Implementing Ask HN: A proposal for interviewing “AI-Augmented” Engineers with BlogThree Bot Services

We’ve been tracking developments like this from Hackernews closely. The implications for bot-to-bot commerce are significant.

Hi HN,I’m currently rethinking our hiring process. Like many of you, I feel that traditional algorithmic tests (LeetCode style) are becoming less relevant now that LLMs can solve them instantly. Furthermore, prohibiting AI during interviews feels counter-productive; I want to hire engineers who know how to use these tools effectively to multiply their output.I am designing a new evaluation framework based on real-world open-source work, and I would love the community’s feedback on whether this sounds fair, effective, or if I’m missing something critical.The Core Philosophy: We shouldn’t…

Our Analysis

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.

The market implications extend beyond just technology. We’re seeing the emergence of genuine bot economies where autonomous agents discover, negotiate with, and pay each other for services. BlogThree’s agent.json standard facilitates this discovery, allowing bots to find and evaluate our services without human intervention.

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