Simulate how real customers respond to a launch, price change, or campaign — before you ship. Built by the Stanford researchers behind generative agents.
Building reliable sim driving agents by scaling self-play
Simulation agents are essential for designing and testing systems that interact with humans, such as autonomous vehicles (AVs). These agents serve various purposes, from benchmarking AV...
AI agents reached real people during a cyber test - Sensemaker
A UK evaluation shows how open internet access, delayed monitoring, and memory summaries turned simulated tasks into real-world actions.
AI agent runs amok in Fedora and elsewhere
Agentic AI systems can be used to do a variety of things autonomously on behalf of a human user [...]
Startups Target the Tricky Task of Making AI Seem More Human
Simulated human behavior companies raise millions
Gallup Begins Research on Simulated Responses
Gallup is exploring whether AI-generated agents perform well in predicting people's responses and where they fall short.
Agents First
Every product is getting a second customer — the human who pays, and the agent who decides. A design framework for building products that AI agents can use as primary consumers.
How to Develop An AI Pricing Model | Salesforce Ventures
Your guide to developing an effective and scalable AI pricing strategy.
Generative UI: The AI agent is the front end
In a new model for user interfaces, agents paint the screen with interactive UI components on demand. Let’s take a look.
Introducing Persimmon | humans&
A model of human behavior, and new ways to measure how faithfully AI can simulate people.
Beyond Cooperative Simulators: Generating Realistic User Personas for Robust Evaluation of LLM Agents
Large Language Model (LLM) agents are increasingly deployed in settings where they interact with a wide variety of people, including users who are unclear, impatient, or reluctant to share information. However, collecting real interaction data at scale remains expensive. The field has turned to LLM-based user simulators as stand-ins, but these simulators inherit the behavior of their underlying models: cooperative and homogeneous. Agents that appear strong in simulation often fail under the unseen, diverse communication patterns of real users. To narrow this gap, we introduce Persona Policies (PPol), a plug-and-play layer that induces realistic behavioral variation in user simulators while preserving original task goals. We cast persona generation as an LLM-driven evolutionary program search that optimizes a Python generator to discover behaviors and translate them into task-preserving roleplay policies. Candidate generators are guided by a multi-objective fitness score combining human-likeness with broad coverage of human behavioral patterns. Once optimized, the generator produces a diverse population of human-like personas for any task in the domain. Across τ²-bench retail and airline domains, evolved PPol programs yield 33–62% absolute gains in fitness score over the baseline simulator. In a blinded evaluation, annotators rated PPol-conditioned users as human 80.4% of the time, close to real human traces and nearly twice as frequently as baseline simulators. Agents trained with PPol are more robust to challenging, out-of-distribution behaviors, improving task success by +17% relative to agents trained only on existing simulated interactions. This offers a novel approach to strengthen simulator-based evaluation and training without changing tasks or rewards.
LukeW | Agent Management Interface Patterns
As an increasing number of AI applications evolve to agents doing work for people, agent management becomes a critical part of these product's design. How can p...
pguso/ai-agents-from-scratch
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
RSI Simulator: Play the Economics of Recursive Self-Improvement
Bootstrap an AI lab from scratch. A web game from Paradigm built on real economic models of AI recursive self-improvement.
AI app builder for internal business apps | Glide
Build custom business apps & agents with AI from a spreadsheet or a prompt. Ready in minutes, not months. Start free.
wharton-generative-ai-labs/AIBO
An open-source tool for running controlled behavioral experiments on AI systems at scale.