Nvidia BlueField-4 STX adds a context memory layer to storage to close the agentic AI throughput gap
Nvidia's new reference architecture targets the storage bottleneck slowing agentic AI — and most major storage vendors are already co-designing on it.
Sean Michael Kerner
Agents need vector search more than RAG ever did
Qdrant raised $50M arguing agents made vector search harder, not obsolete. Two production deployments show where general-purpose databases break down.
Sean Michael Kerner
The team behind continuous batching says your idle GPUs should be running inference, not sitting dark
FriendliAI's InferenceSense turns idle neocloud GPUs into an inference revenue stream — and could put downward pressure on token prices.
Sean Michael Kerner
Databricks built a RAG agent it says can handle every kind of enterprise search
Databricks built a RAG agent it says can handle every kind of enterprise search. Here's how reinforcement learning did what distillation couldn't.
Sean Michael Kerner
ServiceNow resolves 90% of its own IT requests autonomously. Now it wants to do the same for any enterprise
ServiceNow resolves 90% of its own IT requests autonomously — 99% faster than humans. Its new role automation framework bakes governance into the execution layer from day one, so AI agents inherit permissions instead of reasoning past them.
Sean Michael Kerner
IBM's $40B stock wipeout is built on a misconception: Translating COBOL isn't the same as modernizing it
IBM just had its worst single-day stock drop in 25 years because of an Anthropic COBOL announcement. Analysts say Wall Street confused translation with modernization. They're not the same thing.
Sean Michael Kerner
One engineer made a production SaaS product in an hour: here's the governance system that made it possible
Every engineering leader watching the agentic coding wave is eventually going to face the same question: if AI can generate production-quality code faster than any team, what does governance look like when the human isn't writing the code anymore?
The 'last-mile' data problem is stalling enterprise agentic AI — 'golden pipelines' aim to fix it
Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with an automated, auditable process.
Sean Michael Kerner
SurrealDB 3.0 wants to replace your five-database RAG stack with one
SurrealDB 3.0 launches with $23M in new funding and a pitch to replace multi-database RAG stacks with a single engine that handles vectors, graphs, and agent memory transactionally.
Sean Michael Kerner
AI inference costs dropped up to 10x on Nvidia's Blackwell — but hardware is only half the equation
New deployment data from four inference providers shows where the savings actually come from — and what teams should evaluate before migrating.
Sean Michael Kerner
'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks
As AI agents move into production, teams are rethinking memory. Mastra’s open-source observational memory shows how stable context can outperform RAG while cutting token costs.
Sean Michael Kerner
Databricks' serverless database slashes app development from months to days as companies prep for agentic AI
Five years ago, Databricks coined the term 'data lakehouse' to describe a new type of data architecture that combines a data lake with a data warehouse. That term and data architecture are now commonplace across the data industry for analytics workloads.