Category: AI Tools

AI Tools, Artificial Intelligence, Banking, Blockchains, Digital Currency, real estate, tokenization, Uncategorized, Yogi Nelson

🏢 A Step-by-Step Guide to Tokenized Commercial Real Estate

Yogi Nelson

Welcome to the BlockchainAIForum where your technology questions are answered. Commercial real estate has always been seen as a solid investment, but it often feels out of reach for the average person. High costs, complex deals, and limited access keep many investors on the sidelines. Tokenization is changing that. By turning ownership stakes into digital tokens on a blockchain, it is opening commercial real estate to a wider group of investors. But what does that actually mean? Let’s break it down step by step.

💡 What Is Tokenized Commercial Real Estate?

In simple terms, tokenized commercial real estate is when ownership in a property—like an office building, shopping center, or apartment complex—is divided into digital “tokens” recorded on a blockchain. Each token represents a share of ownership. This allows people to buy, sell, and trade fractional pieces of expensive real estate much more easily than before.

Imagine splitting a $10 million building into 10,000 tokens. Instead of needing millions to invest, you could buy a single token for $1,000. It’s like owning a slice of the property.

🌍 Why Do People Care About It?

Tokenization is seen as an important innovation for several reasons:

  • Accessibility: More people can invest in high-value commercial properties.
  • Liquidity: Tokens can potentially be traded on secondary markets, making it easier to sell.
  • Transparency: Blockchain records transactions securely and publicly.
  • Efficiency: Smart contracts can automate processes, reducing paperwork and costs.

In short, tokenization promises to make commercial real estate investment more democratic and streamlined.

🛠️ How Does Tokenized Commercial Real Estate Work? Step by Step

Let’s walk through a typical process for tokenizing a commercial property.

1️⃣ Identify and Value the Property

First, a property owner or real estate company decides which property they want to tokenize. They conduct a professional valuation to determine its market worth. For example, suppose they pick a shopping center valued at $10 million.

2️⃣ Structure the Ownership

Next, they set up the legal structure. This is crucial. Usually, the property is placed in a legal entity, such as a limited liability company (LLC) or a trust. Investors don’t directly own the building but own shares in the entity that owns it. This makes it possible to divide ownership cleanly into tokens.

3️⃣ Create the Tokens

Once the legal groundwork is in place, the ownership is split into digital tokens on a blockchain. If the shopping center is split into 10,000 tokens, each token represents 0.01% of the total ownership.

This step requires working with a blockchain platform that supports token creation. The tokens are coded with rules about how they can be traded and who can hold them, ensuring compliance with regulations.

4️⃣ Offer the Tokens to Investors

The next step is to sell the tokens. This might happen through a direct sale on the issuer’s website or through a digital platform specializing in real estate tokens. Investors buy tokens using traditional currency or sometimes cryptocurrency.

In many jurisdictions, these offerings must comply with securities laws, so they may be limited to accredited investors or follow specific regulations.

5️⃣ Manage the Property and Distribute Income

After the sale, the property is managed like any other commercial investment. Rent is collected, expenses are paid, and profits are distributed. Income—such as rental profits—can be divided among token holders proportionally.

Thanks to blockchain technology, these payments can even be automated via smart contracts, which execute payments once certain conditions are met.

6️⃣ Trade or Sell the Tokens

One of the most appealing aspects of tokenization is the potential for liquidity. Instead of holding a property for 5–10 years before selling, investors might trade tokens on approved secondary markets. This gives them flexibility to exit earlier if needed.

🚀 Why Is This Considered Important?

Tokenized commercial real estate isn’t just a new technology gimmick. It could transform the industry by:

  • Lowering barriers to entry for smaller investors.
  • Enabling global participation in local real estate markets.
  • Making real estate investments more flexible and tradable.
  • Reducing reliance on expensive intermediaries.

While it is still early days, and there are regulatory and technical challenges to solve, many see tokenization as a way to modernize a traditionally slow, opaque, and exclusive industry.

✅ Final Thoughts

Tokenized commercial real estate aims to make property investment more accessible, transparent, and efficient. By turning buildings into tradable digital tokens, it offers a new way for people to invest in—and benefit from—the commercial real estate market. As technology and regulations evolve, it could reshape how we think about owning and investing in property for years to come. It is a fantastic innovation!

