AI Agents Are the Future.
AI Agents are the next evolution in human-computer interaction and can be customized to individual workflows. So, I decided to build my own AI agent with the help of Futurepedia, a YouTube channel built to teach others to leverage AI tools. First, let’s talk about a recent history of AI.
AI Example #1: Alexa by Amazon.
It handles simple tasks like:
“Hey Alexa, what is the weather?”
“The weather in New York City is 61 degrees, partially cloudy.”
“Thank you!”, you make sure to say; just in case Alexa and friends are your boss in 3-5 years.
AI Example #2: ChatGPT. One kind of LLM (Large Language Model).
Like Alexa in many ways. ChatGPT helps with more complex tasks. For example, let’s say we create a meal plan with recipes and shopping lists every Sunday. This takes about an hour. ChatGPT can create this for you in seconds and provides a downloadable version. This saves you time and aggravation. ChatGPT is like Google; many use it now in lieu of Google. Google has its time and place, but ChatGPT is carving its own path. Great for brainstorming and planning.
For instance, when you want to investigate a subject in Google, you may type: “History of Medieval Architecture in the 16th Century”. You’d be presented several pages of links to articles. Reading through even a few would take an hour. Instead, you can use ChatGPT. It will summarize these articles, condensing an hour of research into minutes by aggregating and distilling the key ideas. Then, ask GPT follow up questions and don’t forget to verify information. LLMs make mistakes and have bias. Trusting LLMs is like trusting Wikipedia at face value. Proceed cautiously.
Historically, there was Google. Then, Alexa. Recently, ChatGPT. And now the AI agent (possibly the next big thing). All have their specific strengths, and I am taking liberties in comparing these technologies under the umbrella of AI. AI is complex and diverse and each tool has a specific use case. For the sake of this article, I am drawing comparisons to introduce the topic of AI Agents.
What is an AI Agent?
In the last article, I defined AI as “The capability of computational systems (AKA computers) to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making.”
Simply, AI is the capability of a computer to perform tasks. So, what if we taught these computers to do specific tasks to help us with our day-to-day lives? In 1962, you had Mechano Maid 2000; then, in the 1999 DCOM Smart House you had Pat; now, in 2025 you have AI Agents.
Think back to the examples of Alexa and ChatGPT. What if you could combine those two technologies? The complex LLM thinking of ChatGPT with the personal assistant, Alexa. No longer do you need to ask Alexa the weather every morning. Alexa understands your life and makes it easier; freeing up two of your most valuable resources, time and energy. An AI Agent can send you an email every morning with “daily reports” that contain various pieces of info relevant to you like meetings for the day, top news stories, and if you should bring an umbrella. Like MorningBrew but customized to you. I’ve worked with RPA (Robotic Process Automation) in the past and see similarities in AI Agents and RPA. To me, AI Agents seem to be the next step in RPA. AI Agents seem to add complex reasoning to the RPA process.
This technology sounds exciting, so I wanted to build my own to learn more. FYI, if you are new to the subject and want to create your own, I’d recommend finding an AI YouTube channel that has a step-by-step hands-on tutorial. It is pretty simple. If you run into issues, use LLMs to create step by step instructions.
Building my AI Agent
So as I mentioned at the beginning of this article, I built my own AI agent with the help of Futurepedia, a YouTube channel built to teach others to leverage AI tools. The result, an AI Agent that told me the weather every morning. It looks at my Google Calendar to see if I have a trail run scheduled; jumps over to Google Sheets to look at trail data; lastly, sends me an email recommending the best trail based on conditions like Shade level or Elevation. Depending on temperature, a high elevation run may be too cold.
I used n8n for the development process. n8n is one of many AI workflow automation platform. Warning: I would recommend doing your own research on n8n because there are permissions you must give it to access certain APIs like Google Accounts. Always consider privacy online!
As far as development went it was super manageable. However, my technical experience did help a bit in development especially APIs and HTTP requests.
Building Tools used
At their base, AI Agents consist of three elements: Memory, Brain, and Tools. The brain makes decisions. The memory ensures it takes important info into account. The tools are what the brain uses to complete the task.
The technologies I used to satisfy these requirements are:
Brain: ChatGPT API
Memory: Temporary Memory in n8n
Tools:
- Google Calendar API
- Google Sheets API
- Google Mail API
- OpenWeather API
- HTTP Request
So, I completed this project and now have a computer handling this responsibility for me. No longer do I need to waste my time and energy. I can finally run without worrying about rain and goodbye to 30-minute research sessions at 5 a.m. to find the best trail.
This project is just the start. In the future, I want to securely incorporate AI into my data analytics workflow to provide instantaneous value. I will further brainstorm and research how AI can be used in sales and financial analysis workflows. Many articles have spoken about AI in sales; one of which, Salesforce, a leader in cloud-based sales applications.
AI in Sales
Salesforce published an article titled, “AI Sales Agents: A Complete Guide” written by Kris Billmaier, EVP & GM, Sales Cloud. It discusses how agents are helping sales teams scale fast.
