Real-Time Data Queries for Autonomous Agents
Autonomous agents make hundreds of decisions per second. We trace query paths, bottlenecks, and failure points in slower backends.
Blog
Engineering deep dives.
We build agent data infrastructure, tune query execution, and keep backends aligned with decision loops.
Why Vector Databases Won't Scale Your Agent Memory
Vector search solves one task, not primary agent memory. We examine the performance costs of using it as the memory layer.
Benchmarking Query Latency in Multi-Step Agent Workflows
Four approaches reveal how query latency changes across multi-step agent access patterns. We share the measurements and their production implications.
Streaming State Updates Without Polling
Polling costs time and resources. We explain LaserData's SSE-based push delivery and its role in real-time agent state.
The Case for a Purpose-Built Agent Data Layer
Human-oriented databases add latency, complexity, and operational overhead to agent traffic. We make the case for a purpose-built backend.
Schema Design Patterns for Stateful AI Agents
Query speed follows state structure. We cover four patterns from early-access deployments and the tradeoffs behind each.
Eliminating the Five-System Stitch in AI Backends
A five-system stack can combine vector DB, Redis, Kafka, Postgres, and a job queue. We examine its cost against a single-purpose alternative.
How LaserData Handles Concurrent Agent Sessions
Parallel sessions make shared state contentious. We explain LaserData's namespace isolation model for fast reads under concurrency.
The Query Execution Model Behind Real-Time Decisions
After an agent issues a query, several steps precede the response. We trace LaserData's execution path and its optimizations for agent access.
Data Consistency Guarantees in Multi-Agent Systems
Consistency guarantees shape shared state. We explain LaserData's model, when strong consistency matters, and when eventual consistency is the better tradeoff.
Memory-Efficient Context Windows for AI Agents
Expensive context windows demand careful memory management. We cover ways to reduce context while retaining needed information.
Introducing LaserData: A Backend Built for Agents
Fast reads, streaming state, concurrent sessions, and no stitching: we opened early access to LaserData and explain why we built it.