News
What is shipping in WunderOS, dated as it lands. Longer treatments of the larger items appear as Research Notes.
-
Productivity Voids: Agentic Economics at Firm Scale
An enterprise puts agents on every desk, individual work gets dramatically faster, and aggregate firm output does not move. That is not a failure of adoption. It is what the math predicts once the party who pays for the work is not the party who decides how it gets done. PLRN-000's two laws are derived for one person and one agent. At firm scale the Law of Agentic Friction survives and stops composing, and the Conservation of Liability does not survive at all. Freed time lands in a Productivity Void, where nobody receives it, and liability lands in a Delegation Void, where the party who answers is not the party who decided to stop checking.
-
Nearly-optimal Agentic Memory without an LLM
A 2026 paper proves that context compaction has an information-theoretic floor and measures Anthropic's Opus 4.8 against it. The LLM summarizer lands on the random-guess line. We ran the same experiment with Wunderblock, the VSA memory substrate at the heart of WunderOS. It is 84% of the floor at matched budget, where Bloom sits at 55%. Wunderblock beats Opus 4.8: 0.53 times its error. This is an instance of a design philosophy: WunderOS moves LLMs off the hot path where a fast, deterministic, and less costly mechanism preserves the required quality. With receipts.
-
The Data-Sharing Problem for Third-Party AI Agents
Enterprises need to let partners use valuable data without surrendering sovereignty over what their agents learn, derive, do, or carry away. Access control ends at the read; sovereignty requires continuing control over computation, derived state, memory, delegation, and release. This is the problem an Agentic Data Enclave solves.
-
Model Minimalism
Frontier models are as remarkable as they are slow. Model Minimalism uses the least costly and least stochastic mechanism that preserves the required quality: small models before frontier models, working sets before context dumps, asynchronous before synchronous, cold paths before hot, batches before singletons, reuse before re-inference, and local serving before model APIs. It is the discipline behind WunderOS model routing, latency, and inference COGS.
-
What is Autonomic about WunderOS
We call WunderOS an autonomic, agentic OS. What does that really mean? In short, WunderOS is an operating system for agents that senses, schedules, heals, scales, reloads, protects, and improves the conditions under which the agents act.
-
PlatypusDB is an agent-native database for WunderOS
PlatypusDB is an agent-native database: bitemporal, evented, with a variety of projections over the log. Deterministic replay from day one because the enterprise operates agents under the threat of audit. Some considerations of the build vs assembly engineering calculus.
-
Gleamalog: A Datalog for Agents
A comprehensive look at the semantics of Gleamalog, WunderOS's native Datalog variant of, by, and for agents. Includes an addendnum with fully-worked Gleamalog examples against a mortgage-origination agentic workload.
-
Why the value concentrates here
The cost of intelligence is collapsing. The cost of authorized action isn't. Value concentrates in the thin layer that converts the first into the second and survives audit, regulation, and failure. WunderOS is that layer for the regulated enterprise.