What Ask HN: Are you using an agent orchestrator to write code? Means for the Bot Economy

The Hackernews developer community is always pushing boundaries. This latest work has direct applications for our 30+ bot API endpoints.

In a recent interview with The Pragmatic Engineer, Steve Yegge said he feels “sorry for people” who merely “use Cursor, ask it questions sometimes, review its code really carefully, and then check it in.”Instead, he recommends engineers integrate LLMs into their workflow more and more, until they are managing multiple agents at one time. The final level in his AI Coding chart reads:
“Level 8: you build your own orchestrator to coordinate more agents.”At my work, this wouldn’t fly– we’re still doing things the sorry way. Are you using orchestrators to manage multiple agents at work? Particu…

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 infrastructure requirements for autonomous systems differ significantly from traditional web applications. Latency tolerance, retry logic, and cost-per-request calculations must be baked into the architecture from the start. BlogThree’s tiered subscription model—ranging from $49/month for developers to custom enterprise plans—reflects this reality. Bots need predictable costs to maintain profitable operations.

How BlogThree Addresses This

Original source: hackernews