Academy

Series · Builders · Step 5

Model Selection

Choosing the right language model is not about picking the most capable one — it is about finding the one that fits your task, context length, output requirements, and cost constraints. This series builds a practical, vendor-neutral framework for making that decision well. We start with why attention is a finite resource, work through a structured way to choose and to pair a primary with a verifier, and close with a look at the hidden costs that make apparently cheap choices expensive at scale.

7 pieces, in order

  1. Part 1: Stop ranking LLMs, start profiling them

    Step 5 · 6 min

  2. Part 2: A practical checklist for picking an LLM for your feature

    Step 5 · 4 min

  3. Part 3: When no single model is enough: the primary and verifier pattern

    Step 5 · 4 min

  4. Part 4: Common failure modes in LLM systems — and how to catch them

    Step 5 · 5 min

  5. Part 5: The rule layer: deterministic guardrails around a probabilistic model

    Step 5 · 4 min

  6. Part 6: Evaluate models on your own set, not the public leaderboard

    Step 5 · 6 min

  7. Part 7: Grading what you can't exact-match

    Step 5 · 9 min

All series

For Builders

Steps 1–5 · 5 pieces

Agent Architecture & Coordination

Builders · Steps 3–4 · 12 pieces

Prompting & Context

Builders · Step 2 · 5 pieces

Model Selection

Builders · Step 5 · 7 pieces

Fine-Tuning & Adaptation

Builders · Steps 2–5 · 7 pieces

LLM Infrastructure & Serving

Builders · Step 5 · 6 pieces

For Your Business

Steps 1–5 · 5 pieces

Trust & Autonomy

Business · Steps 3–5 · 5 pieces

What AI Actually Is

Business · Step 1 · 4 pieces

The Chatbot & Its Ceiling

Business · Steps 1–2 · 3 pieces

Agentic Operations & CRM

Business · Step 4 · 5 pieces

Control, Isolation & Fit

Business · Step 5 · 5 pieces