Composio vs Arcade vs Nango: AI Agent Authentication in 2026
A hands-on comparison of the three AI agent authentication platforms I evaluated for our own stack — plus where WorkOS and Merge fit, and which to pick for each scenario.
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A hands-on comparison of the three AI agent authentication platforms I evaluated for our own stack — plus where WorkOS and Merge fit, and which to pick for each scenario.
A hands-on comparison of GPTCache, Redis LangCache, Upstash, and Canopy for semantic caching, with real hit rates, costs, and threshold-tuning lessons from production.
A production-tested comparison of fixed-size, recursive, semantic, late chunking, and contextual retrieval for RAG — with 2026 benchmarks and the strategy I actually deploy.
Benchmark headlines say 94%, but production text-to-SQL fails silently on complex joins. Here's where it actually breaks in 2026 and the semantic-layer architecture that fixes it.
A hands-on 2026 comparison of DSPy, TextGrad, and GEPA for automatic prompt optimization — what each one optimizes, the published benchmarks, real production costs, and a decision matrix from running all three on live AI products.
GraphRAG promises smarter retrieval, but it can cost 40x more to index. Here is a production breakdown of GraphRAG vs vector RAG vs hybrid, with real 2026 cost, latency, and a decision matrix.
After shipping three agent rewrites of ContentForge AI Studio in 18 months, here is what LangGraph, CrewAI, OpenAI Agents SDK, and AutoGen v2 actually feel like in production — with token costs, latency numbers, and the pitfalls each one steers you into by default.
I shipped LLM batch APIs across three production AI products in 2026 and saved $2,800/month. Here is the head-to-head on OpenAI, Anthropic, and Vertex AI batch — discount math, real turnaround times, and when batch is the wrong answer.
I compared FLUX.1, Recraft V3, Ideogram 3.0, DALL-E 3 and Stable Image Ultra across 7 production sites generating 180 images/day. Real pricing, real latency, and what I actually run.
Hands-on comparison of the 4 LLM red teaming tools I shipped to production across 6 AI products at Warung Digital — what each catches, what it costs, and the kill-chain stack that found 91 severity-high vulnerabilities in 4 months.
Five rerankers tested for production RAG in 2026 - Cohere 3.5, Voyage 2.5, Jina v3, Mixedbread mxbai-large-v2, and FlashRank. BEIR scores, latency, cost, and the call I made for our aggregator stack.
A production-tested comparison of vLLM, SGLang, TensorRT-LLM, and Ollama for self-hosted LLM serving in 2026 — throughput, cold-start, cost math, and decision matrix from running a 4-product AI backend on a shared H100.