System One & Jev
Studies in this cluster, in series order. Each one keeps its own URL.
AI / ML
Retrieval, embeddings, vector indexes, evals, and serving patterns for senior interviews.
System One & Jev
6 studies- 1.System One Models & Jev — Fast Structured Decisions for SoftwareChat models optimize for preferred strings. Software needs typed, probabilistic decisions it can branch on without parsing prose. System One Models (TypeSafe, announced 2026-09-15) take unstructured state in and emit typed probabilistic decisions. Jev is the first public System One model — this hub maps the cluster.
- 2.Choice, Score & Noul — State, Parallel Questions & Typed AnswersSystem One usefulness lives in three primitives. Mis-picking the type is a common interview fail: using a Noul when you need ordered levels, or a free-form LLM parse when a closed Choice would do. This lesson teaches state, question IDs, criteria, parallel evaluation, and answer shapes — with sandbox mocks and no API keys.
- 3.Confidence-Gated Routing, Composite Scoring & Workflow DecompositionTyped answers alone do not make automation safe. Confidence (Choice/Score) and noul magnitude (yes/no) are the second axis: what vs whether to act. This lesson teaches stake-scaled thresholds, composite scores owned in code, and speculative fan-out — without re-teaching Structured Outputs validation loops.
- 4.Generators, yield & yield* — Composing Streams and Decision WorkflowsTwo composition styles collide in AI backends: sequential token streams via generators/yield, and one-shot parallel decision round-trips (System One). Interviews expect you to implement async generators for LLM chunks and to compose typed decision steps without confusing them with token streaming.
- 5.LLM Token Streaming vs Parallel Decisions — SSE, TTFT & When Not to StreamStaff interviews split “stream tokens for UX” from “await a structured decision.” Mixing them causes bad architectures: streaming a classifier, or blocking the UI for a paragraph that should have streamed. This lesson covers TTFT, SSE/chunked tokens, cancellation, backpressure, and when a System One parallel call is enough.
- 6.Hybrid Architecture — System One for Route/Guardrail, LLMs for ProseProduction systems rarely pick one model class. The winning shape: System One (or equivalent classifiers) for route, score, and guardrail; generative LLMs for explanations, drafts, and open-ended tools; deterministic code as the source of truth. This capstone wires primitives, confidence, generators, and streaming into an interview-ready architecture.