Technical deep-dives, AI strategy, and engineering perspectives from the team building autonomous systems.
Most Apple Silicon benchmarks publish a single decode number on an 8B model and stop. The interesting question for a real backend is what prefill, decode, and batch scaling look like on a 70B model under the runtimes you would actually ship: mlx-lm and llama.cpp. We tested both on M5 Max.
Most Shopify Hydrogen storefronts ship analytics late and ship it wrong. Pixel based tracking breaks under server side rendering, GA4 misses half the conversion events, and the team ends up rebuilding the funnel after launch. PostHog and Amplitude are the two product analytics platforms most enterprise headless teams pick between in 2026.
Every Apple Silicon local inference benchmark you have read runs for 30 seconds and quotes a peak number. Real backends serve requests for hours. We ran MLX and llama.cpp on M4 Pro, M5 Pro, and M5 Max for four hour continuous load tests and measured what the sustained token rate actually is once the SoC settles into its thermal envelope.
Claude Code, Cursor, and Windsurf each represent a different bet on how an AI coding tool should work. We tested all three on 40 real pull requests across a TypeScript monorepo, a Python service, and a Flutter app. Here is which one finished the work, which one stalled, and what the per task cost actually was.
Image performance is the single biggest lever for Core Web Vitals on a headless commerce storefront. The CDN you pick determines whether you ship a 2 second LCP or a 4 second one, and the cost difference between Cloudinary, Imgix, and Shopify's built in CDN is bigger than most architecture teams realize.
Choosing a merchant of record platform means handing off tax compliance, chargebacks, and payment infrastructure to a third party. Paddle and Lemon Squeezy both promise to handle that complexity, but they serve very different businesses. Here is a precise breakdown of where each wins.
Text-only local inference on Apple Silicon is a solved problem. Vision LLMs are not. The runtime support is uneven, the quantization story is half-finished, and the benchmarks people quote are usually wrong because they ignore image preprocessing cost. Here is what actually works on M4 Pro and M5 Pro hardware in mid-2026.
The three frontier models that actually ship code in production agentic loops are Claude Opus 4.8, GPT-5.5, and Gemini 3.1 Pro. Pairwise comparisons get traffic but lie about how engineering teams pick. Here is a three-way head to head on benchmarks that matter, plus the latency and cost numbers that move the decision.
Perplexity Computer and Claude Code both claim to be AI agents for developers, but they are solving different problems with different architectures. One is a browser-native research agent. The other is a terminal-native coding engine. Here is how they actually compare for engineering teams making the decision in 2026.
Open source headless commerce backends have stopped being toys. Saleor, Medusa, and Vendure are now legitimate alternatives to Shopify Plus and Salesforce Commerce Cloud for the right brand profile. Here is how they compare on architecture, extensibility, and what they cost you in engineering ownership.
Passwordless authentication is no longer a novelty. It is increasingly the default expectation for consumer applications where friction at login directly translates to abandoned sessions and lost revenue. Stytch and Magic.link are the two purpose-built platforms solving this problem, and they have diverged considerably in scope since 2022.
Most teams pick a serverless platform based on what cloud they are already in. That works until you start running AI inference workloads, and then the differences between AWS Lambda and Google Cloud Run start to matter in ways that hit your latency budgets and your invoice. Here is how they actually compare in 2026.