From Model Building to LLM Integration

November 7, 2025

A short guide to shipping useful AI features with clear evaluation, safe integration, and predictable costs.

Start with the product constraint

Before choosing a model, write down what “good” means for the feature:

• Latency and cost budgets
• Allowed failure modes (and what the UI should do)
• Data boundaries (PII, retention, logging)
• A measurable success metric (accuracy, resolution rate, time saved)

Model building: prefer baselines and iteration

If you’re training a model:

• Begin with a baseline (logistic regression, gradient boosting, a small transformer).
• Use a clean split strategy (time-based splits for temporal data).
• Track features, training data versions, and metrics per run.

Treat “model quality” as more than a single number: error clusters and edge cases matter.

LLM integration: treat it like a distributed system

LLMs are non-deterministic and rate-limited. Build for that:

• Use structured outputs (JSON schema) and validate aggressively.
• Add retries with backoff and idempotency keys.
• Implement fallbacks (smaller model, cached answer, human-in-the-loop).

Example (validate the response shape before using it):

type Answer = { answer: string; citations: string[] }

function isAnswer(x: unknown): x is Answer {
    return !!x &&
        typeof x === "object" &&
        typeof (x as any).answer === "string" &&
        Array.isArray((x as any).citations)
}

Vector databases: retrieval is a system, not a query

RAG works when the retrieval pipeline is solid:

• Chunking strategy is part of the model (size, overlap, metadata).
• Index with filters (tenant, permission, doc type).
• Evaluate retrieval separately from generation.

Agents: scope them tightly

Agents are great for multi-step workflows, but only when bounded:

• Explicit tools and permissions
• Tool-call auditing
• Hard limits on steps, time, and spending

Keep the “plan” separate from “execute,” and always log the tool trace.

References

• JSON Schema
• OpenTelemetry documentation