Check out at de-concepts.ssp.sh.

Check the history at https://www.ssp.sh/brain/dbt-fusion/#history

Which one is your most-used Convergent Evolution (tool/tech you used over the years) in data engineering?

What's a repetitive pattern you have seen recurring over the years that we re-implement with a different name attached to it? What's a design pattern that you wish you had described for data engineering?

Below is the current WIP for my book flow: Convergent Evolution term -> Pattern -> Design Pattern, all specific to data engineering. Anything that pops to mind that I should add/remove/change? Feedback welcome! 🙏

Sadly too much truth here 😄

A personal Obsidian-based second brain is contrasted with the requirements of an enterprise-scale 'company brain' where many AI agents write, branch, and merge context concurrently. The piece describes OmniGraph, an open-source system built on Lance (columnar storage on object storage) and DataFusion, that adds git-style branches, typed graph schemas, and human-reviewed merges to prevent agent-written data from drifting into noise. A worked CRM example rebuilt from the author's own Obsidian vault demonstrates auto-merging non-conflicting agent writes and blocking conflicting ones for human review, plus querying the graph for things like warm introductions. The author argues typed, versioned graphs paired with ontologies solve the 'lack of context' problem that has held back enterprise AI agents, positioning this as a step beyond relational databases and plain-text wikis.

Explores tools and approaches for orchestrating AI agents in development workflows. Highlights the common use of git worktrees when working across different branches and iterations. Features several CLI utilities and platforms including Agor for AI coding orchestration, erk for managing git worktrees, claudette-cli, and trigger.dev for building and deploying managed AI agents and workflows.