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Scaling Go Websocket Servers to Millions of Concurrent Connections
The memory math nobody does up front
The Rails 8 Solid Suite: Moving to a Zero-Dependency Stack
Rails 8 (November 2024) did something bold: it made the database the default home for everything that used to need Redis. Solid Queue for background...
DeepSeek-R1 reasoning models: Reinforcement Learning without Supervised Fine-Tuning
The standard recipe for a “reasoning” model is crushing amounts of supervised data: millions of human-curated chain-of-thought traces, distilled from a bigger model, cleaned by...
Fine-tuning vs Prompt-engineering – what to choose in 2025
The 2023 version of this question was about knowledge: “should we fine-tune so the model knows our domain?” That framing is dead in 2025. Current...
Rails 7.2 — Better eager loading with Zeitwerk
Rails 7.2 (August 2024) did not ship a magic filter that “skips patterns” during eager loading — that idea circulates in a lot of upgrade...
Unlocking Speed: Rails Performance Tuning with Ruby 3 YJIT
In Ruby 3.3, YJIT is production-ready. Shopify’s numbers, the Optcarrot benchmark, and the Rails core team all point the same direction: roughly 15–25% latency improvement...
Pattern-matching refinements in Ruby 3.3
If you read the Ruby 3.3 changelog looking for “right-hand patterns”, stop. Pattern matching arrived in Ruby 2.7, and the => rightward assignment shipped in...
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Real-Time Event Streaming in Rails using ActionController::Live and Server-Sent Events (SSE)
“Real-time dashboard” is the feature that silently becomes an architecture decision. The naive version polls a JSON endpoint every second: one client is nothing, but 500 dashboards at 1 req/s...
Speculative Decoding: Accelerating LLM Inference in Production
Decode is memory-bandwidth-bound, and that single fact is why speculative decoding is the cheapest throughput win an inference team can spend a week on. Every autoregressive step loads the entire...
Scaling Go Websocket Servers to Millions of Concurrent Connections
The memory math nobody does up front
Agent Orchestration: Comparing ReAct, Plan-and-Solve, and Reflection Patterns
Almost every agent starts as a naive while True: call_model, run_tool, call_model loop, and almost every production agent ends up as something else. The reason is that the three canonical...
Serialization Benchmarks: Go JSON vs. Protobuf vs. FlatBuffers
Why serialization keeps topping your pprof
Enterprise Text-to-SQL: Building Self-Correcting Execution Loops
Text-to-SQL looks solved in demos and falls apart in production, always in the same four ways: the model invents column names the schema never had, it emits syntax that parses...