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CITY AS A LAB · BALTIMORE

Foundation Labs

Baltimore city-as-lab plan — rebuild homes into Success Hubs

Modeled on Urban Systems, Ph.D. — NYU Tandon and the CUSP Urban Science track: field-test urban infrastructure, data, and AI in real neighborhoods. Agents runs the business layer; Labs holds the research and grant narrative.

Why this plan

Baltimore’s vacant housing and capacity gap

15,000+

Vacant properties across Baltimore City

30%

Of homes in some neighborhoods sit empty

Ashburton PoC

617 Ashburton — rehab + apprenticeship proof

Agents OS

Business CRM and AI workers for hub tenants

Intervention stack

Acquire → Rehab → Hub → Agents → Publish

01

Acquire

Partner with Baltimore City pathways (including vacant / $1-class acquisition) to stabilize strategic blocks.

02

Rehab

Full-scope renovation to code with paid apprenticeships under licensed construction partners.

03

Success Hub

Each restored property becomes a launch point — housing plus a neighborhood node for skills, services, and local enterprise. Larger sites can take the destination-hub form (ticket #293, proposed): Third Place / EV dwell with local food hall and retail collective, indexed on the Labs Place graph.

04

AI worker injection

Agents Property Lab plus Agentic OS supplies CRM, outreach, tickets, and AI business workers so hub operators run modern ops for real people — not a demo CRM on Foundation.

05

Measure & publish

Field evidence flows into the Labs field track (journal workspace + Lab Desk). Grant narratives for city leadership and funders are built in Labs; RFP facts and amounts come from the Let’s Talk PR (LTP) shared Drive grant ledger — never invented.

Research comparable

NYU Urban Systems + CUSP — city as a lab

NYU Tandon’s Urban Systems Ph.D. uses the city as a laboratory to develop and field-test solutions for urban infrastructure, community needs, resilience, data, AI, and public systems. It includes a Community Impact Project and coursework in urban infrastructure, monitoring cities, applied data science, AI, machine learning, and system optimization. The CUSP Urban Science doctoral track deepens complexity, informatics, and sensing methods for that same field orientation.

City as a lab — solutions designed and tested in real neighborhoods, not only in simulation

Community Impact Project — scholarship tied to measurable local outcomes

Urban infrastructure, monitoring, applied data science, AI / ML, and system optimization

CUSP specialization — complexity, informatics, and sensing for urban systems

Baltimore adaptation

Homes as field instruments

Blocks of vacant and underused properties drain neighborhood wealth and youth opportunity. Public acquisition pathways (including city vacant programs) exist, but rehab alone does not restore economic capacity. Homes need a second job: become launch points for community Success Hubs and modern business tooling.

Acquire: Partner with Baltimore City pathways (including vacant / $1-class acquisition) to stabilize strategic blocks.

Rehab: Full-scope renovation to code with paid apprenticeships under licensed construction partners.

Success Hub: Each restored property becomes a launch point — housing plus a neighborhood node for skills, services, and local enterprise. Larger sites can take the destination-hub form (ticket #293, proposed): Third Place / EV dwell with local food hall and retail collective, indexed on the Labs Place graph.

AI worker injection: Agents Property Lab plus Agentic OS supplies CRM, outreach, tickets, and AI business workers so hub operators run modern ops for real people — not a demo CRM on Foundation.

Measure & publish: Field evidence flows into the Labs field track (journal workspace + Lab Desk). Grant narratives for city leadership and funders are built in Labs; RFP facts and amounts come from the Let’s Talk PR (LTP) shared Drive grant ledger — never invented.

Success Hubs

Launch points for enterprise and learning

Restored homes are not endpoints. They host Success Hubs — neighborhood nodes where trades pathways, local enterprise, and community services meet. The destination form (ticket #293, proposed — not a completed building) is a Third Place / EV Mobility Hub: dwell time (20–45 minutes at the charger) subsidizes a lounge, a food hall of local operators instead of legacy QSR chains, and a retail collective of independent shops. R. House is a Baltimore size comparable. The Agentic OS on Agents is the business layer operators actually use. Labs indexes the hub as a Place (spatial zones, dwell windows, consented community→Place edges) — fandom belonging that currently lives online becomes geographic when people opt a community into the site.

Housing stability + neighborhood presence

Skills and apprenticeship continuity on-site

Local enterprise tooling via Agents (CRM, outreach, AI workers)

Destination hub dwell: lounge + local food hall + retail collective (proposed)

Field evidence captured for Labs R1 research — Place graph, not person surveillance

Research ↔ funding

Agents informs research · Labs builds the ask

Ops and CRM data from Agents show what growth looks like on the ground. Labs field track turns that into publishable research and city-facing grant narratives. Award amounts and RFP packages stay on the LTP shared Drive grant ledger.

Agents → growth and capacity signals

Labs field workspace → R1 research ledger

Foundation proposal → narrative for city leadership and funders

LTP Drive ledger → authoritative RFPs and amounts

Grant proposal output

Narrative for city leadership and funders. Budget amounts come from the Let’s Talk PR (LTP) shared Drive grant ledger — synced in Lab Desk — not invented here.

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Baltimore, Maryland

Rebuilding Baltimore. Training Leaders. Creating Opportunity.

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Baltimore, Maryland

[email protected]

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501(c)(3) Non-Profit Organization · Baltimore, MD