each compression method works, when to use them, and practical SQL examples for cutting vector memory 4–32x while preserving search quality.
Boyd Stowe|Feb 20, 2026LLM Agents: 4 Components That Separate POC From Production
LLM agents plan, act, remember, and coordinate. Most die after the demo. This guide breaks down the 4 core components every LLM agent needs, the types you'll encounter in production, and the infrastructure gaps that kill real deployments.
Boyd Stowe|Feb 19, 2026Full-Text Search in PostgreSQL: The Complete Guide to Building Search That Actually Works
Full-text search in PostgreSQL goes far beyond LIKE queries. Learn how tsvector, tsquery, trigram matching, inverted indexes, and relevance ranking work — with practical examples for e-commerce, content search, and production applications.
Boyd Stowe|Feb 18, 2026Similarity Search: What It Is, How It Works, and Why Most Teams Implement It Wrong
Similarity search ranks by vector proximity, not exact keywords. Learn how embeddings, ANN indexes, and hybrid search work — and why bolting on a separate vector database creates an infrastructure trap most teams don't see coming.
Boyd Stowe|Feb 17, 2026Why Real-Time Decisions Fail: Incomplete, Inconsistent, and Outdated Context
Outdated data breaks AI decisions even when pipelines are fast. Fraud slips through, agents act on wrong memory, personalization fails—not from slow systems, but from data freshness gaps and context that's incomplete, inconsistent, or outdated at decision time.
Boyd Stowe|Feb 11, 2026What Is Data Observability? The Complete Guide [2026]
Data observability monitors data health across your pipelines. Learn what data observability means, how it differs from data quality, the pillars of data observability, and why reactive monitoring isn't enough.
Boyd Stowe|Feb 14, 2026Multi-Agent Architecture: 8 Coordination Patterns That Actually Work [2026]
When AI agents conflict, you get duplicate orders, race conditions, and angry customers. Here are 8 production-tested coordination patterns — from simple locks to distributed consensus — with code examples for each.
Boyd Stowe|Jan 28, 2026Feature Freshness Explained: Why Model Accuracy Drops in Production
Your model scored 94% in training. In production it's drifting toward 80%. The features you trained on don't match what the model sees at inference. Here's how to measure feature freshness, detect drift, and close the gap.
Boyd Stowe|Jan 15, 2026Primary Key Design Mistakes That Double Your Query Time
Your analytical queries are slow—and it's probably not indexing. I've seen query latency double without any code changes, just from a bad primary key choice. Here are the 3 patterns that actually work at scale.
Boyd Stowe|Dec 29, 2025Code Like a Mammal
Evolve to stay a step ahead.
Boyd Stowe|Oct 15, 2025Context Lake in Practice: Detecting Fraud with Live-context LLMs
Securing systems where milliseconds mean millions.
Boyd Stowe|Sep 9, 2025Stateful vs Stateless AI Agents: Architecture Guide for Production Systems
Stateful agents retain context across requests. Stateless agents scale but forget. This guide covers the 5 failure modes teams hit in production, when to use each pattern, and the hybrid architectures that actually work at scale.
Boyd Stowe|Jan 6, 2026