AI chatbots are now widely used to get quick tips, personalized recommendations, or technical guidance across a variety of domains, including web development. Their ability to process vast amounts of data and deliver tailored suggestions in seconds makes them a powerful assistant to developers and other members of the team. Yet when it comes to selecting essential tools for a web project, blindly following AI recommendations can backfire. Let’s find out why.
What AI Chatbots Can Offer
In recent years, AI chatbots have been growing and evolving at an incredible pace, becoming a valuable source of information for both individuals and businesses in various situations, including purchasing decisions. According to a 2024 survey released by Statista, most consumers (61%) are influenced by product recommendations received from chatbots.
Source: Statista
A similar trend can be noticed on the software market. According to the G2’s Buyer Behavior Report 2025, software buyers named GenAI chatbots as the top source that influences the shortlisting of software vendors.
Source: G2’s 2025 Buyer Behavior Report
The time-saving capability makes AI chatbots not just a convenience but a necessity for people who are often limited in time. Web developers definitely fall under this category. Therefore, AI chatbots such as ChatGPT, Gemini, or DeepSeek have become valuable helpers for many dev teams. Such tools not only help save time in various aspects of the development process (prototyping, debugging, documenting, etc.) but also decide on the main items in their technology stacks.
It is challenging to keep up with all the noteworthy novelties in the JavaScript ecosystem for various purposes, such as data analysis, project management, or content handling. The detailed analysis of the matter may be too time-consuming. Thus, it seems reasonable to delegate this task to a smart AI chatbot, or rather, a part of the job, where chatbot suggestions work best:
- Provide a quick overview of available options.
- Narrow down the list of suitable options based on stated requirements.
- Clarify complex documentation or code samples.
- Generate side-by-side comparisons of similar JS tools and their feature sets.
Chatbots can be useful in many ways, but they are far from being ideal. Even the most widely used chatbot comes with the disclaimer: “ChatGPT can make mistakes. Check important info”. That is why it is important to bear in mind the potential negative consequences of relying solely on chatbots for purchasing decisions, especially when selecting commercial JavaScript UI components as core elements for your projects.
Limits and Risks of Relying on Chatbot Suggestions
It is often said that the ability to find answers to challenging questions online is a defining trait of a skilled developer. But it may be tempting to delegate tasks in search of required tools to chatbots, especially when devs have other pressing concerns. And it may work, at least in part. While chatbots can point you in the right direction, relying on them to pick the backbone of your project can be risky for a number of reasons.
Inaccurate Suggestions and Hallucinations
Chatbots may offer outdated or even deprecated solutions. It is rare for chatbot answers to reflect very recent product updates. Also, it happens that chatbots attribute nonexistent features or APIs (hallucinations) to recommended products. Sometimes, AI chatbots fail to make a clear distinction between similar yet different JavaScript tools.
Focus on Popular Tools
AI chatbots generate suggestions based on patterns learned from various sources available online (documentation, tutorials, forums, etc.). Therefore, they give priority to more popular, well-documented, and frequently mentioned tools. What’s wrong with that? This means that some less-known (or new) but viable tools may be overlooked unless explicitly prompted.
Lack of Awareness about Project Peculiarities
AI chatbots often struggle to fully grasp the unique characteristics of a development project that influence tool selection. Factors like the team’s expertise, architectural constraints, or long-term technical goals are difficult to convey in a prompt and even harder for a chatbot to assess correctly.
Lack of Practical Insight
AI chatbots can provide you with an overview of functional capabilities for a given product, but they will hardly warn you about potential drawbacks that become apparent only during hands-on use. For instance, a chatbot might suggest a JavaScript library that looks great on paper, but has compatibility issues with frameworks or performance decline under high loads.
Many of the risks discussed above stem from vague, incomplete, or overly generalized prompts. While well-thought-out prompts do not eliminate the possibility of hallucinations, outdated suggestions, or other issues, they can significantly improve the relevance and accuracy of responses. When you provide crucial details about your project and the tool required for it, chatbots are more likely to return meaningful suggestions.
The efficiency of your interaction with AI chatbots may also depend on the proper use of their key capabilities such as deep research-like features and adherence to the best known practices.
Ways to Improve Your Experience when Communicating with AI
Here are practical techniques to help you communicate more clearly and productively with AI, whether you’re working through complex decisions or testing ideas:
- Clearly state your requirements and specify the format and style you expect in the AI’s reply.
- Supply documents and relevant instructions to help the AI understand the context.
- Prompt AI to generate several options instead of settling for a single answer, thus encouraging it to explore deeply and provide unexpected insights.
- Use deep research in ChatGPT if you need a more precise and reliable answer.
- For important tasks, switch to the advanced models instead of relying on the default fast one.
- When you’re stuck on a decision, try defending the opposite view. The counterpoint often reveals blind spots and unlocks unexpected solutions.
- Test your results by switching the order of options, since language models, including ChatGPT, often prefer the first option you’ve listed.
- Try the double-check method and ask the same question in two separate chats – one requesting confirmation and the other critique. Rely on the outcome only when both responses agree.
Tips to Confirm or Challenge AI Suggestions
Despite any possible precautions, it is still recommended to verify all AI-gererated suggestions, especially when they influence core decisions in your project. For this purpose, it is reasonable to form your own opinion on shortlisted options to cross-check chatbot recommendations. Here, you can use the following sources:
- Popular software review platforms (e.g., G2, Capterra, SoftwareSuggest).
- GitHub activity, open issues, and commit history.
- NPM download statistics and package popularity.
- Independent benchmarks and performance comparisons.
- Vendor case studies and testimonials.
When consulting chatbots about commercial tools for a web project, it is essential to pay attention to the availability of a trial version, technical support, quality of documentation, and integration options with popular frontend frameworks.
Final Thoughts
AI chatbots are valuable companions during the research phase when exploring potential JavaScript tools for your project. However, chatbot recommendations should be taken as one of numerous information sources rather than as undisputed facts, since chatbots are still prone to errors and inaccuracies. Therefore, it is advisable to complement chatbot responses with manual research to select the most suitable tool for a web project.