kylettra@usc.edu
Real Estate Finance · Applied Analytics · AI
USC B.S. Real Estate Development · Minor, Finance & Applied Analytics
AI project · News agent

The CRE Finance & Tech Brief.

An agent I built reads 400 sources a week. I edit what survives. Mondays, 10 AM PT.

Free · Every claim sourced

Agent run · latestMon 23:00 UTC
412
Sources
2,100+
Items/week
28
Issues
5
Min read

Three sections, every Monday

What's inside each issue
§ 01

AI models & tools

Claude releasesDeprecationsToken pricing
§ 02

The agent stack

Copilot/M365Claude CodeAgent frameworks
§ 03

Proptech & CRE fintech

CRE debtData centersProptech M&A

How the agent works

Collect → Draft → My pass
01

Collect

412 feeds swept every Monday at 23:00 UTC — RSS, APIs, filings.

02

Cluster

Embeddings dedupe roughly 2,100 items down to ~220 distinct stories.

03

Score

CRE-relevance weighting ranks stories; the top 22 survive to draft.

04

Draft

Claude drafts all three sections with citations back to source.

05

My pass

I read every line, cut what does not hold up, and send it myself.

Built in three weekends

Python 3.12Claude APIasynciopgvectorPostgresActions cronMailerLite

The whole pipeline runs on a scheduled GitHub Action: async Python fetches and dedupes the week's sources, embeddings land in Postgres via pgvector for clustering, and Claude drafts each section with citations back to source. I read every line before it ships — the agent proposes, I decide.

Model spend$0.61 / issue
Pipeline runtime14 min
My time20 min
Time replaced~5 hrs/wk
Send windowMon 10:00 PT
One real run

Issue N° 15

July 23, 2026 · 15 stories

The CRE Finance & Tech Brief
Issue N° 15 · July 23, 2026
§ 01 Frontier AI

Record capex turns Alphabet's free cash flow negative for the first time

§ 02 Builder's toolkit

Cursor Router turns model choice into a policy: 60% cheaper at frontier quality

§ 03 Proptech & CRE

CBRE says US data-center pipeline doubled YoY to 8.8 GW