From the Team
Engineering insights, product updates, tutorials, and industry analysis from the Transactional team.
Webhooks Will Fail. Here are the Retry and Idempotency Patterns That Save You.
Practical patterns for reliable webhook delivery: exponential backoff with jitter, idempotency keys, dead letter queues, and signature verification. TypeScript code included.
We Evaluated 12 LLM Observability Tools. Most of Them Do Not Matter.
A practical evaluation of LLM observability tools across tracing, cost tracking, quality monitoring, and prompt management. What matters, what is marketing, and what to actually look for.
An Enterprise Team Was Shipping Hallucinations to Users. Traces Showed Them Where.
How an enterprise company with AI-powered customer support reduced hallucination rates from 8% to 0.3% and cut AI issue MTTR from days to minutes using LLM observability and trace-level analysis.
Your AI Agent Will Crash in Production. Plan for It.
Common AI agent failure modes and how to handle them: tool execution failures, context window overflow, infinite loops, and hallucinated function calls. Production-ready error patterns with code.
A Fintech Team Cut Their LLM Bill by 70%. Here is Exactly How.
How a fintech company processing loan applications with LLMs reduced their monthly AI spend from $15K to $4.5K using semantic caching, fallback routing, and token optimization.
From 78% to 99.5% Inbox Placement. One SaaS Team's Email Fix.
How a B2B SaaS sending 2M transactional emails per month went from 78% inbox placement to 99.5% in 6 weeks by fixing authentication, IP reputation, and sending practices.
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.
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The EU AI Act Starts Enforcing in August. Here is What You Need to Do.
The EU AI Act enforcement begins August 2026. A practical guide for developers building AI features, covering risk classification, documentation requirements, and compliance steps.
Your Developers Are Already Using AI Tools You Do Not Know About
Shadow AI is the new shadow IT. Developers are using ChatGPT, Copilot, and Claude without oversight. Blocking them is not the answer. Here is a governance framework that actually works.
AI Security in 2026: 77% of Companies Have No Policy. That is a Problem.
Most enterprises have deployed AI without any security policy. Here is what a minimal AI security framework looks like and why you need one before August.
Build an AI Chatbot with Persistent Memory in 30 Minutes
Step-by-step tutorial for building an AI chatbot that remembers previous conversations using vector storage, embeddings, and context retrieval. TypeScript code throughout.
Agentic AI is the Biggest Security Risk Nobody is Talking About
Autonomous AI agents are proliferating across enterprises. The security implications of giving AI tools, credentials, and decision-making power are massive and largely unaddressed.
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.
RAG is Probably the Weakest Link in Your AI Security Chain
Retrieval-Augmented Generation pipelines introduce unique security vulnerabilities that most teams overlook. Data poisoning, prompt injection via context, and access control gaps are endemic.
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.
JWT Authentication in 2026: What Most Tutorials Get Wrong
Common JWT mistakes that compromise security, and the correct patterns for token storage, rotation, and validation. Includes Express and Next.js code examples.
Stop Writing Raw HTML Emails. Use React Email Templates Instead.
Build maintainable, responsive email templates using React Email instead of struggling with raw HTML tables. Includes password reset and order confirmation examples.
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.
Your AI Should Never Go Down. Here is How to Set Up Fallback Routing.
Configure fallback chains across LLM providers so your AI features stay up when any single provider goes down. Includes TypeScript implementation with health checks and cost-aware routing.
Track Your LLM Costs in Real-Time Before They Surprise You
Set up real-time cost tracking for LLM API calls with token counting, dashboards, alert thresholds, and budget controls. Practical TypeScript examples included.
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.
BIMI Puts Your Logo in the Inbox. Here is Why That Changes Everything for Email.
BIMI displays your brand logo next to emails in the inbox. With 10-15% open rate improvements and growing adoption, here is why BIMI matters and how to implement it.
Every Token, Every Trace, Every Dollar. Introducing LLM Observability.
Traditional APM tools were not built for LLM workloads. LLM Observability gives you token-level tracing, cost attribution, latency breakdowns, quality scoring, and prompt version tracking.
Only 16% of Domains Have DMARC. Yours Probably Does Not Either.
Email authentication adoption remains shockingly low despite enforcement by Google and Yahoo. Here is the current landscape and what needs to change.
We Got Tired of Errors Reaching Users First. So We Built Error Tracking.
Error tracking built for AI-native applications. Groups errors by semantic similarity, integrates with LLM traces, and catches AI-specific failure modes that traditional tools miss.
Set Up SPF, DKIM and DMARC Correctly the First Time (2026 Guide)
A step-by-step guide to configuring SPF, DKIM, and DMARC DNS records for your domain. Avoid the common mistakes that break email deliverability.
We Built One API for All LLM Providers. Introducing AI Gateway.
Meet AI Gateway: a single unified API that routes to 13+ LLM providers with automatic failover, cost tracking, semantic caching, rate limiting, and prompt management.
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