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AI as accessibility: what happened when a neurodivergent solutions architect stopped fighting his brain and started building. In this post, I share how AI serves as an accessibility tool for […]

This post is co-written with Vijay Venkatesh, CTO at Bluesight. If you build software for hospitals, you know that compliance work scales poorly. Hospitals managing 340B Drug Pricing Program compliance

When you deploy generative AI agents into multi-tenant production architectures, you face a specific identity problem: when an agent calls a downstream API on behalf of a user, whose identity

Deploying generative AI models to production requires finding the right combination of instance type, serving container with settings, and optimization strategy. This process typically requires a long iteration cycle of

Model customization transforms general-purpose AI models into specialized enterprise assets. By fine-tuning foundation models (FMs) on domain-specific data, businesses teach AI their unique workflows, terminology, and deep domain specialization, along

In dentistry, image quality determines whether a claim is paid or denied. Up to 20 percent insurance claims are initially denied, with missing or low-quality images among the leading causes.

In this post we show how to build a semantic layer on AWS using Stardog’s Semantic AI Application over Amazon Aurora and Amazon Redshift, and how to run a Strands

An artificial intelligence (AI) agent can process an invoice, help adjudicate a claim, or classify a support ticket in a proof of concept. But running these agents across thousands or

This post was co-written with Daniel Han and Michael Han from Unsloth. Deploying large foundation models (FMs) stored at their original 16-bit floating-point precision (BF16 or FP16) is expensive. They

When Model Context Protocol (MCP) tools underperform, the cause is rarely the protocol itself but the tool design. Many teams start by exposing an existing API as-is and trusting the