Engineering
Browse all engineering posts from the Transactional team.
Why Your AI Chatbot Forgets Everything (And How to Fix It)
Architecture of persistent user memory using vector search for LLM applications. Embedding strategies, retrieval patterns, memory decay, and per-user scoping.
How Semantic Caching Can Cut Your LLM Costs by 60%
A practical guide to implementing semantic caching with vector embeddings to reduce LLM API costs. Covers architecture, similarity thresholds, cache invalidation, and production considerations.
MCP Security: What Developers Need to Know
Security analysis of the Model Context Protocol ecosystem. Authentication gaps, tool poisoning risks, excessive permissions, and a security checklist for developers adopting MCP servers.
Prompt Injection Nearly Broke Production AI. These Patterns Can Save You.
Prompt injection incident analysis and proven defense patterns: input sanitization, output validation, system prompt hardening, sandwich defense, and canary tokens.
15 Years of Shipping Software Taught Me Email Deliverability is an Infrastructure Problem
Why developers treat email as an afterthought and what goes wrong at scale. IP warming, feedback loops, bounce handling, reputation management, and the architecture of a reliable email pipeline.
We Were Flying Blind on LLM Costs Until We Started Tracing Every Token
How we built token-level tracing to gain visibility into LLM costs, latency, and performance across providers. Architecture of the observability pipeline and the cost surprises we caught.
Traditional APM Cannot Track AI Errors. Here is What We Built Instead.
Why Sentry and Datadog fail for AI-specific errors like hallucinations, context overflows, and model degradation. Architecture of an AI-native error tracking system.
We Built an AI Gateway That Routes Across 13 LLM Providers. Here is How.
Architecture deep-dive into building a unified LLM proxy that routes requests across OpenAI, Anthropic, Google, Mistral, and more with load balancing, failover, and schema normalization.
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