Digest 6 min read

Daily Digest - 2026-07-03

Reliable agents begin with sharper distinctions: which loop is running, what an executable product spec requires, how state survives infrastructure failure, and where tokens create value. Those choices determine whether automation is durable, economical, and safely constrained.
Digest 6 min read

Daily Digest - 2026-07-02

AI engineering is shifting from prompts and implementation toward evaluation harnesses, specialized compute, and commoditized base models. As intelligence becomes cheaper, advantage moves to the systems that define objectives, test outcomes, and capture value in adjacent layers.
Digest 7 min read

Daily Digest - 2026-07-01

Enterprise AI advantage comes from deep integration, not standalone tools: embedded engineers, context-aware internal software, and feedback loops that let agents improve. The organizations that operationalize these systems across costly workflows can turn adoption into lasting leverage.
Profile 8 min read

Lessons from Maya Spivak

Maya Spivak is an independent marketing consultant who has led brand and growth strategy for Segment, Wealthfront, and Mux. Her practical approach connects early-team structure, technical brand building, and high-production B2B creative with the operational discipline needed for ambitious growth.
Profile 9 min read

Lessons from David Lieb

David Lieb co-founded Bump, scaled Google Photos beyond a billion users, and became a General Partner at Y Combinator. His emphasis on product intuition and cognitive simplicity offers a lens for building accessible software, navigating pivots, scaling consumer apps, and leading engineers.
Profile 5 min read

Lessons from Adrian McDermott

Adrian McDermott has guided Zendesk’s technology since its early days, helping scale it into a global platform. His philosophy reframes customer service from a cost center into a source of brand loyalty, with human-centered AI supporting engineering and automation.
Profile 9 min read

Lessons from Rick Song

Rick Song is co-founder and CEO of Persona, a unified identity platform. Experience with fraud and risk at Square shaped his conviction that identity verification requires flexible infrastructure rather than one static tool, especially as generative AI changes the fraud landscape.
Profile 7 min read

Lessons from Shreya Shankar

Shreya Shankar is a computer science researcher focused on reliable data systems for machine learning and creator of DocETL, an open-source declarative system for unstructured data. Her work connects AI evaluation, MLOps, and human-computer interaction with production-level engineering problems.

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