Insights

Research, analysis, and perspectives on the built world.

Technology

Real Estate Development Management Software: What It Does and Why AI-Native Delivery Beats the Legacy Stack

Real estate development management software spans project controls, deal management, construction platforms, and ERPs -- none of which covers the full lifecycle well. This piece explains what the category is built to do, where legacy tools break down for institutional developers, and why AI-native delivery is replacing the software layer for lean, high-volume teams.

April 26, 2026 ·4 min read

Workflows

Construction Lien Waivers: Types, Requirements, and How AI Tracks Them

Construction lien waivers come in four types -- conditional and unconditional, on progress and final payment -- and missing or mismanaged waivers are one of the most common sources of owner exposure at project closeout. This guide explains how tracking breaks down, what AI automates across document extraction, payment matching, and gap detection, and where human judgment is still required.

April 26, 2026 ·4 min read

Workflows

Automation in Real Estate: What's Actually Being Deployed and Where It Saves the Most Time

AI automation is now deployable across almost every stage of the real estate development lifecycle. This piece maps where automation is live today -- from site screening and due diligence to pro forma modeling and IC prep -- and how development teams should sequence deployment to maximize ROI.

April 25, 2026 ·4 min read

Technology

AI Agents for Real Estate: What They Are, What They Can Do, and Who Is Actually Using Them

AI agents differ from chatbots and copilots in one critical way: they execute multi-step workflows using tools, memory, and planning. This piece explains how agents work, where institutional development teams are deploying them in 2026 -- site sourcing, due diligence, market analysis, IC prep -- and what to evaluate before selecting one.

April 25, 2026 ·4 min read

Workflows

Document Automation in Real Estate Development: What AI Handles and What Still Needs a Lawyer

Real estate development generates hundreds of documents per project. AI automation reliably handles due diligence extraction, lease abstraction, draw package assembly, and IC memo drafting -- but PSAs, development agreements, and complex construction contracts still require legal review. This piece maps the boundary.

April 25, 2026 ·4 min read

Industry

Sovereign Wealth Funds Are Betting on Digital Infrastructure. Here Is What That Means for Developers.

Sovereign wealth funds including GIC, ADIA, Mubadala and PIF have rotated aggressively into digital infrastructure real estate, concentrating capital in data centers, fiber networks and energy assets. This piece covers which funds are leading the allocation, why the shift is structural rather than cyclical, and three practical implications for development teams navigating a market where sovereign-backed platforms are setting the pace.

April 24, 2026 ·4 min read

Asset Classes

Self-Storage Development in 2026: What the Site Criteria Actually Look Like

Self-storage has become a core institutional asset class, and the 2022-2024 supply wave is clearing in most markets. This piece covers the demand model, product type breakdown, site screening criteria and pro forma framework institutional developers use to evaluate new development, plus where AI compresses site screening and underwriting time.

April 24, 2026 ·5 min read

Workflows

Cost-to-Complete Analysis with AI: Forecasting Construction Costs Before the Budget Burns

The cost-to-complete analysis is the monthly document that tells lenders and development teams how much money is left to finish a building. This piece covers the three failure modes that make CTCs unreliable, how AI addresses each one through front-loading detection, pending change order aggregation and line-level burn rate alerts, and what still requires human judgment.

April 24, 2026 ·4 min read

Technology

Foundation Model Selection for CRE Development Workflows: A Practical Evaluation Guide

Foundation model selection has a direct impact on CRE workflow accuracy, cost and analytical depth. This guide maps GPT-4o, Claude, Gemini and o-series models to specific development tasks and provides an evaluation framework covering context window, tool use reliability, structured output fidelity and cost at scale. Teams routing by task type rather than defaulting to a single model cut inference cost 40-60% while improving accuracy on high-stakes outputs.

April 23, 2026 ·4 min read