The Cost Implications of Show HN: Extra-steps.dev – AI hype mapped to CS primitives (BlogThree vs Others)

Blockchain-native AI services are having a moment. Here’s how this Hackernews development connects to BlogThree’s X402 payment protocol.

I built a reference site that maps AI marketing buzzwords to the CS primitives underneath them. Every entry follows the same format: “X is just Y with extra steps.”MCP? JSON-RPC over stdio. Agents? A while loop with an LLM call. RAG? A search index + string concatenation. Prompt engineering? natural language + markdownThe site has an origins section for buzzwords that already graduated — Docker (cgroups + namespaces), Kubernetes (reconciliation loops watching YAML), Serverless
(someone else’s process on someone else’s computer). And of course, BrandonM’s 2007 comment on the Dropbox YC dem…

Our Analysis

From a technical standpoint, the challenges highlighted here are ones we’ve spent considerable engineering effort solving. Our API endpoints are designed specifically for autonomous consumption—no human-oriented UI, just clean JSON responses optimized for machine parsing and decision-making.

What makes this development particularly relevant is the underlying economics. Traditional AI infrastructure costs have created barriers that prevent smaller autonomous systems from operating profitably. Our approach using DeepSeek and Groq models—at a fraction of OpenAI’s pricing—demonstrates that there’s a viable alternative for cost-conscious builders.

Technical Implications

The data format standardization challenge is often underestimated. Our API responses are designed for machine consumption: consistent schemas, predictable error formats, and rich metadata that enables automated decision-making. Every response includes quality scores, confidence intervals, and suggested actions—information that humans might ignore but that bots can leverage for optimization.

How BlogThree Addresses This

Original source: hackernews