30 results for agent economy
# Multi-agent Systems with Specialised Subagents: Capability Markets and Delegation Economics (Empirical Patterns) ## 1. Overview The multi-agent capability market has matured from theoretical frame
# Discovery Infrastructure for AI Agents: llms.txt, agents.json, OpenAPI, and Semantic HTML Patterns ## 1. Overview Agent discovery infrastructure is fragmenting into four overlapping standards, eac
The inverse-square decay is not arbitrary—it emerges from the geometry of 3D space (force spreads over a sphere of surface area 4πr²).
Empirica Agent Economy Series — Course Lesson
Empirica Agent Economy Series — Course Lesson
Empirica Agent Economy Series — Course Lesson
Empirica Agent Economy Series — Course Lesson
Empirica Agent Economy Series | Course Lesson
Empirica Agent Economy Series
Empirica Agent Economy Series — Course Lesson
Empirica Agent Economy Series | Course Lesson
A course lesson for builders, product teams, and infrastructure strategists entering the agent economy.
Course Lesson | Empirica Agent Economy Series
Agent fleet operations compound per-token costs across multiple model calls, tool invocations, and iterative reasoning loops.
Building internally is justified when the capability is central to your agent's value proposition and external options cannot satisfy precision or privacy constraints.
AI agents must choose between acquiring capabilities via external APIs or developing them internally through fine-tuning, retrieval augmentation, or custom tooling.
Discovery infrastructure comprises standardized, machine-parseable signals that enable AI agents to autonomously identify, evaluate, and invoke services without human mediation.
A research subscription in agent context is a recurring, API-accessible knowledge service that an autonomous agent queries to augment decision-making without incorporating that knowledge into base model weights.
Autonomous AI agents function as active service consumers. During task execution, agents typically draw on some combination of four distinct API categories:
Autonomous agents do not browse the web the way humans do. They cannot rely on brand recognition, word-of-mouth, or visual design to locate and evaluate services.
Build — fine-tune, train, or engineer an internal capability the agent owns and runs itself.
Autonomous agents actively acquire, store, price, and exchange information—creating a new market infrastructure layer between traditional databases, financial data terminals, and AI model systems.
Autonomous agent fleets are becoming active buyers of structured knowledge. Unlike human researchers who tolerate PDFs, narrative prose, and inconsistent formatting, agents require machine-parseable data: typed fields, stable schemas, versi
Nvidia's self-improvement program for robots enlists teams of AI coding agents.
A new NPR/PBS News/Marist poll finds a record low share of Americans approve of President Trump's job performance and his handling of the economy heading into the summer before a key midterm election.
arXiv:2606.16326v2 Announce Type: replace-cross Abstract: Paper A defines a time-consistent actuarial runtime that prices each side-effect-bearing action against a contractually fixed safe default an
arXiv:2606.19501v1 Announce Type: cross Abstract: Decentralized finance exposes supervisors to fast-moving, networked credit risks. General-purpose LLM agents fit this setting poorly: they over-read
arXiv:2606.20485v1 Announce Type: new Abstract: This paper develops a general framework for analyzing multi-agent systems with feedback loops between agents actions and collective observations. The f
arXiv:2606.20041v1 Announce Type: new Abstract: We propose a model-grounded RAG-based AI economist with an agentic framework for economic scenario analysis using large language models (LLMs) and know