Bespoke means custom...
Bepoke tailoring means one that fits you perfectly.. P/C Wikimedia.
... as in a "bespoke" suit--one that's made specifically for you.
For a long time, if you wanted a custom data visualization, you had two tough choices: learn a massive, complex platform or hire an engineering team. It was slow, expensive, and often frustrating. But something big changed in early 2026.
We've entered the era of seriously good "vibe coding."
This isn't about writing perfect lines of code for months; it's about using LLMs to rapidly generate functional software in minutes. The barrier to entry hasn't just lowered—it has collapsed. Now, we can create interactive, special-purpose tools for a single task and then just throw them away when we're done. This new technology has completely changed the cost structure of traditional sensemaking tasks. [Russell, 1993]
The New "Floor" for Visualization
I've seen this first-hand in the classroom. Students who used to struggle with syntax are now building professional-grade interactive tools in hours. By offloading the "boilerplate" work to AI, they can focus on the most important part: mapping data to visual meaning. As noted in recent research, data visualization literacy is no longer just for experts; it's a vital workplace skill for everyone. [Börner]
Disposable Sensemaking Tools
In a professional setting, this means we can build "disposable" artifacts. For example, when analyzing conceptual overlaps in academic papers, we don't need a generic network tool. We can vibe-code a "Concept Map" in ten minutes that does exactly what we need: highlight specific connections between papers and topics, then get discarded once the insight is found. Here's one I made in a few minutes. I uploaded a set of papers, have it identify the common concepts between the papers, and then create an interactive visualization so I can probe the relationships between the papers and what's in them. Try it out yourself.
The Challenge: Quality vs. Speed
Is it perfect? Not on the first try. "Zero-shot" AI outputs often have messy labels or weird colors. However, vibe coding is an iterative loop. You aren't a "coder" anymore; you're a "director of design." You spot the flaws, ask for a tweak, and watch the tool evolve in real-time.
There is a catch, though. Research shows that when making moves is too "cheap" and easy, we sometimes fall into mindless trial-and-error instead of thoughtful planning. We have to stay "planful" even when the tools are fast. [O'Hara]
Exploration vs. Explanation
Bespoke tools are amazing for finding the truth (such as when you're doing Exploratory Data Analysis), but they can be terrible for telling the truth to others. For presentations, stick to the classics like bar charts and histograms. You don't want your audience to have to learn a whole new visual language just to understand your point. You can read all about it in my paper from a few years ago. [Russell, 2016]
One way to explore a set of papers is with an interactive, bespoke AI analysis tool. Today, in 10 minutes, I made this bespoke info visualization that reads in a set of PDFs, creates a 25 word summary of the paper, and then lets you ask questions of all the papers, putting the answer to your query/prompt in the third column.
I've asked for short summaries of the papers AND in column 3, asked the tool to extract all of the place names mentioned in each PDF.
When we did this same task in 2014 on the SearchResearch Rancho, it was a LOT more complicated and not nearly as accurate. Things do improve!
SearchResearch Lessons
The future of sensemaking isn't simply that we'll have one giant software platform that does everything for everybody. It's a series of small, tight, custom-fit tools that are easy to make, and more-or-less disposable. They help us see deeply into our data just when we need to.
What bespoke tool will you vibe-code today? Have you tried vibe coding to build tools that you've needed? Let us know in the comments.
And keep searching...
References
Börner, A Bueckle, M Ginda . Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments. Proceedings of the National Academy of Sciences, 2019
Knoll, Christian, Torsten Möller, Kathleen Gregory, and Laura Koesten. "The Gulf of Interpretation: From Chart to Message and Back Again." In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pp. 1-17. 2025.
O'Hara, Kenton P., and Stephen J. Payne. "The effects of operator implementation cost on planfulness of problem solving and learning." Cognitive psychology 35.1 (1998): 34-70.
Russell, Daniel M. "Simple is good: Observations of visualization use amongst the big data digerati" Proceedings of the International Working Conference on Advanced Visual Interfaces, pp. 7-12. 2016.
Russell, D. M., Stefik, M. J., Pirolli, P., & Card, S. K. (1993, May). The cost structure of sensemaking. In Proceedings of the INTERACT'93 and CHI'93 conference on Human factors in computing systems (pp. 269-276).
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