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1049 Why Dustin Uses Manus As His AI Agent

There are many choices when it comes to artificial intelligence agents (different than LLMs). Dustin chooses Manus and here is why and some of the powerful things you can do with it.

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Growing beyond a one-person appraisal office into a thriving enterprise can feel out of reach, but the path is more practical than it seems. The key is learning how to take the systems, habits, and tools that work for a solo office and replicate them across people and processes. Drawing from his experience running both a small office and a multi-million dollar appraisal company, Dustin breaks down the principles, strategies, and actionable steps you can use to scale with confidence and build long-term success.

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Here are 5 short, usable summaries (with links) of 2025 articles and reports about AI agents and LLMs that are directly relevant to real-estate appraisers. Each summary includes a quick “why it matters for appraisers” line

• “On the Performance of LLMs for Real Estate Appraisal” — arXiv (research paper, Jun 13, 2025)
  Summary: This technical study benchmarks leading large language models on house-price estimation tasks using zero-shot, few-shot, and hybrid prompting strategies. The authors show LLMs can produce competitive, interpretable estimates when given structured local market context and example cases, but performance varies by model and data quality. They highlight how careful prompt design and combining LLM output with numeric AVMs reduces large, systematic errors.
  Why it matters: shows LLMs can assist appraisers with initial valuation drafts, explanation text, and scenario testing — but human oversight and good local data remain essential. arXiv

• “The AI inflection point — Charting a new course for CRE valuations” — Altus Group (industry insight, Jun 11, 2025)
  Summary: Altus Group describes agentic AI and GenAI workflows that accelerate commercial appraisal tasks (data collection, comparable selection, sensitivity analyses) and improve consistency across valuations. The piece explains integration patterns (APIs to MLS/registry data, automation of repetitive checks) and governance needs (audit trails, model-explainability). It also offers use-case examples where AI agents reduced turnaround time while freeing appraisers for exceptions and judgment calls.
  Why it matters: practical roadmap for integrating agentic tools into appraisal workflows while preserving auditability and professional judgment. Altus Group

• “The state of AI: How organizations are rewiring to capture value” — McKinsey (2025 report, PDF)
  Summary: McKinsey’s 2025 survey/report describes enterprise GenAI adoption patterns and governance best practices across professional services. Key takeaways: firms that centralize governance, invest in prompt engineering and data pipelines, and pair AI with domain experts realize larger productivity gains. The report stresses rigid verification steps for outputs used in regulated contexts (like valuations).
  Why it matters: offers governance and implementation lessons appraisers and appraisal firms can copy to safely deploy LLM agents (version control, human-in-loop checks, standardized prompts). McKinsey & Company

• “The Future of AI in Real Estate Valuations: Understanding tomorrow’s appraisal standards” — AppraisalBuzz (industry article, Jul 28, 2025)
  Summary: AppraisalBuzz discusses AI tools tailored for appraisal workflows — from AVM enhancement to customizable checklists that learn lender preferences. The article highlights early vendor features that let firms teach agents specific institutional standards and automatically flag deviations, plus examples of AI-generated narrative sections for reports. It also covers regulatory and ethical considerations for disclosure and explainability.
  Why it matters: concrete vendor-level features appraisers can trial now (custom checklists, auto-narratives), and practical advice on preserving compliance. Appraisal Buzz

• “The 2025 AI Index Report” — Stanford HAI (AI overview, 2025)
  Summary: Stanford HAI’s 2025 AI Index provides a high-level snapshot of rapid GenAI investment and adoption across industries, and documents technical advances in LLMs and agentic systems. It includes statistics on enterprise uptake, investment trends, and the growing ecosystem of specialized agents and tooling. The report frames expected industry impacts (speed, new capabilities, need for governance).
  Why it matters: useful context to understand the pace of innovation and why appraisal firms should prioritize pilot projects and vendor evaluations now. Stanford HAI