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3 Lessons Learned From Building Our First AI Agent
ai-agents

3 Lessons Learned From Building Our First AI Agent

Discover three essential lessons from building an AI agent that improves customer service and business efficiency.

August 8, 2025
5 min read
Aytekin Tank

3 Lessons Learned From Building Our First AI Agent

Having led a business for nearly 20 years, I’ve overseen many product launches—and still learn something from every single one. Recently, my company, Jotform, ventured into entirely new territory with the release of our first AI agents. Our journey into agentic AI began in 2023, well before "AI agent" became a common term. The last few months have been filled with hype—from grand promises about AI agents’ disruptive potential to fears about their impact. Regardless of the discourse, AI agents are reshaping how business is done. Here are three lessons we learned from creating ours.

Listen To Data, Not Hype

Like any product, your original idea may transform significantly by launch. When Jotform first explored AI integrations, generative AI was the hot topic. During one of our regular hack weeks, our team developed an idea: AI-powered forms users could generate and customize by interacting directly with the form. We launched a beta version and gathered real-world feedback. It was a hit—users engaged with the product and retention was strong. But data revealed an unexpected insight: 90% of users weren’t using the tool for forms; they used it for customer service. This was not our initial vision, but the data was clear. We pivoted to support this use case. The lesson? Success depends on your ability to listen to customers and adapt, even if it means changing your original plan. The data never lies.

Efficiency Over Friendliness

AI companions have sparked concerns about replacing human relationships. This might lead leaders to think their agents need charming personalities to succeed. However, users care more about efficiency than personality. Historically, customers preferred humans over chatbots due to frustration with the latter. Our testing showed users actually prefer agents—not just for faster responses and 24/7 availability, but because agents remove social pressure. Users don’t worry about asking “dumb” questions or repeating themselves. Without the need to be pleasant, they get the help they need. Research from Salesforce supports this: overly human-like AI agents can disappoint users and erode trust if expectations aren’t met. Yvonne Gando, Salesforce’s senior director of UX, explains it’s better to keep AI helpful and approachable without creating false human connections. In short, make your agent helpful and pleasant, but don’t try to make it human.

Reach Your Customers Where They Are

We realized the importance of integrating AI agents across multiple channels—websites, phone lines, messaging apps like WhatsApp, and more. Their 24-hour availability and multilingual capabilities break down barriers that traditionally prevent users from getting answers, making agents accessible. Knowing your customers and meeting them on their preferred platforms ensures a cohesive experience no matter how they interact with your AI agent.
AI agents aren’t a fleeting trend—they’re transforming customer engagement. By listening to data, prioritizing efficiency, and meeting users where they are, companies can build AI agents that truly add value. Like any product, maintain flexibility and adapt to changing realities. You won’t regret it.
Originally published at Forbes on August 7, 2025.

Frequently Asked Questions (FAQ)

AI Agent Development and Strategy

Q: What is the most important lesson learned when building AI agents? A: The most crucial lesson is to listen to data rather than hype. Initial visions for AI tools can be transformed by user feedback and observed behavior, indicating a need for adaptation. Q: Should AI agents be designed with human-like personalities? A: While approachability is important, users primarily value efficiency. Prioritizing helpfulness and speed over overly human-like personalities leads to better user satisfaction and trust. Q: Why is integrating AI agents across multiple channels important? A: Reaching customers where they are by integrating AI agents across websites, messaging apps, and phone lines breaks down traditional barriers to accessing information, making the service more accessible and cohesive. Q: How can businesses ensure their AI agents are successful? A: Success hinges on listening to customer data, adapting plans based on real-world usage, prioritizing functional efficiency, and ensuring accessibility across preferred customer channels. Q: What is the difference between an initial vision and the actual use of an AI agent? A: Data often reveals that users utilize AI agents for purposes beyond the original intent. For instance, a form-building AI agent was predominantly used for customer service. This highlights the need for flexibility and data-driven pivots.

Crypto Market AI's Take

The insights from Jotform's AI agent development journey resonate deeply with our approach at Crypto Market AI. We also emphasize the critical role of data in shaping our AI-powered trading tools and market intelligence. Our platform leverages advanced AI agents to analyze market trends, predict price movements, and execute trades with maximum efficiency. Just as Jotform adapted its AI agent based on user behavior, we continuously refine our algorithms based on real-time market data and user interactions to provide the most effective crypto trading solutions. We understand that the success of AI in finance hinges on delivering tangible value through efficiency and intelligent automation, a principle we embody in all our offerings.

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