ExplainerAI in production
Microsoft UserRepGen makes inputs for a simulated user
UserRepGen turns a conversation into task and behavior descriptions. Follow the intermediate artifact through a synthetic support-assistant evaluation.
Articles
Guides, news and explanations about AI and reliable systems.
ExplainerAI in production
PulsarLM keeps context small by dropping old token pages
PulsarLM removes low-attention pages rather than summarizing them. A synthetic archive-retention case explains what a local agent’s recall trial must inspect.
GuideIncident response
Checking AI incident-summary citations with Python
Build a local, synthetic citation check that exposes wrong-version evidence while keeping interpretation, source freshness and action permission separate.
GuideAI in production
Hermes Agent guide: what it is, when to use it, and how to get started
Understand Hermes Agent, its origins, models, memory and skills. Choose a setup, try two checkable examples, and learn where its limits matter.
GuideAI in production
What is OpenRouter? A practical guide to choosing and using AI models
Understand the model marketplace and gateway, compare chat and API workflows, and choose a useful route through its models, providers, costs and privacy controls.
GuideAI in production
Model inference: what happens when you ask AI a question?
What a model does when you ask a question, how we got here, and how to choose between local and hosted inference without confusing fast text with useful work.
ExplainerAI in production
KoboldCpp 1.123 makes agent approvals depend on the tool and workdir
The global auto mode is only part of the permission decision. Follow per-tool overrides, directory scope and restored settings through a copied-runbook exercise.
ExplainerAI in production
Anthropic Scion puts source control behind a cache hierarchy
Scion reduces repeated repository work for online agents. Its cache hierarchy explains why warm checkout speed and fleet recovery need different tests.
GuideAI in production
What is OpenShell and how do I use it?
Run an AI agent with useful access to files and services, then test exactly where OpenShell stops it. A hands-on guide to sandboxes, policy, credentials, and SRE workflows.
ExplainerAI in production
AMD Helion separates agent execution from model inference
Helion places CPU agent loops, token routing, GPU inference and supporting services in separate capacity zones that still share one task outcome.
ExplainerAI in production
Muse Wonder's Active Memory needs an operational test
Test selective recall, corrected state, tool-failure recovery, clarification, and the independent destination result before trusting a long-running agent.
GuideAI in production
Measuring retry amplification in AI agent workflows
Connect logical tasks to every model and tool attempt, then measure cost and latency per accepted outcome without hiding failed or unknown work.