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How People Are Using AI For Visualizing data

In 2025, people ask AI to turn raw inputs into tables, charts, and dashboards—researchers use Claude Code from a terminal, teams refresh recurring cost/performance charts with agents, and creators generate visitor analytics dashboards with Replit agents from a one-shot prompt. Professionals request graphs from signup timestamps, build content tables with links, auto-generate slide decks with charts from financial filings, and scientists visualize molecules via RDKit inside chat; Gemini 2.5 compiles tables and scenarios, and report tools save outputs directly to dashboards.

🤖 ai summary based on 17 tweets

✨ User Stories 10 💡 Expert Insights 1 🚀 Product Demos 6

Stories from AI users. WhatsNextForAI curates public sources. No product affiliations. Opinions are the authors.

All ChatGPT Agent 2 Claude Code 1 Claude 1 Genspark 1 Claude 4 1 Gemini 2.5 1
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Claude-4 is crushing data analysis and data enrichment for my team. Example use case: my team is running a webinar. Within a few hours of launch, we had thousands of signups. I grabbed only the timestamps of signups. Threw them into ChatGPT and Claude asking for a graph of signups per hour, benchmarks, insights, action plan. ChatGPT (specifically o4-mini-high) created errors and blamed them on me. Claude 4 handled it beautifully, first attempt. One of the biggest improvements in these models is going from 3-4 asks in conversation to 1 ask. And when things can be nailed in the first attempt, fully autonomous systems start looking more and more likely in 2026.

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