Vibe coding seems to be a popular concept these days. Instead of writing all the codes by themselves, developers are turning to natural language prompts to simplify the programming process. It seems much more accessible, efficient, and beginner-friendly.
So what about data analysis? It still seems highly professional now, and the majority of people naturally think that they cannot do the data work but have to resort to analysts for help. But maybe with the advance of AI data analysts, everyone can get a customized tool for them to do 'Vibe Data Analysis'--have the data analyzed simply by asking questions to AI.
They just need to upload their dataset, however large it is, ask questions in plain language, and wait for the tool to process. The tool analyzes the data and responds with clear summaries, visualizations of all kinds of charts, and actionable insights, enabling users to make decisions based on solid evidence, without having to spend hours learning softwares, coding skills, or just waiting for an analyst to free up.
For data analysts, their work may become much more easier, as the tools can take over and automate much of the tedious work like data cleaning and calculatiion. They can focus on more creative and valuable aspects, like digging deeper into the data, interpreting the results, and delivering insights to their clients.
I've seen some very cool products launched in July despite being a summer month (PH Makers never stop), like AI video makers, agents or therapy with AI.
What cool new launches are going to come in August?
AI coding tools seem to come in two main flavors: IDE-based, like @Cursor and @GitHub Copilot, and terminal-based setups, like using @Claude Code to generate commands, scripts, or entire files. Both have their fans, but which one actually helps you move faster?
Curious what flow people are sticking with long term, and where you see the most gains (or frustrations).
