How to Create BI Dashboards with Vibe Coding—and Are Replit and Lovable Suitable?
Vibe coding is a new development style where you state requirements in conversation and an AI coding agent generates and modifies code accordingly. With vibe-coding tools, even people without formal programming training can develop working software.
Platforms like Replit and Lovable are especially popular. You may have seen social media posts of people building websites with vibe coding.
Looking at those examples, you might assume vibe coding is only for prototypes or hobby projects. However, when combined with the right operational foundation, it can support business software that runs in production and stays maintainable over time.
In this article, I explain how to apply vibe coding in real business settings—specifically how to build BI dashboards with vibe coding and what knowledge and practices you need to make them work.
Why build BI dashboards with vibe coding?
Many BI dashboards focus on aggregating and displaying as much business data as possible. As organizations accumulate more data, dashboards tend to become more complex. In practice, the dashboard itself becomes the goal, and the work stops short of driving decisions and judgment.
In real business operations, KPI granularity and formulas change frequently. Historically, updating dashboards required engineering effort and slowed down decision-making. As COO of Squadbase, I’ve experienced months where dashboard maintenance consumed dozens of hours of work. If you’ve ever wondered why “a simple change” takes so long, you’re not alone.
With vibe coding, requests like “change the sales aggregation window” or “add a new KPI” can be implemented through dialogue with the AI.
Can popular vibe-coding platforms be used for enterprise BI dashboards?
Most people start with Replit or Lovable, but there are several hurdles for enterprise BI dashboards, making them impractical as-is.
Data-source connectivity
Production data typically lives in on-prem databases (PostgreSQL, MySQL), cloud data warehouses (BigQuery, Snowflake), or SaaS APIs (Salesforce, HubSpot). Connecting to these sources in a way that satisfies enterprise security requirements usually forces you to build dedicated infrastructure or additional systems.
Security and deployment
Sharing dashboards internally requires deployment to an environment that’s secure and accessible only to employees. Depending on the use case, you may also need role-based data access control and to capture audit logs for incident response and compliance.
These requirements are unavoidable in enterprise contexts—and meeting them usually demands engineering time and therefore cost.
So how can we actually build BI dashboards with vibe coding?
Tool selection matters. Below are practical choices for AI tools, development environments, frameworks, and data connectivity.
The right AI tools — Coding agents
There are many AI tools that can develop software, and vibe-coding platforms are one option. For serious dashboard development, coding agents are the most capable. Examples include Claude Code, Cursor Agent, and Codex CLI. These tools understand source code as context and, based on your instructions, edit files from the terminal. They can also be extended via MCP (Model Context Protocol).
If there’s an MCP server for your target data source, the agent can automatically learn schemas and handle data retrieval and transformation.
Even without an MCP server, you can provide API docs and have the agent generate the necessary code.
Note that you will need a proper development setup—an editor and a terminal—to use these coding-agent tools effectively.
Development environment — GitHub Codespaces
If you already have a local environment, use it.
If not, GitHub Codespaces is a great option. You can spin up a full-featured dev environment in the browser and start today.
For setup instructions, see this eBook:
Building a Cloud Dev Environment with GitHub Codespaces
Application frameworks — Streamlit / Next.js
For code-first BI dashboards, a full-stack web framework works best. I especially recommend Streamlit and Next.js.
Streamlit is a Python full-stack framework well-suited to “data apps” that connect to data sources. Writing in Python makes data processing and visualization straightforward.
Next.js is a React-based full-stack framework. It’s one of the most popular frameworks worldwide, used by many companies and brands. It excels at rich interactions and polished UIs.
Choose based on your goals. Squadbase provides dashboard starter templates for both:
How do we share dashboards safely inside the company?
Now that we’ve covered how to build dashboards with vibe coding, let’s look at secure internal sharing. Our platform, Squadbase, was built precisely for this need. It provides an operational foundation to safely share and run dashboards built via vibe coding:
- One-click deploy: Use Squadbase Editor to do vibe coding on Squadbase and deploy with a single click.
- GitHub-linked deploys: Connect a GitHub repo and deploy automatically on each change.
- Access restrictions: Only invited members on Squadbase can view the app.
- Authorization: Control access by user and group.
- Data-source connections: Connect your data sources securely with minimal effort.
- Audit logs: Capture and retain complete access history.
By deploying the generated code directly to Squadbase, you can meet enterprise security requirements and enable your whole team to use the dashboard.
Where does vibe coding beat Tableau, PowerBI or Looker?
Vibe coding shines not just at “building dashboards,” but at continuously evolving an application’s behavior as requirements change. While Tableau/Looker excel at drag-and-drop visualization, semantic layers, and self-service BI, vibe-coding approaches have clear advantages in the following areas:
Application-level flexibility You can express custom UX, workflows, and business logic in code. Beyond “read-only” views, you can build input forms, approval flows, and rich integrations with external APIs on the same foundation.
Change velocity & developer experience With coding agents and MCP, schema/KPI changes are applied conversationally and promoted through tests and deploys quickly. This fits teams that operate under constant requirement change.
Version control & reproducibility Everything is code, so Git enables history, review, rollback, and PR-driven change management. CI smoke tests protect quality while you increase release frequency.
Data connectivity & extensibility MCP servers/SDKs connect to internal systems, SaaS, and DWHs the way your org needs. It plugs into existing SSO/RBAC and audit-logging foundations without contortions.
Cost structure & ownership Fewer constraints from per-user/per-view licensing; the codebase becomes a durable asset you own. It’s easier to start small, extend over time, and keep long-term TCO in check.
Note: Tableau/Looker are still the best fit for certain scenarios—rapid drag-and-drop exploration, established LookML/semantic models, and mature, at-scale self-service with centralized governance. Conversely, if KPIs and business logic change frequently, your use case requires workflows or external APIs (i.e., “view + act”), or you want automated tests/CI tightly coupled to production operations, vibe coding tends to win.
Conclusion
With the right choices, vibe coding is practical for enterprise BI dashboards.
- AI tools: Use Claude Code or Cursor Agent.
- Dev environment: Build in the browser with GitHub Codespaces.
- Frameworks: Choose Streamlit or Next.js.
- Deployment: Operate securely on Squadbase to satisfy enterprise requirements.
If traditional BI tools feel heavy and slow, consider building dashboards with vibe coding. You can increase development speed and reduce operational costs at the same time.
If you’re considering vibe coding in your organization, start by discussing concrete technical choices with your engineering team.