The Builder Path: From First Trace to Production-Grade AI Evaluation

The LayerLens Team builds and maintains Stratix, the continuous evaluation infrastructure for production AI teams.

TL;DR

• The Builder Path is a 14-step, 1-hour-50-minute structured track for engineers who need to instrument an AI system, wire AI judges, and put evaluations into CI/CD.

• It starts with a first trace in 10 minutes and ends with a production deployment reference architecture.

• The path covers the full SDK surface: async clients, CLI automation, datasets, trace data models, and judge configuration DSL.

• Engineers who complete it leave with a working evaluation pipeline, not just conceptual familiarity.

• Access it at stratix.layerlens.ai/learning.

What the Builder Path Is

Most AI teams instrument their systems late, after a production failure surfaces that they had no way to detect. The Builder Path is designed to close that gap fast. It is a structured, hands-on curriculum for engineers who are actively building AI products and need evaluation infrastructure in place before the next deploy.

The path runs 1 hour and 50 minutes across 14 steps, mixing short video walkthroughs with hands-on tutorials. It does not assume prior experience with LayerLens. It does assume you are writing code.

What the Path Covers

The path opens with two quick-start tutorials (steps 1 and 6) that give engineers a working trace and a running evaluation within the first session. These are checkpoints, not preambles. After each one, the SDK fundamentals modules fill in the underlying mechanics.

Steps 2 through 5 cover the four core SDK surfaces engineers touch every day. Step 2 handles installation and first trace. Step 3 introduces AI judges and code scorers, the two grader types the platform supports. Step 4 covers triggering evaluation runs and polling for results. Step 5 covers CLI commands, datasets, and automation patterns for integrating evaluations into pipelines.

Steps 7 and 8 move from setup to operation. Step 7 walks through building a custom AI judge from scratch, covering criteria configuration and verdict thresholds. Step 8 covers the comparison interface, where evaluation results across models, judges, and runs are set side by side.

Step 9 handles migration: importing existing Langfuse traces into LayerLens without losing historical data. For teams switching instrumentation tools, this step prevents the evaluation gap that typically follows a migration.

Steps 10 and 11 are the best-practices modules. Step 10 covers production-grade trace collection patterns: structuring spans, managing upload volume, handling multi-service environments. Step 11 covers CI/CD integration, specifically how to wire evaluations as quality gates that block deployment on regression.

Steps 12 through 14 are reference-grade deep dives. Step 12 is the AI judge configuration deep dive, covering weighted criteria, rubric DSL, version management, and severity mappings. Step 13 covers the trace data model: JSON structure, span types, upload methods, and storage strategies. Step 14 presents the production deployment reference architecture.

Who This Path Is For

The Builder Path is designed for engineers who are instrumenting AI systems and need a working evaluation setup, not a conceptual overview. The right candidates are teams that have already chosen or are evaluating Stratix as their evaluation infrastructure, and engineers who want to move from zero instrumentation to a CI/CD-integrated evaluation pipeline.

The intermediate level designation reflects the path's assumption that you are comfortable with Python and understand what a trace is, but have not necessarily used an AI evaluation platform before. Teams that need to orient decision-makers or procurement leads to the platform first should start with the Researcher Path instead.

Key Takeaways

• 14 steps, 1 hour 50 minutes, intermediate level: this is the fastest structured route to a production-ready evaluation setup on Stratix.

• The path covers the full SDK surface: async clients, CLI automation, datasets, AI judges, code scorers, and trace collection.

• Quick-start checkpoints at steps 1 and 6 give engineers working artifacts before the deeper content.

• CI/CD integration is a first-class topic in step 11, covering evaluation gates that block on regression.

• The final three steps are reference documents, not tutorials: engineers can return to them after completing the path without re-reading introductory content.

• The path links out to the Researcher Path for teams that need stakeholder orientation first, and to the Operator Path for teams ready to configure production observability.

Frequently Asked Questions

Is a LayerLens account required to start?

Yes. Steps 1 and 2 walk through account setup and API key configuration. The path assumes you have a Stratix account or are setting one up as part of the onboarding sequence.

How is this different from reading the documentation?

The path sequences content in the order that produces a working system fastest. Documentation is organized by feature. The path is organized by the workflow an engineer actually follows when instrumenting a production system. The quick-start tutorials at steps 1 and 6 are designed to produce working artifacts before you hit the deeper reference material.

Can steps be skipped for engineers already familiar with the SDK?

Yes. Each step is self-contained. If you have already uploaded traces, you can skip steps 1 and 2 and start from step 3 (AI judges and scorers). The path is structured so that later steps do not depend on earlier ones having been completed in sequence.

How long does CI/CD integration actually take to set up?

Step 11 covers the integration patterns. Setup time depends on your pipeline configuration, but the pattern is an evaluation run triggered as a pipeline step, with pass/fail thresholds determining whether the deployment proceeds. Engineers familiar with GitHub Actions or similar tooling typically complete the integration in a single session after working through the path.

What comes after completing the Builder Path?

The natural next step is the Operator Path, which covers production observability configuration: multi-judge suites, scheduled evaluation runs, cryptographic attestation, and audit-ready compliance reporting. The Operator Path assumes you have completed the Builder Path setup.

Does the path cover multi-agent trace structures?

Step 13 covers the trace data model, including span types used in multi-agent environments. Step 14, the production deployment reference architecture, addresses multi-service ingestion patterns. For a dedicated deep dive on agent traces, the Operator Path step on Trace Explorer covers multi-agent trace inspection in detail.

Methodology

The Builder Path curriculum was developed by the LayerLens engineering team based on the setup workflows observed across teams onboarding to Stratix. Content sequencing reflects the order in which teams encounter blockers when instrumenting AI systems without guidance: trace upload issues before judge configuration, CI/CD wiring before production observability. All tutorials are validated against the live Stratix API.

Start the Builder Path at stratix.layerlens.ai/learning, or browse all three paths and 158 content items in the Stratix Education Portal.