87 articles matching your search.
After shipping streaming for 6 production AI apps, I learned SSE, WebSocket, and polling each win different battles. Here is when to pick which, with real numbers from our Hostinger stack.
I tested four production LLM guardrail stacks across six AI products I shipped. Honest comparison of Lakera, NeMo Guardrails, Guardrails AI, and Pillar Security — latency, pricing, and what I actually run in production.
Choosing the wrong embedding model is the most expensive mistake in RAG. Here is a side-by-side comparison of OpenAI text-embedding-3-large, Voyage voyage-3-large, Cohere embed-v4, and Jina embeddings-v3 with real pricing math, latency, multilingual, and a clear decision matrix from production RAG experience.
A working engineer's view of the four libraries that actually solve the malformed-JSON problem in production AI: Instructor, BAML, Outlines, and Pydantic AI. Real benchmark numbers from 1.4M monthly LLM calls.
A firsthand comparison of four AI agent orchestration platforms — Inngest, Trigger.dev v3, Hatchet, and Temporal — across pricing, durability, language support, and real-world cost for production workflows in 2026.
After 18 months running AI search APIs across seven production aggregator sites, here is when to pick Tavily, Exa, Perplexity Sonar, or Linkup.
I ran the same LoRA fine-tune of Llama 3.1 8B on four platforms with 12,400 training pairs from our SmartExam product. Real costs, training times, inference latency, and the multi-adapter math that decided which one we shipped.
Last quarter, our Anthropic console showed $612 in API costs across our six AI products. After a focused prompt caching refactor, it dropped to $167 - a 73% cut without changing models. Here is exactly what worked, what didn't, and the mistakes that cost real money.
After eight months running Cline, Aider, Continue, and OpenHands across 50+ production projects, here is the honest comparison: real token costs, governance trade-offs, and which agent matches your team's actual workflow.
After porting a customer-support agent across all three frameworks, here is the honest TypeScript AI framework comparison for production in 2026 with benchmarks, code volume counts, and migration notes from real client work.
I ran E2B, Modal Sandboxes, and Daytona in production across 380K agent invocations at Warung Digital. Here is what I learned about cold starts, isolation, GPU support, and which one to pick for your AI agent code execution stack in 2026.
OpenAI bought Promptfoo for $86M in March 2026. Here is how the three leading LLM eval tools — Braintrust, Promptfoo, DeepEval — actually compare for production teams in May 2026.