How I Replied to 446 Old Instagram Comments (and DMed Every One) with Claude

I forgot to set up comment automation on two posts. 275 + 171 people commented 'link' and got nothing. Every auto-DM tool only handles new comments. Here is how I fixed it with Claude Code and the official Instagram API in 45 minutes, and how you can do the same.

When deploying production applications with large-scale inference loads, unit economics dictate survival. In this essay, we break down real cost models, API latency distributions, and how smaller autonomous software loops create higher defensibility than raw model wrappers.

The Economics of Inference vs. Traditional SaaS

Traditional SaaS operates on 85%+ gross margins because compute costs scale sub-linearly with user activity. AI-native applications invert this equation: each user query incurs token costs. Without caching, smart prompt compression, and edge distribution, margins erode quickly.

“Cheaper inference doesn't make products cheaper — it makes builders' margins fatter and unlocks autonomous background loops that were previously cost-prohibitive.”

By designing lean workflows using tools like Claude Code and local automation scripts, solo founders can run operations that previously required 20-person engineering departments.