https://miasyster.github.io/en/tags/architecture/Recent content in Architecture on AI + Quant EngineeringHugoenFri, 08 May 2026 00:00:00 +0000https://miasyster.github.io/en/posts/cross-model-review-is-architecture/Fri, 08 May 2026 00:00:00 +0000https://miasyster.github.io/en/posts/cross-model-review-is-architecture/Single-LLM self-reflection has a structural blind spot — the model tends to confirm its own output. QuantGPT enforces a hard rule in factor-mine SKILL Phase 0.5: Claude must consult DeepSeek before designing a new factor family. Not a suggestion, a hard rule. This isn’t redundancy — it’s the antidote to structural bias.https://miasyster.github.io/en/posts/agent-native-architecture/Fri, 01 May 2026 00:00:00 +0000https://miasyster.github.io/en/posts/agent-native-architecture/When the system operator changes from a human to an LLM Agent, design principles need fundamental rethinking. Humans need GUIs and documentation. Agents need semantically clear tools and constraints that throw errors.https://miasyster.github.io/en/posts/why-agent-infra-not-agent/Fri, 01 May 2026 00:00:00 +0000https://miasyster.github.io/en/posts/why-agent-infra-not-agent/While everyone is building Agent frameworks, I chose a different path: build infrastructure for Agents, not the Agent itself. Not because I can’t build Agents, but because the Agent layer is a consumable — infrastructure is an asset.https://miasyster.github.io/en/posts/skill-orchestration-over-agent-loops/Thu, 30 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/skill-orchestration-over-agent-loops/Current AI Agent frameworks obsess over building complex loop chains: Planner → Executor → Reflector → Re-planner. I chose the opposite: tools are stateless pure functions, and the LLM decides the call sequence itself. Not because loop chains aren’t cool — but because they put decision authority in the wrong place.https://miasyster.github.io/en/posts/expression-parser-is-a-compiler/Wed, 29 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/expression-parser-is-a-compiler/QuantGPT’s core is an 870+ line hand-written recursive descent parser supporting 80+ operators, automatic cross-sectional/time-series grouping, and dual-mode compilation. Not because I didn’t know eval() is simpler — but because what eval() can’t do happens to be what matters most.https://miasyster.github.io/en/posts/api-guard-pattern/Tue, 28 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/api-guard-pattern/QuantGPT uses threading.local to enforce a runtime guard: all backtest calls must go through the API boundary. Direct function calls raise an exception. Not because the function is dangerous — but because a system without boundaries can’t be audited.https://miasyster.github.io/en/posts/anti-overfit-is-architecture/Mon, 27 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/anti-overfit-is-architecture/Most backtest systems treat anti-overfit as an optional add-on check — run the backtest, then test for overfitting if you feel like it. QuantGPT builds it into the scoring system and evolution engine: anti-overfit results directly affect factor scores, and the evolution engine reads anti-overfit metrics to decide its next strategy. Factors that haven’t proven robustness don’t even qualify for iteration.https://miasyster.github.io/en/posts/ai-as-operator/Thu, 02 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/ai-as-operator/Letting AI drive research workflows doesn’t mean letting AI decide how the system runs. I made a key separation: AI is just the operator, the execution engine is the law. This decision came from a failure.https://miasyster.github.io/en/posts/design-for-the-endgame/Thu, 02 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/design-for-the-endgame/Most systems are designed to run first, then audited as an afterthought. I inverted the order — first define what questions the system must answer when things go wrong, then work backwards to what each layer must record. This inversion reshaped the entire architecture.https://miasyster.github.io/en/posts/why-not-multi-agent/Thu, 02 Apr 2026 00:00:00 +0000https://miasyster.github.io/en/posts/why-not-multi-agent/Multi-agent is the hot paradigm in AI engineering. I chose single agent + state machine for my AI-driven quant research system. Not because multi-agent is too hard, but because the problem structure doesn’t match.