Organisational charts reveal formal structures. But much of organisational life unfolds through informal networks, routines and patterns of co-ordination that are difficult to observe directly.
org charts depict reporting and instructions flows. Nothing else. All the work interaction is outside the orgchart. None of it needs codified selves to make it observable, it is already observable without AI, just needs too much coordination and effort to do it.
[[Sabine Harnau p]] talk [[PKM Summit 2026 20260320080947]]
My pkm system has always been personal, not so much the QS stuff, but personal meaning. I don't really get the PKM as factual stuff starting point. [[Personal Knowledge Management Is Threefold Personal]] after all.
We introduce a minimal hierarchical partially observed control model with latent dynamics, structured episodic memory, observer-belief state, option-level actions, and delayed verifier signals.
大多数AI系统设计倾向于使用完全可观测的模型，并假设系统状态是已知的。但作者提出了一个部分可观测的层级控制模型，包含潜在动态、结构化情景记忆、观察者信念状态、选项级行动和延迟验证器信号。这一观点挑战了传统AI系统设计的完全可观测性假设，认为部分可观测性更接近现实世界的复杂性。
the majority of operational problems that arise when moving to a distributed architecture are ultimately grounded in two areas: networking and observability.
track
In the case of dbt, rather than executing dbt models as black boxes, the framework can accumulate information about dbt runs over time, making that information available for longitudinal views and connecting it back to individual runs of your pipelines with no marginal setup effort.Engineers can monitor dbt model execution in the same tool they use to monitor other technologies on the data platform.Observability boils down to a couple of simple capabilities that we think everyone operating with data needs. With Dagster, individual dbt users can self-serve questions like “Which dbt models are at risk of becoming bottlenecks in our reporting pipeline?” And engineers can monitor dbt model execution in the same tool they use to monitor other technologies on the data platform.
how [[dbt]] enables [[o11y]]
Support for observability is built into the system. Whether the nodes in your orchestration graph (what Dagster calls solids) run dbt models or reports in Mode, instigate Spark jobs or perform pure Python computations, they yield a stream of structured metadata back to the framework as they execute. This metadata makes deep integrations with other technologies possible.
[[observability]] is built into the system, and is becoming an important need for security and compliance as well, [[o11y]]
Lovato, J., Allard, A., Harp, R., & Hébert-Dufresne, L. (2020). Distributed consent and its impact on privacy and observability in social networks. ArXiv:2006.16140 [Physics]. http://arxiv.org/abs/2006.16140
"The wider world is mostly characterized by wicked learning environments, where you can’t see information. It’s hidden from us. Feedback is delayed and sometimes inaccurate.
Un-wicked-ize computing! Make it visible! Let everyone see it happen! This could be the most illuminating, clearest environment, the most causal & overt of realities! If we dare to try to make it so.
#UnwickedizeComputing!