Until next time,

Yogi Nelson

AI Agents, AI Tools, Artificial Intelligence, Banking, Blockchains, cryptography, Decentralized, Digital Currency, international aid, International Finance, Productivity, Science, Uncategorized, Yogi Nelson

The Advantages of Stablecoins for Sending Remittances and International Payments

Yogi Nelson

🌍💸

By Yogi Nelson

Welcome to the BlockchainAIForum where your technology questions are answered. Today we answer the following question: What are the advantages of stablecoins to transmit remittances and international payments?

Sending money across borders has long been expensive, slow, and sometimes unreliable. Millions of families around the world rely on remittances—money sent home by people working abroad. Traditional methods often take days to arrive and cost a big chunk of the amount sent in fees.

Enter stablecoins: a type of cryptocurrency designed to hold a steady value, usually pegged to a traditional currency like the U.S. dollar. While “crypto” might sound complicated or risky, stablecoins have clear advantages for cross-border payments—especially for everyday people who just want to get money to loved ones quickly and cheaply. Below, let’s explore what makes stablecoins such a game-changer for international payments.

🕰️ 1️⃣ Faster Transfers

Traditional money transfers often rely on banks and money transfer operators. These institutions use old payment networks that involve multiple middlemen. It can take 2–5 business days for the money to arrive. I can speak from personal experience–too slow in today’s world.

✅ With stablecoins:

  • Transfers are nearly instant or settle in minutes.
  • Blockchain networks operate 24/7, including weekends and holidays.

Example: Sending USDC (a popular U.S. dollar-pegged stablecoin) from the U.S. to someone in Panama can take under 10 minutes, compared to days via bank wires.

💰 2️⃣ Lower Fees

Sending money internationally is notoriously expensive. According to the World Bank, the average remittance fee is around 6% globally—and even higher in some regions. Banco Popular charged me $100 to send $5,000 to Panama. Way too expensive!

✅ Stablecoins reduce fees because:

  • No need for multiple banks to process the payment.
  • No foreign exchange markup if both sender and receiver use the same stablecoin (e.g., USDC, USDT).

Example:

  • $100 sent via Western Union might cost $6–10 in fees.
  • $100 sent as a stablecoin can cost under $1 in network fees, depending on the blockchain used.

🌐 3️⃣ Global Accessibility

Many people in developing countries do not have bank accounts. But they often have smartphones. Stablecoins can be sent, received, and stored on mobile wallets, without the need for a traditional bank.

✅ Key benefits:

  • Financial inclusion for the unbanked or underbanked.
  • Access to USD-equivalent value without needing a dollar bank account.

Example: A worker in the U.S. can send USDC to a family member in El Salvador who holds it in a smartphone wallet, without needing local bank infrastructure.

💵 4️⃣ Protection Against Local Currency Volatility

In some countries, local currencies lose value quickly due to inflation. Receiving money in local currency may mean losing purchasing power almost immediately.

✅ Stablecoins help by:

  • Being pegged to stable currencies like USD.
  • Preserving value across borders and over time.

Example: A family in Argentina might prefer to receive USDC instead of pesos, protecting their remittance from inflation.

🔐 5️⃣ Transparency and Security

Stablecoin transactions are recorded on blockchains, which are public, auditable ledgers. This adds an extra layer of security and transparency.

✅ Advantages:

  • Sender and receiver can track the transfer in real-time.
  • Less risk of funds being lost in transit.
  • Resistant to censorship and freezes compared to some traditional systems.

⚡️ How Does It Work in Practice?

Here’s a simplified step-by-step:

  1. Sender buys stablecoins on an exchange or app.
  2. Sender transfers stablecoins to the recipient’s wallet address.
  3. Recipient receives them instantly or in minutes.
  4. Recipient can hold them, spend them where accepted, or convert to local currency.

This simple flow cuts out middlemen and delays.

🌟 Conclusion: A Better Way to Send Money

Stablecoins are not just a trend. They offer real, practical benefits for millions who rely on international payments:

  • ✅ Faster delivery times.
  • ✅ Lower costs.
  • ✅ Greater accessibility.
  • ✅ Protection from inflation.
  • ✅ Transparent and secure transactions.

Of course, challenges remain, like educating users, ensuring good regulation, and making stablecoins easy to cash out locally. But as adoption grows, these hurdles are being addressed.

For many families, stablecoins are already changing the way money crosses borders, making remittances fairer and more efficient.

