The Banished Bottom of the Housing Market

📝 Discussion Summary (Click to expand)

The discussion revolves heavily around the disappearance of low-cost, shared-living housing options like Single Room Occupancy (SRO) buildings and boarding houses, and the complex factors contributing to this decline.

Here are the three most prevalent themes:

1. Decline and Difficulty in Sustaining Low-Cost Communal Housing (SROs)

A core theme is the lament over the loss of extremely cheap historical housing models and the difficulty landlords face in operating them today, often due to regulatory environments.

Supporting Quote: A user mourned the loss of these affordable housing types, stating, "That is the sad thing, in the City I grew up in, we had a few large 'one room' rental buildings were people shared a bathroom that were rather cheap. But those started disappearing in the late 90s. Now, none are left :(" ("jmclnx").
Supporting Quote: Another user highlighted the operational challenge posed by modern tenant protections: "These kinds of housing are not compatible with current tenant laws. In order to cover this zone of the market you need the ability to boot bad actors. If you can’t do that, you get massive adverse selection..." ("renewiltord").

2. The Role of Regulation and Zoning in Housing Scarcity

Many participants pointed to local zoning, modern building codes, and expansive tenant rights laws as primary culprits, arguing these regulations inadvertently (or intentionally) make building and maintaining low-cost density financially unviable or illegal.

Supporting Quote: One user directly blamed zoning politics, stating, "This is why zoning should never have been made a local question. People who want to live in the area but can't because it is unaffordable don't get a vote, and the exclusionary communities become self-reinforcing." ("roguecoder").
Supporting Quote: Another summarized this regulatory effect: "The market solved the problem, regulations killed the solution and now we have a bigger and worse problem." ("brightball").

3. Trade-offs Between Low-Cost Housing and Social Issues (Mental Health/Substance Abuse)

There is significant debate regarding whether modern social problems, such as increased drug use and mental illness, make the historical SRO model fundamentally unworkable today, even if housing were available.

Supporting Quote: Concerns were raised about managing communal spaces with volatile populations: "I can’t imagine what it would look like today with a communal kitchen shared by strangers paying $231 inflation-adjusted dollars per month to be there." ("jancsika").
Supporting Quote: Conversely, others argue that the alternative—street homelessness—is worse, and that SROs offer a necessary first step: "If the options are 'people have conflict over who cleans the kitchen' and 'rampant street misery' the decision is obvious, at least to me." ("hamdingers").

🚀 Project Ideas

Regulatory Audit Tool for Low-Cost, High-Occupancy Housing (SRO/HMO)

Summary

A software tool designed to scan local zoning codes, building codes, and tenant law documentation for inconsistencies or overly restrictive requirements that prevent the creation or operation of low-cost, high-occupancy housing models (like SROs or shared living arrangements).
Core value proposition: Providing clarity and compliance pathways for innovative, low-cost housing models currently suppressed by regulatory complexity and conflicting mandates.

Details

Key	Value
Target Audience	Real estate developers focused on missing middle housing, non-profit housing advocates, municipal housing departments seeking reform.
Core Feature	NLP/ML-driven scanning of indexed municipal archives to generate a "Compliance Conflict Report" highlighting specific code sections (e.g., minimum unit size combined with mandatory private bath requirements) that conflict with high-occupancy models.
Tech Stack	Python (Scrapy for scraping/indexing, spaCy/Transformers for NLP code analysis), PostgreSQL, Web interface (React/Next.js).
Difficulty	High (Requires robust legal document parsing, indexing historical code changes, and maintaining comprehensive jurisdiction coverage).
Monetization	Hobby

Notes

Solves the core tension raised by users like renewiltord and Aurornis regarding modern tenant laws and building codes making SROs infeasible: "These kinds of housing are not compatible with current tenant laws. In order to cover this zone of the market you need the ability to boot bad actors." and "It doesn't take much thought to come to the conclusion that this approach will never fully alleviate basic housing concerns."
Users like epicureanideal specifically asked for clarification on legality: "So we may need to explicitly make these legal again so Americans will rent in this way." This tool provides the necessary groundwork for that legalization effort.

Landlord Risk Mitigation & Eviction Simulation Service (LMS)

Summary

A specialized SaaS service that models the financial and temporal risk associated with evicting tenants in high-turnover or shared-occupancy properties under current local jurisdiction laws.
Core value proposition: Quantifying the operational risk of strict tenant protections, allowing property managers (especially of SROs or shared homes) to assess viability and set fair, but sustainable, rent prices.

Details

Key	Value
Target Audience	Small to mid-sized landlords, operators of shared housing/SROs, legal firms specializing in tenant/landlord disputes.
Core Feature	"Eviction Time/Cost Calculator": Input jurisdiction and breach type (non-payment, nuisance, contract violation), and the system outputs a simulated timeline (days to serve, mandated waiting periods) and estimated legal cost range, referencing specific statute citations (`Aurornis` cited this as a major barrier).
Tech Stack	Go or Node.js backend for fast calculation engine, REST API, Dockerized deployment, comprehensive, region-specific legal database (initially focused on states with the most cited friction).
Difficulty	Medium (Requires meticulous, jurisdiction-specific research validation, but the simulation logic itself is process-driven).
Monetization	Hobby

Notes

Directly addresses the major constraint pointed out by Aurornis and encoderer: "If it takes you 6 months to evict a sociopath... Tenant rights is a huge one." This allows operators to price in the risk of "bad actors" (Negitivefrags's social contract enforcement issue).
It helps landlords (stackskipton, steveBK123) whose risk aversion, when amplified by complex laws, causes them to only accept the highest-income, lowest-risk tenants, thereby excluding the lower end of the market.

Decentralized High-Density Housing Viability Mapping (DHD-Mapper)

Summary

A public data visualization service that overlays proposed new housing projects (e.g., apartment complexes) with historical data on job centers, infrastructure capacity (mapped via public GIS data), and existing low-cost housing concentration.
Core value proposition: Combating NIMBYism and poor urban planning by providing developers and city planners with objective data showing where dense housing creates logistical efficiencies versus points where it strains existing systems, connecting housing to transit/jobs (as suggested by AnimalMuppet).

Details

Key	Value
Target Audience	Urban planners, municipal zoning boards, real estate investors analyzing market gaps, and policy advocates countering NIMBY arguments.
Core Feature	Multi-layered map view comparing proposed unit density against commuting distance to major employment hubs and historical infrastructure spending, flagging areas where low-income housing supply is desperately low relative to workforce needs.
Tech Stack	Python/R for data processing, JavaScript (Mapbox/Leaflet) for visualization, leverages publicly available Census/ACS data layers.
Difficulty	Medium (Data acquisition and harmonization across different municipal formats is the primary challenge).
Monetization	Hobby

Notes

Directly addresses the concern about job relocation and urban sprawl (AnimalMuppet, cyberax): "Creating SRO housing near the locations where the low-wage jobs are now."
It provides a data-driven response to the argument that dense housing increases costs and pollution by quantifying density benefits relative to services, pushing back against the sprawl advocates (array_key_first vs. cyberax). If density is more efficient for sanitation and infrastructure maintenance, this tool visualizes that efficiency gain.