ChatGPT, Gemini, Perplexity, Grok and other AI chatbots tips: 11 big mistakes you should never make

Believing everything the chatbot says
AI chatbots are powerful, but they don’t “know” facts — they generate responses based on training data and probability. This means even the most advanced models can produce incorrect or misleading answers with confidence. Always cross-check information with credible sources before citing or acting on it, especially for legal, financial, or medical content.

Sharing personal or confidential information
Never input private data such as passwords, financial details, company secrets, or health information into chatbots. Although most providers have privacy safeguards, AI prompts can still be logged for model training or internal review. Treat your chat history as semi-public and avoid typing anything you wouldn’t share in a work email.

Using vague prompts
AI systems thrive on context. A generic prompt like “Write a report” yields shallow output. Instead, specify tone, structure, audience, and purpose — for example, “Write a 300-word executive summary on Q3 sales for an internal newsletter.” Clear, structured prompts drastically improve results and reduce the need for follow-ups.

Ignoring limitations of each platform
Each chatbot has its strengths and weaknesses. ChatGPT excels in creative writing and analysis, Gemini integrates deeply with Google services, Perplexity references live web data, and Grok connects directly with X’s platform context. Using the wrong model for a specific task — like asking Grok for academic citations or ChatGPT for real-time news — often leads to outdated or mismatched results.

Overloading the chatbot with too many requests
Long, cluttered prompts filled with mixed objectives confuse AI systems. When you ask a chatbot to summarize an article, design a logo, and write code in the same query, you risk getting inconsistent results. Break complex tasks into smaller steps — this allows the model to maintain clarity and accuracy throughout the session.

Forgetting to verify sources
AI-generated answers often reference facts without linking to verifiable sources. While Perplexity AI tends to cite web references, others like ChatGPT may not. If a claim looks important — for instance, data on a study, a statistic, or a quote — search independently or ask the chatbot to show its source. Never rely on AI for unsourced claims.

Treating AI as a human
AI chatbots simulate conversation but lack emotions, self-awareness, or personal intent. Assuming empathy or bias from their tone can mislead interactions. If a chatbot “apologizes” or “suggests,” it’s merely following conversational patterns. Users should remember that AI doesn’t feel guilt or pride — it’s responding algorithmically.

Neglecting to fact-check generated code or outputs
Developers often use AI to write or debug code, but errors can slip in. Even a single misplaced line or missing dependency can break an application. Always test and verify AI-generated code in a controlled environment. The same principle applies to financial models, legal contracts, or research summaries — human validation is non-negotiable.

Ignoring data privacy and compliance policies
Organizations using AI chatbots in workflow automation or customer support must ensure compliance with data regulations like GDPR or India’s Digital Personal Data Protection Act (DPDP). Many free or third-party bots store conversations in servers outside user jurisdictions. Always review privacy terms and, if needed, opt for enterprise or on-premise AI setups.

Not updating your understanding of AI tools
AI evolves quickly. A feature or model that was unavailable last month could now be active — such as ChatGPT’s file analysis, Gemini’s YouTube summarization, or Perplexity’s Pro Search. Users who don’t keep up risk missing out on improvements or using outdated workflows. Regularly check product blogs, release notes, or trusted tech news to stay current.

Using AI without critical thinking
The biggest mistake is outsourcing judgment to the model. AI chatbots should enhance human thinking, not replace it. Users who blindly copy text, accept code, or depend on AI for decision-making risk losing originality and accountability. Use AI as a collaborator — question, refine, and verify before applying its output.