Smarter Week

How to automate it

How to automate “train, tune and evaluate models”

Here are 2 ways to spend less time on this, best first. Each comes with steps you can follow today and, for AI fixes, a prompt to copy.

120 min
typically, a few times a week
40%
of the time can be automated
Some setup
to set up

Fix 1 of 2

Software featureBest fix

Track runs and tune automatically with MLflow or Weights & Biases

Experiment tracking logs every run's parameters and metrics, and managed tuning searches settings for you, so you stop keeping results in spreadsheets and rerunning by hand.

Typically saves about 30% of the time1 h to set up
  1. 1Add MLflow or Weights & Biases logging to your training code (a few lines).
  2. 2Use built-in sweeps or tuning (W&B Sweeps, Optuna, Databricks or SageMaker tuning) instead of manual grids.
  3. 3Compare runs in the dashboard and register the chosen model.
  4. 4Ask a coding agent to add the logging to existing scripts.

Tools: MLflow · Weights & Biases · Optuna · Databricks · Amazon SageMaker

Fix 2 of 2

AI

Use a coding agent on your dbt or pipeline repo

Claude Code, Codex, Cursor and Copilot can read the project, write models and tests, run dbt build and fix errors. You review the logic and the data it produces.

Typically saves about 30% of the time30 min to set up
  1. 1Add a short instructions file to the repo (CLAUDE.md or AGENTS.md) with naming conventions and how to run dbt and tests.
  2. 2Give the agent a well-scoped task with the prompt below.
  3. 3Let it run the build and tests against a dev target, never production.
  4. 4Review the SQL and check row counts against a known source before merging.
Prompt to copy
In this [DBT / AIRFLOW / DAGSTER] project, [TASK, e.g. add a model that calculates monthly active customers from events]. Follow the conventions in [EXAMPLE MODEL]. Add tests for [UNIQUENESS, NOT NULL, ACCEPTED VALUES] and a description for each column. Run the build against the dev target, fix any errors, and summarize what you changed plus anything you were unsure about. Do not run anything against production.

Tools: Claude Code, OpenAI Codex, Cursor or GitHub Copilot

Who does this task

Roles in our library that list this as one of their common tasks. Each guide covers the rest of that role’s week.

Data scientist

HourLeak · the 8-minute work audit

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Other common tasks for Data scientists