💬 My closing thought comes from Ethiopia where they say: “a fool is thirsty in the midst of water.” If you have thoughts or questions about stablecoins and remittances, drop them in the comments below!

Until Next time,

Yogi Nelson

AI Agents, AI Tools, Artificial Intelligence, Blockchains, Science, Uncategorized

Understanding Decentralized Science: A New Era for Research Funding

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered.  Is there an alternative to the existing science research funding model? The answer is yes–there is an alternative, it’s called Decentralized Science (DeSci) and the best example is called Unbound Science.  We begin with what is science research funding, who funds science, and conclude with a very brief mention of Unbound Science.  An exhaustive examination of Unbound Science will be presented in parts two-and-three of this three-part series over the course of the next three weeks.

What is science research funding? There is no precise definition of science research funding that is universally accepted.  However, using a general consensus definition, I think we can say science research funding:  

is the financial support provided to researchers and institutions to conduct studies, experiments, and investigations that push the boundaries of human knowledge. This crucial resource enables scientists to explore new ideas, develop cutting-edge technologies, and tackle some of the world’s most pressing challenges. It typically covers expenses such as personnel salaries, laboratory equipment, data collection, publication costs, and travel for conferences

Who Funds Science Research.  Please draw your attention to the critical phase in the definition, “… financial support provided…”.  The statement begs the question, “provided” by whom?  The answer to that question follows.

According to the National Science Foundation, science research funding by category and percentage of the total science budget is: 

  • Private Sector, i.e., Corporate Research and Development                           50%
  • Federal Government Agencies                                                                       35%
  • Academic institutions                                                                                     11%
  • Private foundations                                                                                            3%

Clearly the top three funding sources dominate the landscape.  If you add the four funding sources the sum equals 99%.  Where is the missing one percent?   You will find it in something called emerging decentralized science platforms.  What are decentralized platforms within a science research funding content?  I’ll explain that next and start by naming this phenomenon—it’s called decentralized science or DeSci.     

What is Decentralized Science (DeSci). DeSci is an emerging movement and technological framework that uses blockchain, cryptographic tools, and decentralized governance to improve how scientific research is funded, conducted, validated, shared, and rewarded. DeSci aims to address long-standing inefficiencies and inequalities in traditional science by enabling open, transparent, and community-governed research ecosystems.  DeSci operates in the web-3 ecosystem; thus, separating it from existing models.  Web-3 ecosystems are characterized by decentralized technologies, i.e., smart contracts, tokens, and governance via decentralized autonomous organizations (DAOs), not top-down hierarchies.  In DeSci, the emphasis is fund, govern, and distribute scientific research in a transparent, open-access, and community-driven manner. In other words, when operating as intended, DeSci is antithesis to the status quo and disrupts the big donor science research funding model. 

How Does DeSci Work.  Under ideal circumstances DeSci is characterized by the following six traits:

  1. Funding Research via Blockchain.  Scientists can raise funds directly from across the globe using crypto-currencies, NFTs, or project-specific tokens.
  2. Decentralized Governance.  Funding decisions can be made through DAOs and/or community members.
  3. Tokenized Incentives.  Contributors are rewarded with tokens for participation, publication, peer-review, data sharing, and many other activities.
  4. Open Access and Data Transparency.  Research outputs are stored on decentralized storage platforms, making the research permanently accessible.
  5. Reputation and Credentialing.  With DeSci verifiable credential, on-chain peer review, and reputation scores are all possible and that helps assess the credibility of researchers without relying solely on traditional academic gatekeepers.
  6. Interoperable and Modular.  Generally speaking, DeSci platforms are composable.  Composable platforms allow interoperability across funding tools, DAOs, publishing platforms, and decentralized identity systems.

What is Unbound Science.  Unbound Science is a prime example of a DeSci platform.  Unbound Science is designed to check every box on the checklist above when it reaches full maturity. Next week a deep dive into Unbound Science.

Until next time,

Yogi Nelson

AI Agents, AI Tools, Blockchains, cryptography, Uncategorized, Yogi Nelson

Building Effective AI Agents: A Complete Guide

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered.  Today’s question: are there practical tips for building an artificial intelligence (AI) agent?  Answer—yes.  Today I’ll explain, starting with what is an AI agent.

