I’m looking to bring artificial intelligence into my planting and seeding workflow so I can streamline how and when seeds go into the ground. The overall aim is to optimize farming processes rather than simply chasing higher yields or tackling logistics; everything comes back to making planting decisions smarter, faster, and more data-driven. Here’s what I need: • A practical plan for embedding AI into the planting and seeding stage of my operation. • Clear recommendations on the data that should be captured in-field (soil, weather, GPS, machinery telemetry, imagery, or any other source you deem valuable). • A working proof of concept or model—Python or similar—that demonstrates how seed placement, row spacing, or timing could be fine-tuned automatically. • An implementation roadmap that outlines hardware, software, and integration steps with typical farm equipment (John Deere Ops Center, Trimble, etc.). • Brief guidance on training and maintenance so the system keeps improving throughout the season. You’re welcome to draw on machine learning, computer vision, or geospatial analytics; just keep the solution pragmatic for a modern farm. If this sounds like a challenge you can tackle, let’s talk details and get seedlings in the ground with smarter support.