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FDE Curriculum Audit — High-Reasoning Model Evaluation
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FDE Curriculum Audit — High-Reasoning Model Evaluation

Compare models on realistic tasks from an ongoing Frontier Deployed Engineer (FDE) and AI-engineering curriculum project. Evaluate long-context reasoning, consistency across governing documents, dependency analysis, production reliability, evidence discipline, code-review judgment, and minimal-change planning. Prefer correct, verifiable, actionable answers over confident speculation, verbosity, or generic advice. The goal is to select the model best suited to continue an existing project without redesigning it from scratch or inventing unsupported facts.

Prompt

You are a senior technical curriculum auditor continuing an existing Frontier Deployed Engineer (FDE) and AI-engineering roadmap. Your task is to audit and improve the existing curriculum, not redesign it from scratch. PROJECT CONTEXT The mission is to take a real business problem through discovery, solution selection (including non-AI alternatives), implementation, evaluation, security, deployment, integration into work, impact measurement, and handover. The learner already has C++, object-oriented programming, and data structures and algorithms experience. Do not teach beginner programming or generic algorithms. The current roadmap uses lesson IDs in the P<phase>.<number> format. Backend and API-integration practice uses TypeScript/Node.js in Phases 2–10. Python starts at P11.2 for AI-engineering labs; do not create two parallel curricula. Existing coverage includes P4.1–P4.7 for HTTP and API contracts; P5 for relational data and migrations; P6 for transactions and concurrency; P7 for architecture, testing, and code review; P8 for distributed systems; P9 for production engineering; and P11 onward for AI-engineering capabilities. Preliminary findings: provider contract discovery and credential lifecycle need better proof; P4.8 is proposed for third-party API onboarding, provider guarantees, token lifecycle, and contract drift. Existing foundations must not be marked missing merely because they use different terminology. Outbox is P8.6; webhook receipt and inbox-style deduplication involve P8.4 and P8.2; reconciliation is P8.7; retry deadlines and jitter are P8.3. Some gaps concern proof, dependencies, evidence, or outdated wording rather than missing topics. Preserve IDs. Documentation does not establish actual code behavior, and a source landing page does not prove a specific technical claim. TASK Produce a prioritized audit and change plan. Identify the six highest-priority changes and give the affected lesson/file, real gap, classification (missing capability, partial coverage, proof/practice gap, evidence gap, dependency gap, duplication, or outdated wording), smallest justified change, acceptance evidence, and priority. Evaluate whether P4.8 is warranted without duplicating existing topics. Identify dependency corrections and justify them. Separate established facts from provisional findings and verification needs. List five consequential checks before implementation and identify changes that must remain proposals pending approval. CONSTRAINTS Do not assume access to unprovided files, repositories, code, books, or prior conversations. Do not invent source IDs, quotations, verification results, or repository behavior. Preserve uncertainty. Prefer minimal justified changes, not a roadmap rewrite. Make the reasoning behind classifications and priorities explicit.

Answer guidance

A strong answer preserves the TypeScript/Node.js versus Python phase boundary; does not mistake existing P4–P9 foundations for missing topics; evaluates P4.8 as the narrowly scoped provider-contract and credential-lifecycle addition; preserves lesson IDs; prioritizes demonstrable evidence and production risk; identifies dependency changes with reasons; and explicitly distinguishes project facts, proposals, and unverified claims. It should not claim to have read or edited files that were not provided.

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