In a recent LinkedIn post, Linas Beliūnas discusses a remarkable achievement in AI development: a solo developer’s ability to create a sophisticated geospatial tracking system over a single weekend, a feat that typically requires years and millions of dollars in enterprise contracts.
Linas Beliūnas highlights the work of former Google PM Bilawal Sidhu, who reportedly combined Google’s Gemini 3.1 and Anthropic’s Claude 4.6 to build a system dubbed “World View.” This project, as described by Beliūnas, appears to merge the capabilities of platforms like Palantir with Google Earth.
“Enterprise geospatial software can take years & multi-million-dollar contracts to deploy. Using AI, a solo developer built a geospatial tracking system with live planes, satellite traffic cams, and panoptic detection in just one weekend 😳”
The “World View” System and Its Capabilities
According to Linas Beliūnas, “World View” integrates a wide array of data sources, showcasing the power of modern AI and public APIs. The system reportedly includes:
- Live aircraft tracking data.
- Satellite imagery feeds.
- Real-time traffic camera footage from locations like Austin, mapped onto 3D building models.
- Earthquake overlay information.
- Simulated thermal (FLIR), night vision, and a “classified” CRT-style user interface.
Beliūnas emphasizes that this impressive system was constructed using publicly available data and APIs, a key point that shifts the focus from proprietary secrets to the power of data aggregation.
The Power of Aggregation and Public Data
A significant concern raised by Linas Beliūnas in his post is not the secrecy of the data, but its combination. He breaks down the components:
“→ ADS-B plane tracking (public)
→ USGS earthquake feeds (public)
→ Traffic cameras (public)
→ AI “panoptic” object detection, tying it all together”
Beliūnas argues that while each of these data sources is individually harmless, their aggregation creates a powerful, comprehensive overview. He notes:
“Individually: harmless.
Combined: god’s-eye view.”
This perspective underscores a critical shift in technological capability. As Linas Beliūnas points out, tools previously exclusive to large government agencies and commanding substantial enterprise contracts can now be prototyped by a single individual leveraging accessible AI tools and APIs.
Implications for the Future of Development
The implications of such rapid development are profound, as Linas Beliūnas suggests. The ability for a solo developer to assemble a system with the complexity and scope of “World View” in such a short timeframe signifies a democratization of advanced technology. This lowers the barrier to entry for creating powerful data aggregation and visualization tools, potentially disrupting traditional enterprise software deployment models.
Beliūnas concludes his post by sharing a link to another project, highlighting how he built an AI operating system to run a startup with Claude, further illustrating the practical applications and rapid advancements in AI-driven development.
📝 About This Content
This article is based on insights shared by Linas Beliūnas on LinkedIn.
📅 Originally posted on February 22, 2026 | View original post on LinkedIn →