Engineering Ideas

Engineering Ideas

Ethics, safety of artificial intelligence, the science behind intelligence and decision-making, as well as the development of organizations and communities, along with methodological approaches.

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  • 1 week ago | engineeringideas.substack.com | Roman Leventov

    I believe that the most important factor in whether our AI future goes broadly well or poorly is whether people quickly develop effective AI-ready (and AI-enabled) institutions and networks. In that, I agree with the recent Séb Krier's essay "Maintaining agency and control in an age of accelerated intelligence".

  • Jan 7, 2025 | engineeringideas.substack.com | Roman Leventov

    Everyone is talking about AI agent architectures, frameworks, and protocols at the moment. Let me apply John Doyle’s architecture theory lens to this topic, as well as Micah Beck’s hourglass model (2019). In this first post in this series, I present the key ideas from the architecture theory and the hourglass model. In the next post, I will apply these ideas in the domain AI agents. The two core concepts in John Doyle’s architecture theory are levels and layers.

  • Oct 12, 2024 | engineeringideas.substack.com | Roman Leventov

    This post is a reply to Eugene Kirpichov's post on Linkedin.

  • Sep 6, 2024 | engineeringideas.substack.com | Roman Leventov

    This article is the ultimate one in the five-piece series:1. “The future of OLAP table storage is not Iceberg” argues for why object storage-based open table formats: Apache Iceberg, Apache Hudi, and Delta Lake, although they may completely cover all analytical querying needs for some data teams, impose several significant limitations and inefficiencies for some OLAP use cases, and therefore shouldn’t be trumpeted as the “future” of columnar table storage. 2.

  • Sep 4, 2024 | engineeringideas.substack.com | Roman Leventov

    In the previous article, I argued that there is an opportunity for creating a new family of protocols: table transfer protocols, namely Table Read and Table Write protocols to address the M x N interoperability problem between OLAP, timeseries, vector, and search databases on the one hand and data processing/query and ML engines on the other hand.