Videos

Same tool logic. Same host machine. Two boundaries. In this short, I compare an in-process tool path against the same tool running behind a remote MCP-style server boundary. The result was not close: local p95 landed at 0.018 ms, remote p95 landed at 12.716 ms, and the remote lane started dropping

The fastest backend on the chart still lost the production verdict. This short shows why raw throughput is not enough to pick a backend stack. In this video: - C# wins raw speed - Go wins the actual payoff score - Rust stays the efficiency specialist - memory and startup change the final decision

One chart is not enough for a production stack decision. Which Backend Actually Pays For Itself In 2026? In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bottleneck Comment with your stack and workload; I can publish the b

Rust winning this benchmark was not the weird part. The weird part was PHP taking second over Elixir under the same live load. Same /work endpoint. Same JSON payload. Same Podman host. Same concurrency ramp. Same sampling cadence. At c300, Rust stayed in a different class on throughput and memory.

Same `/work` endpoint. Same JSON payload. Same Podman box. Same live ramp from 10 to 300 concurrent users. Result: - Rust wins throughput, latency, and memory - PHP takes second place - Elixir pays the biggest memory tax in this run In this video: - live RSS ramp - throughput across c10, c50, c150

One chart is not enough for a production stack decision. Does Rust Save More Than Rust Devs Cost? In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bottleneck Watch the full breakdown on the channel for benchmark method, tr

Same microservice. Same database. Same read endpoint. Three very different throughput curves. Verified read throughput: - Go: 28,945 to 29,068 to 28,916 RPS - Rust: 11,364 to 11,024 to 11,349 RPS - ASP.NET: 24,474 to 14,055 to 14,159 RPS Go stayed flat across c=50, c=200, and c=500. Rust stayed st

We built the same HTTP API in four runtimes and measured final container image size with Podman on Apple M4. - Rust (scratch): 3.5 MB - Go (scratch): 5.65 MB - Python (Alpine): 53.4 MB - Node.js (Alpine): 163 MB Rust is 47x smaller than Node. Every pull, every deploy, every cold start in your clus

Node.js just ate 465 MB for the same API that Rust runs in 18 💀 same server, same endpoint, same machine. multiply by 100 instances and tell me memory doesn't matter.

AI agents are great at local correctness: generate code, pass the happy path, open the PR. But that does not prove system behavior. Retries, redirects, session state, cache invalidation, and fallback paths still have to be validated by humans. If QA is the first team discovering the design bug, y

Flutter teams asked the right follow-up: if Rust wins over pure Dart through dart:ffi, does Zig close the gap enough to change the pick? This video reruns the benchmark with the same shared Dart bridge, the same checksum gate, and a wider scenario sweep: - boundary-heavy - balanced - compute-heavy

Vector search won the overall quality chart in this benchmark. That does not mean you should delete grep from your stack. This short benchmarks 4 retrieval lanes across 255 documents, 112 labeled queries, and 7 developer-search scenarios: - `grep` for exact string search - `BM25` for lexical ranki