v0.8.0

v0.8.0 - 2026-06-17

Added

• make scaffold-lock-upgrade re-resolves the bundled workspace's uv.lock to the newest dependency versions its pyproject.toml allows (PKG=<name> to bump a single package), with a companion make scaffold-lock-check drift guard. Matching make lock-upgrade / make lock-check targets do the same for the root uv.lock; both checks run in CI and are included in make ci.

Changed

• Bundled AI toolkits are now one-shot and data-exploration (previously one-shot-pipeline and dlthub-platform). The one-shot toolkit is reshaped around create-minimal-pipeline and deploy-minimal-pipeline; the platform deployment toolkit (deploy-workspace, prepare-deployment, setup-runtime, debug-deployment, …) is dropped in favor of data-exploration (explore-data, build-notebook).
• Bumped WORKBENCH_REF to a6a4b08e and refreshed the bundled AI workbench scaffolds across all agents (claude/codex/cursor).
• Widened the startup banner logo so it no longer renders compressed, and added a blank line above it for spacing.
• The minimal workspace now loads into the managed, zero-config playground delta destination instead of local warehouse (duckdb), so data persists across ephemeral job runs. Bumps the dlt floor to [hub,deltalake]>=1.27.2 (drops the unused filesystem extra, adds deltalake which pulls deltalake/pyarrow; 1.28.0 in uv.lock) and drops the orphaned [destination.warehouse] block.
• After the first pipeline run, the CLI no longer streams the run's logs live or opens the workspace overview. It now submits the run without --follow and then surfaces it with dlthub job runs show pipeline.load_sample_shop, so the user sees the run and its logs instead of an overview page.
• The starter prompt handed to the coding agent is now a concrete example — "Load the 50 most recent GitHub issues from https://github.com/dlt-hub/dlt and show me the data on the dltHub query editor" — instead of the fill-in-the-blanks "Build a dlt pipeline for the [API name] API and load [endpoint/data] into DuckDB."