GFThe Grown-Ass Field Guide

FG / 03 / Field guide

AI

Learn through useful work: bounded authority, visible failures, repeatable evaluations, and a real quality bar.

What is moving now.

Separate models, products, workflows, agents, and the harness that makes them dependable. A model demo is not a production system, and an agent is not merely a longer prompt. Reliability lives in the surrounding constraints and feedback loops.

  1. 01

    Choose a repeated job

    Define inputs, output artifact, quality bar, privacy class, unacceptable failures, time saved, and the human decision that remains.

  2. 02

    Build the smallest loop

    Use explicit instructions, structured output, minimal tools, permission boundaries, logs, and a clear stop condition.

  3. 03

    Keep an evaluation set

    Save representative examples, known traps, latency, cost, tool failures, and review outcomes; rerun them after changes.

Context

Select, retrieve, compress, and isolate the information a model needs without treating a huge prompt as architecture.

Harness

Control tools, permissions, state, retries, handoffs, tracing, budgets, and durable work products.

Evaluation

Measure actual workflow quality with examples, graders, failure taxonomies, human review, and regression checks.

Choose models and platforms by the actual workflow: data sensitivity, quality, tool use, modalities, latency, cost, maintenance, auditability, retention, access control, and portability. Benchmark the work—not the launch demo.

Framework
before
affiliate

Start with voices you already value. Verify before concluding.

YouTube

9

Podcast

1

Instagram

6

Newsletter

7

App / Tool

5
  • Hermes AgentApp / Tool
  • Grok / Grok BotApp / Tool
  • Claude CodeApp / Tool
  • CodexApp / Tool
  • DGX Spark / StationApp / Tool

Reference layer

Use these to settle claims—not to manufacture certainty.

Independent analysis built from the strongest available evidence.

Concrete jobs where AI earns its place: the workflow, the human boundary, the failure modes, and what success looks like.

No use case has qualified yet.