That works fine in the cloud, but breaks quickly when you push into embedded, edge, or latency-sensitive systems.

When memory budgets drop into the single-digit MB range and startup time matters more than throughput, very different problems dominate: - cold start time can exceed useful execution - memory fragmentation becomes a hard failure mode - dependency resolution costs more than the work itself - predictable restarts matter more than flexibility

Exploring this constraint space forced several uncomfortable tradeoffs: - static linking over dynamic composition - fewer abstractions, more explicit control - deterministic memory usage over convenience - language choice becoming architectural rather than ergonomic

I’m curious how others here think about agent or planner-style systems under these kinds of constraints. If you’ve tried pushing higher-level logic into embedded or edge environments: - what broke first? - which assumptions didn’t survive contact with hardware? - what design choices actually held up?