Location: 200 E Randolph St. Chicago Floor 25

Date Oct 20th 2026

Speakers 

Thoughtworks: Eric Nagler and Arun Srinivasan

Databricks: Kevin Hartman

Host

Thoughtworks

Agenda: 

5:00-5:30p.m Happy Hour

5:30 (45–60 min) — AI-Ready Semantic Layers: from ontology to Genie

- The problem: metric views give agents dimensions & formulas, not part-of / is-a / rolls-up-to — and Genie Ontology only infers what your assets already encode (the "right answer, wrong rollup" failure — not a model problem).

- The moat: the platform moved the floor; the domain-specific semantic layer (metric views, glossaries, ontology) is still the differentiator.

- The build: rapid discovery with the Ontology Accelerator → where to model non-metric concepts (tables vs. UC semantics vs. ontology vs. agent) → two live demos (infer vs. supply; end-to-end Genie Agent).

6:30 (~60 min) — Consort (open source)  

- What it is: keeps AI-written code clean and correct — a deterministic state machine drives /plan → /design → /build → /deploy so agents can't skip steps, weaken tests, or drift from spec.

- Why Lakebase: every git branch auto-pairs with a copy-on-write Postgres branch in ~1s — tests run against real data, not mocks, and schema evolves in lockstep with code.

- How it works: 8 role agents (Spec Author, Architect, DBA, Test Strategist, UX, Navigator, Driver, Product Owner) communicate only through immutable artifacts; RED → GREEN → refactor; human-approval gates that fail closed.

- The differentiator: engineering discipline enforced by contract, not suggestions — "green" means a real test pass on live infra. Live /consort:start scaffolds repo + paired DB + agents (StockFlow sample).