u/OrganicRaisin7352

Estoy desarrollando una herramienta para administración de alquileres y quiero entender mejor cómo lo manejan hoy quienes tienen varias propiedades.

Me interesa algo bien concreto: ¿qué información se les desordena primero? ¿Los pagos y comprobantes, los ajustes, las reparaciones o alguna otra cosa?

También me sirve saber si lo resuelven con una planilla, carpetas, WhatsApp o un sistema, y qué parte sigue siendo manual aunque tengan todo organizado.

Buenas. Estoy desarrollando Renteric, un SaaS para administración de alquileres de largo plazo en Argentina.

Apunta a inmobiliarias, administradores y propietarios con cartera. La idea es reemplazar el manejo disperso de Excel, WhatsApp, comprobantes y recordatorios por una plataforma donde se puedan llevar contratos, pagos, ajustes, punitorios, gastos, reparaciones, vencimientos y portales para propietario/inquilino.

El producto ya está bastante avanzado, pero el gran desafío ahora es distribución: cómo llegar a inmobiliarias y propietarios que hoy ya tienen un sistema informal armado, aunque sea incómodo.

Me interesa escuchar opiniones de gente con experiencia comercial, real estate, SaaS o ventas B2B.

Mis dudas principales:

• ¿Irían primero por inmobiliarias o propietarios?
• ¿Conviene vender por demo directa, referidos, LinkedIn, colegios inmobiliarios o partners comerciales?
• ¿Qué pricing tendría sentido para Argentina?
• ¿Qué objeciones creen que aparecerían primero?

Si quieren el sitio me lo piden por privado ya que por reglas no se puede.

Cualquier crítica sincera sirve.

I think Anthropic — and other major AI companies — need to treat ban policies much more carefully. AI tools are no longer just “apps.” For many developers, students, writers, researchers, founders, and professionals, they are becoming part of the basic work infrastructure.

That means losing access is not a minor inconvenience. It can affect someone’s ability to work, learn, build, and compete.

To be clear, platforms absolutely need to enforce their terms, stop abuse, prevent fraud, and protect users. Serious misuse should have serious consequences.

But a lifetime ban should be a last resort. It should be reserved for clear cases of repeated, intentional, and serious abuse — not for ambiguous prompts, accidental violations, misunderstood research, or automated systems making a bad judgment call.

A better approach would be graduated enforcement:

1. A clear warning explaining what rule was violated.
2. A temporary suspension if the behavior continues.
3. Longer suspensions or feature restrictions for repeated issues.
4. A permanent ban only after serious review or severe abuse.

This would help users learn the rules instead of suddenly losing access with little explanation. Most users are not trying to abuse the platform; they want to understand the boundaries and use the tool correctly.

Trust in AI platforms is not only about model quality. It is also about account stability, fair enforcement, clear rules, and meaningful appeals. If users fear that one misunderstood request could permanently lock them out, they will hesitate to build serious workflows around the product.

At minimum, permanent bans should involve human review, clear notice, proportional consequences, a real appeal process, and some way to export user data when possible.

This is not about weakening safety. It is about making safety enforcement more mature.

As AI becomes essential infrastructure, companies like Anthropic will have more power over people’s professional capabilities. That power needs transparency, proportionality, and accountability.

A permanent ban should be the final step after clear evidence and serious review — not the first time a user truly understands they crossed a line.