Subscribe
Sign in
Home
Podcast
Archive
About
Latest
Top
Discussions
Build a Jev-Supervised AI Agent
Typed decisions, guarded tools, and a measured comparison with LLM supervisors
11 hrs ago
•
Damien Benveniste
4
September 2026
How Jev Turns Questions Into Decisions
Inside the state, typed-output, probability, and application-policy contracts of a decision model
Sep 30
•
Damien Benveniste
5
The Complete Guide to Evaluation Pipelines for AI Agents
From production traces and isolated trials to evidence you can use for release decisions
Sep 28
•
Damien Benveniste
11
How AI Agent Memory Updates a Changed Preference
Follow one correction from a user message to the active fact a future task retrieves.
Sep 25
•
Damien Benveniste
6
How LLM Routers Balance Cache Reuse and Queue Time
Four routing strategies, one repeated prompt, and the point where a cold replica wins
Sep 23
•
Damien Benveniste
9
How Test-Time Scaling Allocates LLM Reasoning Across Depth, Width, and Feedback
Why the same inference budget can finish one path, explore alternatives, or learn from a failure
Sep 21
•
Damien Benveniste
5
How Constrained Decoding Makes LLM Outputs Follow a Schema
The decoder can guarantee the shape of a tool call while leaving its values completely wrong.
Sep 18
•
Damien Benveniste
12
How Sparse Attention Makes Long-Context LLMs Cheaper, and What It Misses
Full reach, sliding windows, and learned selectors turn the same prompt into three different evidence sets.
Sep 16
•
Damien Benveniste
8
Four Retrieval Techniques for Video Search
Why frame rate, change detection, temporal hierarchy, and targeted rewatching fail in different ways
Sep 14
•
Damien Benveniste
8
Deep Dive: How AI Text Watermarks Work
How a language model leaves a detectable pattern in its word choices, and why copying the text preserves it.
Sep 11
•
Damien Benveniste
5
1
Deep Dive: How Speculative Decoding Makes LLMs Faster
How a smaller model helps a larger model generate text faster without changing its output distribution.
Sep 9
•
Damien Benveniste
15
AI Digest: Model Validation, Agents, and Generative AI
Seven visual lessons on testing models, recovering tool calls, speeding up text generation, detecting watermarks, and checking image and document…
Sep 7
•
Damien Benveniste
12
1
1
This site requires JavaScript to run correctly. Please
turn on JavaScript
or unblock scripts
