IDYLLIC LABS

An independent research lab for the future of programmable intelligence.

We design composable primitives and legible representations for malleable AI systems.

The future of human agency depends on our ability to shape machine intelligence, not just use it. Today's frameworks constrain how we express AI systems to narrow, rigid patterns. We believe programmable intelligence is the foundation of that future: new primitives and representations that dissolve the boundary between human intent and machine execution.

Our research draws from programming language theory, cognitive science, and interaction design to explore how humans and AI systems can be composed together. Each project advances a specific thesis and explores a concrete problem space, grounded in mechanistic understanding and human-oriented design.

We believe research works best when it improves practice in real-time. Rather than focus on papers, we present our research through libraries, components, and integrations with polished, empathetic devX.

Everything we publish is open source.

Research Areas

01

Primitives & Representations

What patterns are reliable enough to deserve first-class support? We identify building blocks that work consistently across contexts and compose meaningfully. The goal is discovering new primitives on the frontier that extend agent capabilities, and designing representations that make systems legible and malleable.

02

Agent Programming Systems

How do humans express agent systems? The interface between human intent and machine execution. Languages, visual systems, declarative specs. Making the authoring layer disappear.

03

Human-Agent Coordination

How do humans and agents work together? Delegation patterns, attention management, multi-agent orchestration from the human's perspective. Not "how do agents coordinate with each other" — "how does a human effectively direct and collaborate with multiple AI systems simultaneously."

Current Work

01

Elements of Agentic System Design

A conceptual framework mapping "intelligent" agent behaviors to concrete code patterns. What does it actually mean when an agent "remembers" or "learns" or "acts autonomously"?

Framework
02

mdagent

What would be possible if agent behavior was defined entirely in markdown? A minimal interpreter layer for experimenting with new primitives before they need real infrastructure.

Lab Notebook
03

Cortex

A pipeline for turning large unstructured text into connected wikis. An intermediate substrate between raw documents and knowledge graphs.

Lab Notebook
04

Idyllic Runtime

Stateful sessions, streaming responses, real-time sync. The boring infrastructure for agent prototypes, so we can focus on the interesting parts.

Lab Notebook
05

Lab Notes

Raw research as it happens. Explorations, dead ends, and whatever else we're curious about.

Archive

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Occasional updates when we publish new research. For a preview, browse our posts.