What is an AI Agent.  AI agents are poised to become ubiquitous.  Says who?  All the IT giants, e.g. Amazon, Microsoft, Google, etc., that’s who. Let’s start by defining AI agents.  According to IBM, AI agents:

a system or program that is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools.  AI agents can encompass a wide range of functionalities beyond natural language processing including decision-making, problem-solving, interacting with external environments and executing actions. AI agents can be deployed in various applications to solve complex tasks, including software design, IT automation, code-generation tools and conversational assistants. AI agents use advanced large language models (LLMs) to comprehend and respond to user inputs.

Knowing When to Build an AI Agent. Open AI, the company behind ChatGPT, says building AI agents requires rethinking how existing systems make decisions and handle complexity.  Therefore, if you find yourself dealing with the situation below, you have an ideal circumstance for introducing AI agents, says Open AI:

Click to access a-practical-guide-to-building-agents.pdf

  1. Complex Decision Making.    Workflows involving nuanced judgment, exceptions, or context-sensitive decisions, e.g. refund approval in customer service workflows.
  2. Difficult to Maintain Rules.  Systems that have become unwieldly due to extensive and intricate rule sets, making updates costly or error-prone, e.g. performing vendor security reviews.
  3. Heavy Reliance on Unstructured Data.  Scenarios that involve natural language, extracting meaning from documents, or interacting with users conversationally, e.g. processing a home insurance claim.

AI Agent Design Foundations.  Fundamentally, AI agents consists of three core components: 1) model; 2) tools; and 3) instructions.  Let’s briefly define each core component.  Model refers to the large language model powering the agent’s reasoning and decision making. Tools means the external functions or APIs the agent can use to take action.  And instructions are the explicit guidelines and guardrails defining how the agent behaves. Next we examine principles for selecting a model.

Principles for Choosing a Model.  Not all AI models are identical.  Models vary by capabilities.  And, of course, not every task requires the best model.  Ideally build your AI agent with the most capable model for the task, factoring in trade-offs related to task complexity, latency, and cost.  With those considerations in mind, use the following methodology:

  1. Set up evaluations to establish a performance baseline.
  2. Focus on meeting your accuracy target with the best model available.
  3. Optimize for cost and latency by replacing larger models with smaller ones where possible.  If you want an Open AI model, visit this link:  https://platform.openai.com/docs/guides/model-selection

What are AI Tools.  AI tools extend the capabilities of AI agents by using APIs from underlying applications or systems.  Tools should have a standardized definition, enabling flexible, many-to-many relationships between tools and agents.  AI agents need three types of tools:

  1. Data.  Data enables AI agents to retrieve context and information necessary for executing workflow.
  2. Action.  Action tools enable agents to interact with systems to take actions, i.e., adding new information, updating records, or sending messages.
  3. Orchestration.  This is where it gets a bit science fiction.  Orchestration allows AI agents themselves to serve as tools for one or more AI agents!  When to use multiple agents?  When the single agent model fails to follow complicated instructions or consistently selects incorrect tools.

Best Practices for AI Agent Instructions.  Without high quality instructions, your AI agent will be suboptimal.  Below are a few suggestions for creating high quality instructions:

  1. Use existing documents. 
  2. Prompt the AI Agent to break down the tasks into smaller more manageable steps.
  3. Define clear actions.  In other words, make sure every step corresponds to a specific action.
  4. Capture edge cases.  Not everything fits in a box and sometimes information is missing.  Hence, instructions should anticipate common variations and include instructions on how to handle the non-routine with conditional steps.

Guardrails.  What are guardrails?  Essentially, guardrails are layered defense mechanism.  When properly designed, guardrails help manage risk.  Consider three factors when constructing guardrails:  1) privacy and safety; 2) add new guardrails based on real world experience; 3) optimize the balance between security and user experience.  With that in mind below are possible AI agent guardrails:

  1. Relevance Classifier.  This ensures the AI Agent stays within the intended scope by flagging off-topic queries.
  2. Safety Classifier.  These detect unsafe inputs that attempt to exploit system vulnerabilities.
  3. PII Filter.  PLL filters prevent unnecessary exposure of personally identifiable information.
  4. Moderation.  Moderation guardrails flag harmful or inappropriate inputs.
  5. Tool Safeguards.  With tools safeguard you can assess the risk of each tool available to the AI Agent.
  6. Rules-Based Protections.  The idea behind rules-based protection is to use simple deterministic measures to prevent known threats.  
  7. Output Validation.  Ensure responses align with brand values via prompt engineering and content checks.

Until next time,

Yogi Nelson and his AI Agent