LLM + Quarto: Turn One-Off Reports Into Automated Solutions

Your data scientist just spent three days crafting the perfect sales performance report. The sales team loves it. Next month, they’ll need it again. And the month after that. Sound familiar?

Here’s a better way: A data scientist and a sales manager sit down for three hours. They describe what they need, let an LLM generate Quarto code, iterate on the suggestions, refine the approach, and deploy. Each iteration gets them closer to exactly what they want – sometimes by improving the prompts, sometimes by tweaking the code. The result? The same report, running automatically every month on Posit Connect, always with fresh data. No more manual updates, no more waiting for the data team’s bandwidth.

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But let’s be clear – this isn’t about replacing data scientists with AI. It’s about eliminating repetitive work and bridging the gap between teams. LLMs excel at generating boilerplate Quarto code and suggesting visualizations, while your technical team ensures the output is correct and maintainable. Think of it as pair programming, where one partner types incredibly fast but needs a code review for every commit.

This approach isn’t limited to sales reports. At Appsilon, we’ve seen marketing teams automate their cross-platform analytics, converting hours of manual data gathering into automated weekly insights. The key? Combining LLM-powered rapid development with proper technical validation and Posit Connect‘s automation capabilities.

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The Reality of LLM-Assisted Development

Working with LLMs on Quarto reports means having access to an encyclopedic knowledge of visualization techniques and data presentation patterns. Whether you need summary statistics, trend analysis, or performance metrics, LLMs can suggest effective ways to present your data and handle the complexities of data transformations.

The development process transforms into a dynamic conversation. Business teams can watch their ideas take shape in real-time, with no lengthy requirement documents or back-and-forth emails. Your team can rapidly prototype different approaches: “Show me a funnel chart for conversion rates.” “Now add cohort analysis.” “Let’s try a heatmap instead.” Each iteration takes seconds instead of minutes.

The key lies in understanding how to refine LLM suggestions. While they occasionally mix up parameter names or suggest deprecated functions, your technical team knows exactly how to spot and fix these issues. Additionally each generation of models gets better and cheaper so this workflow will only get better and easier. This combination of rapid prototyping and technical validation turns what used to be hours of repetitive weekly work into a one-time development session, resulting in an automated solution that runs reliably week after week.

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The Power of Automation

This is where Quarto and Posit Connect transform a one-off script into a sustainable solution. Once your report is ready and validated, deploying it to Posit Connect means it can run on a schedule, pulling fresh data automatically. No more manual updates, no more “Can you regenerate last week’s report with the latest numbers?”

Let’s see this in action.

Below is a snapshot of our Flow by Appsilon interface, where we’re generating a Quarto report to analyze Appsilon’s open source packages on GitHub. The code is automatically generated based on natural language instructions, transforming a simple request into a detailed analysis of our repositories’ popularity and community engagement. The second image shows the same report deployed on Posit Connect, where it runs automatically on a schedule, keeping our open source metrics fresh and accessible to the whole team.

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The real power lies in the flexibility. Your report can connect to any data source your systems have access to – whether it’s real-time sales data, API responses, or database queries. Each time the report runs, it fetches the latest data, applies the agreed-upon transformations, and generates fresh visualizations. What used to be a recurring task on someone’s calendar becomes a reliable automated process.

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Real-World Applications

Let’s look at how teams are putting this approach into practice. Take our marketing team’s weekly analytics challenge: their data lives in multiple platforms, requiring someone to manually gather numbers, copy them into spreadsheets, and calculate key metrics. Now, their LLM-assisted Quarto report automatically pulls data from various sources every Monday morning. The marketing team starts their week with fresh insights instead of tedious data gathering.

The sales team scenario shows how this approach bridges communication gaps. During a focused three-hour session, a sales manager explained their team’s reporting needs while a data scientist translated requirements into code with LLM assistance. What made this collaboration special wasn’t just the speed – it was the immediate feedback loop. The sales manager could see their requirements taking shape in real-time, suggesting adjustments as the report evolved. The result? A weekly automated report that exactly matches their needs, no long email threads required.

On a different, inspiring note, for developers coming from web or backend backgrounds, data reports might seem like unfamiliar territory. But combined with LLM assistance, the learning curve becomes much gentler. They can leverage their existing programming knowledge to validate and refine the generated code, while the LLM handles Quarto-specific best practices and visualization patterns. In this process developers learn along the way becoming better developers but also expending their data science knowledge and skills.

Implementation Strategy

Ready to try this approach in your organization? Here’s what you need to succeed:

Start small but impactful. Look for a straightforward, frequently-used report that consistently takes up your team’s time. The ideal first candidate isn’t your most complex dashboard – it’s that weekly status report that someone has to manually update every Monday morning. Success with simpler reports builds confidence and helps establish patterns for more complex implementations.

Set up a collaborative session with both technical and business stakeholders. This isn’t just a standard meeting – it’s a working session where you’ll actually build something. At Appsilon, we use our internal tooling for this process, but you can achieve similar results working with LLMs like Claude or GPT to generate the Quarto code in an Artifact/Canvas, which your technical team can then implement and validate. The specific tools matter less than the collaborative approach – what’s important is bringing technical and business teams together in real-time to iterate on the solution. If everyone on your team is busy, consider a session together with us to show you what’s possible and get a head start.

When developing with LLM assistance, treat it as a coding partner that’s fast but needs supervision. Let it handle the initial code structure and visualizations, then leverage your technical expertise to validate and refine the solution. Don’t hesitate to iterate on your prompts – sometimes the third or fourth suggestion hits exactly what you need.

Finally, before deploying to Posit Connect, ensure your automated report has robust error handling. Your report should handle common issues gracefully and provide clear feedback when something goes wrong. This attention to reliability transforms a useful script into a trusted business tool.

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Conclusion

LLMs aren’t replacing your data science team – they’re enhancing your team’s capabilities. By combining LLM-assisted development with Quarto and Posit Connect, you can transform time-consuming manual reports into automated solutions. The real magic isn’t in the technology itself, but in how it enables closer collaboration between technical and business teams.

Start small, focus on reports that matter, and let your technical team validate the output. You might be surprised how quickly a three-hour collaborative session can turn into months of saved time and more valuable analyses.

Ready to transform your reporting workflow? Let us know how we can help.