https://blog.turboawesome.win/posts/ Recent content in Posts on Bits, Trades & Systems Hugo en-us Wed, 13 May 2026 09:00:00 +0000 https://blog.turboawesome.win/2026/05/a-software-engineer-plays-quant-building-a-market-data-research-stack-in-python/ Wed, 13 May 2026 09:00:00 +0000 https://blog.turboawesome.win/2026/05/a-software-engineer-plays-quant-building-a-market-data-research-stack-in-python/ I spent a decade building the systems trading firms run on, without ever being the person making the trading decisions. This is the first post in a series where I cross the floor — a software engineer applying engineering discipline to market-data analysis in Python with numpy and pandas. Starting with the unglamorous foundation everything else depends on. https://blog.turboawesome.win/2025/10/migrating-a-production-service-from-zap-to-slog-notes-from-the-trenches/ Tue, 07 Oct 2025 09:15:00 +0000 https://blog.turboawesome.win/2025/10/migrating-a-production-service-from-zap-to-slog-notes-from-the-trenches/ log/slog landed in the standard library in Go 1.21, but most production services are still on zap or zerolog. Here is what an actual migration looks like: where slog wins, where zap still wins, and how to move incrementally without a big-bang rewrite. https://blog.turboawesome.win/2025/08/context-engineering-what-the-term-actually-means-and-what-it-doesnt/ Tue, 19 Aug 2025 09:30:00 +0000 https://blog.turboawesome.win/2025/08/context-engineering-what-the-term-actually-means-and-what-it-doesnt/ "Context engineering" became the term of the year in 2025, mostly used to mean nothing. Here is what it actually refers to as an engineering discipline: managing the finite token budget of a model's context window as a resource, with the same rigour you'd apply to memory or a cache. https://blog.turboawesome.win/2025/06/go-1.23-range-over-functions-what-its-for-and-what-it-isnt/ Wed, 18 Jun 2025 09:00:00 +0000 https://blog.turboawesome.win/2025/06/go-1.23-range-over-functions-what-its-for-and-what-it-isnt/ Go 1.23 shipped range over functions — the ability to range over an iterator function rather than a slice, map, or channel. The feature is genuinely useful for a specific class of problems and genuinely misunderstood by engineers reaching for it in places where a slice works better. https://blog.turboawesome.win/2025/05/evaluating-llm-integrated-systems-what-works-and-what-doesnt/ Wed, 07 May 2025 11:00:00 +0000 https://blog.turboawesome.win/2025/05/evaluating-llm-integrated-systems-what-works-and-what-doesnt/ LLM outputs are probabilistic and context-dependent. The testing and evaluation approaches from deterministic software don't transfer directly. What does work: eval datasets, LLM-as-judge, regression suites, and the practices that separate teams with confidence from teams flying blind. https://blog.turboawesome.win/2025/04/distributed-consistency-models-what-your-service-actually-guarantees/ Wed, 16 Apr 2025 13:12:00 +0000 https://blog.turboawesome.win/2025/04/distributed-consistency-models-what-your-service-actually-guarantees/ Linearisability, serializability, eventual consistency, causal consistency — these terms are used loosely and understood imprecisely. Knowing what your data store actually guarantees determines whether your distributed system is correct. https://blog.turboawesome.win/2025/03/ai-native-development-what-it-actually-means-to-use-these-tools-well/ Wed, 05 Mar 2025 10:55:00 +0000 https://blog.turboawesome.win/2025/03/ai-native-development-what-it-actually-means-to-use-these-tools-well/ AI coding tools have changed the texture of software development. Not by writing code for you, but by changing what's worth doing yourself and what isn't. A practitioner's view of where the leverage actually is. https://blog.turboawesome.win/2025/01/staff-engineer-or-engineering-manager-on-choosing-the-road-that-doesnt-come-back/ Wed, 22 Jan 2025 11:15:00 +0000 https://blog.turboawesome.win/2025/01/staff-engineer-or-engineering-manager-on-choosing-the-road-that-doesnt-come-back/ Thirteen years in, the fork in the road becomes real. The honest framing of what each path actually involves, and why the choice is more reversible than people claim — and less. https://blog.turboawesome.win/2025/01/building-with-ai-coding-tools-what-actually-changes-and-what-doesnt/ Wed, 22 Jan 2025 10:08:00 +0000 https://blog.turboawesome.win/2025/01/building-with-ai-coding-tools-what-actually-changes-and-what-doesnt/ A year into using AI coding assistants seriously: what they've changed about how I work, where they still fall short, and the habits that make the difference between AI as a demo and AI as a productivity multiplier. https://blog.turboawesome.win/2024/11/cross-team-technical-alignment-at-scale/ Wed, 20 Nov 2024 10:30:00 +0000 https://blog.turboawesome.win/2024/11/cross-team-technical-alignment-at-scale/ Getting multiple engineering teams to agree on technical direction is hard. The approaches that work — architecture forums, decision records, working groups — and why lightweight coordination beats heavy governance. https://blog.turboawesome.win/2024/10/tail-based-trace-sampling-why-head-sampling-is-usually-wrong/ Wed, 09 Oct 2024 13:00:00 +0000 https://blog.turboawesome.win/2024/10/tail-based-trace-sampling-why-head-sampling-is-usually-wrong/ Head-based sampling decides whether to trace a request at the start. Tail-based sampling decides after the request completes. For finding latency outliers and errors, tail-based sampling is almost always what you want — and almost never what gets implemented. https://blog.turboawesome.win/2024/09/rag-systems-in-production-what-the-tutorials-dont-cover/ Wed, 11 Sep 2024 10:44:00 +0000 https://blog.turboawesome.win/2024/09/rag-systems-in-production-what-the-tutorials-dont-cover/ Retrieval-Augmented Generation works well in demos and breaks in interesting ways in production. The gap between 'it answers questions' and 'it reliably answers questions correctly' is where most of the engineering lives. https://blog.turboawesome.win/2024/08/writing-rfcs-for-wide-audiences/ Wed, 21 Aug 2024 09:45:00 +0000 https://blog.turboawesome.win/2024/08/writing-rfcs-for-wide-audiences/ RFCs that need sign-off from multiple teams or leadership require a different structure than internal team proposals. The writing changes when the audience includes people who don't share your context. https://blog.turboawesome.win/2024/07/llm-integration-patterns-for-backend-engineers/ Wed, 10 Jul 2024 09:38:00 +0000 https://blog.turboawesome.win/2024/07/llm-integration-patterns-for-backend-engineers/ Integrating LLMs into backend systems requires engineering discipline that the AI ecosystem tutorials often skip. Structured output, function calling, retry strategy, and testing patterns from production. https://blog.turboawesome.win/2024/05/observability-at-scale-what-good-looks-like-when-you-have-too-much-data/ Wed, 29 May 2024 09:47:00 +0000 https://blog.turboawesome.win/2024/05/observability-at-scale-what-good-looks-like-when-you-have-too-much-data/ Observability problems at large scale are different from small-scale ones. Too little signal is replaced by too much signal, and the engineering challenge inverts. https://blog.turboawesome.win/2024/05/evaluating-llm-applications-why-it-looks-good-is-not-enough/ Tue, 14 May 2024 14:22:00 +0000 https://blog.turboawesome.win/2024/05/evaluating-llm-applications-why-it-looks-good-is-not-enough/ LLM applications fail in ways that traditional software testing doesn't catch. Building evaluation frameworks that give you real signal about quality — before and after deployment — is the engineering challenge that separates serious AI products from demos. https://blog.turboawesome.win/2024/03/cache-design-as-a-reliability-practice-not-an-optimisation/ Wed, 27 Mar 2024 11:47:00 +0000 https://blog.turboawesome.win/2024/03/cache-design-as-a-reliability-practice-not-an-optimisation/ Most engineers add caches to make things faster. At scale, the more important reason to design caches carefully is reliability — a cache failure should not cascade into a system failure. The patterns that prevent that are different from the patterns that optimise for speed. https://blog.turboawesome.win/2024/02/engineering-at-enterprise-scale-what-changes-when-the-system-is-actually-big/ Wed, 14 Feb 2024 10:22:00 +0000 https://blog.turboawesome.win/2024/02/engineering-at-enterprise-scale-what-changes-when-the-system-is-actually-big/ After a decade in financial technology — trading firms, institutions, a startup, a European fintech — joining a large US technology company. The technical and organisational delta. https://blog.turboawesome.win/2023/11/eleven-years-in-a-retrospective-on-careers-choices-and-compounding-knowledge/ Wed, 15 Nov 2023 15:41:00 +0000 https://blog.turboawesome.win/2023/11/eleven-years-in-a-retrospective-on-careers-choices-and-compounding-knowledge/ Eleven years of software engineering across trading firms, financial institutions, startups, and large technology companies. What compounds, what doesn't, and the decisions I'd make differently. https://blog.turboawesome.win/2023/10/gos-race-detector-in-ci-catching-data-races-before-they-catch-you/ Wed, 04 Oct 2023 09:35:00 +0000 https://blog.turboawesome.win/2023/10/gos-race-detector-in-ci-catching-data-races-before-they-catch-you/ Data races are among the hardest bugs to find and reproduce. Go's built-in race detector finds them automatically — if you run it. Here's how to integrate it into CI effectively and what to do when it fires.