“Recent data suggests that sales reps only spend 28% of their time actually selling, with the rest spent on administrative tasks and non-revenue-generating work. To alleviate the pressure and busywork, sales teams are turning to AI sales agents, which allows them to focus on actual selling,”Billmaier said.
Agents are freeing up sales reps’ time by automating their admin work and allowing them to focus on the people. These tools can perform repetitive sales tasks such as nurturing leads, scaling outreach, and even rep/partner onboarding; don’t forget quote creation, billing, and invoice management.
“AI sales agents work autonomously like human users in your existing sales CRM and tech stack. For customers, the experience is seamless – they’re aware they’re interacting with an AI agent but carry out conversations in natural language to supply information or schedule meetings,” Billmaier said.
Salesforce says these autonomous sales agents can be built using natural language from the developer. This means you shouldn’t a computer science background to build your own agent. However, I do see the programming background helping especially in understanding how to communicate with the application. The AI leaders will most likely be the ones with the technical and hands-on knowledge. One AI leader, Nvidia CEO Jensen Huang, said AI Agents will become a huge industry.
The Future: Healthcare, Jobs, and the Market
“On January 31, Nvidia CEO Jensen Huang unveiled the next generation of RTX Blackwell GPUs at CES 2025… He also declared the rise of ‘Agentic AI’ as the next major technological shift, predicting AI agents will drive a multi-trillion-dollar industry and transform how people work,” now, McAfee editor-in-chief Brooke Seipal said.
Obviously, there are many ethical concerns including job displacement, deep fakes, and giving tech companies access to our brain. These concerns should be taken seriously and not pushed aside in pursuit of profit or innovation. There are also many benefits to AI; we should understand the ethical and moral dangers of this powerful technology. This can be done many ways including public awareness, proper security, and governance.
“The keynote opened with a video demonstrating AI’s growing role in everyday life. From AI-powered safety features in cars to cartoon-style robots comforting children at doctor visits, the video painted a picture of AI agents becoming integrated into health care, mobility, and personal well-being. It also highlighted AI’s potential to ‘restore what we’ve lost,’ featuring people regaining speech and mobility through AI-driven technologies,” Seipal said.
The introduction of AI into healthcare has detected cancers and assisted disabled individuals to gain more independence. Transferring though thought to movement using brain chip implants. Empowering disabled individuals to perform normal daily tasks. All of the different implementations have contributed to the increase in media prevalence. AI seems to be gaining traction and people are noticing. One big beneficiary of this popularity are the companies in the AI industry. Stock prices have been going to the moon. This next section not investment advice and AI is very speculative. Some have compared this period in AI to the 2000s dot-com crash. If you want to invest, do your own research and at your own risk.
Wall Street Loves AI Too
The NVIDIA stock price has stagnated YTD, it has grown 1,421% from $9 to $135 over the past 5 years. Again, not a stock tip but to show immense recent growth in AI-centric companies.
Amazon uses AI in their business including Alexa, Amazon.com, and AWS. While Amazon has grown over the past 5 years, it is nowhere near the growth NVIDIA has seen in the same timeframe. NVIDIA is a producer of the GPUs needed for AI and their customers are Amazon. Amazon had breakout growth 10 years ago and is further down the supply chain than NVIDIA. As well as Amazon still recovering from the Covid Crash.
It will be interesting to watch the growth of tech companies with the increasing popularity of AI. There will most likely be new players arriving on the scene if AI is as revolutionary as people are saying.
In Conclusion
This was a really interesting project to take on and I learned some about AI agents. I’m excited to build out another AI agent and see how AI integrates into my workflow. I have been using ChatGPT for a while now and can see how it changes my workflow. Building my own agent helped me realize what’s possible when AI and GPTs are personalized and embedded in everyday life. The next step? Creating agents that directly support financial analysis, customer insights, and productivity.
The future of work may be agent-powered and I’m training to be ready.
By Jake Lender
Works Cited
Billmaier, K. (n.d.). Ai sales agents: Types, examples, & benefits. Salesforce. https://www.salesforce.com/sales/ai-sales-agent/guide/
IMDb.com. (1999, June 26). Smart house. IMDb. https://www.imdb.com/title/tt0192618/?ref_=mv_close
Seipal, B. (2025a, January 31). Nvidia’s Jensen Huang says AI agents are “a multi-trillion-dollar opportunity” and “the age of Ai Agentics is here.” Yahoo! Finance. https://finance.yahoo.com/news/nvidia-jensen-huang-says-ai-044815659.html
Yahoo! (2025, May 30). Amazon.com, inc. (AMZN) stock price, news, Quote & History. Yahoo! Finance. https://finance.yahoo.com/quote/AMZN/
Yahoo! (2025b, May 30). Nvidia Corporation (NVDA) stock price, news, Quote & History. Yahoo! Finance. https://finance.yahoo.com/quote/NVDA/
Wiki, C. to T. J. (n.d.). Mechano Maid 2000. The Jetsons Wiki. https://thejetsons.fandom.com/wiki/Mechano_Maid_2000
