About

Infinite Slate is a consultancy dedicated to long term positive impact on humanity with expertise and two decades of industry experience in the following areas

Machine Learning and Artificial Intelligence

  • Industry Standard with experience from Slack, Palantir, Fivetran and Pixar

  • Data: API / Data Backend with experience from Slack, Palantir, Fivetran and Pixar

  • Efficiency: Cost reductions through model introspection and algorithm evaluation

  • Release Time: Find bottlenecks in release process with impact-over-effort ratios

  • Stakeholder Confidence: model introspection and intermediate layer analysis

  • Diminishing Returns: Asymptotic return optimization with model introspection

Architecture and System Design Review

  • Industry Standard: Software architecture with experience from Slack, Palantir, Fivetran and Pixar

  • What’s Out There Analysis: Evaluation of possible managed service tradeoffs

  • Cloud Vendors: Help finding the best vendor depending on needs

Org and Management

  • Industry Standard: Product org eval with experience from Slack, Palantir, Fivetran and Pixar

  • Coordination Overhead: Analysis of coordination overhead bottlenecks

  • Engineering Efficiency: Granular evaluation of efficiency across org

  • Prompt Engineering: Conversion from traditional eng org to modern one leveraging AI

People

Andy Dreyfuss (Principal)

Status: Currently at capacity but open to initial consult requests.

From building Palantir’s data team and working on Foundry’s data ingestion framework, to rearchitecting Fivetran, to building data science pipelines at Pixar and Kairos Aerospace, to designing large volume systems at Slack, my two decades plus in software has given me in-depth knowledge of some of the world’s most critical system architectures, full stack designs and people organizations at all scales. I approach problems topologically from all ends, looking at the space surrounding the problem, the interactions with business requirements as well as technical upstream and downstream dependencies, finding possible paths and natural solutions that meet the goals of the business. I help build a common picture of what we have and where we could go from here, applying a balance of industry standards and creativity to each problem. I’m a strong advocate for iterative approaches that move very fast with frequent short pauses to evaluate direction from a higher level and adjust as needed.

My current work is in both the public and private sectors, applying machine learning to the problem of branching patient care towards an optimal outcome as early as possible in their journey through the system.