GuideAI in production
What are model weights, and how does training change them?
Follow a weight through a training update, save a tiny model, and learn how checkpoints, fine-tuning, LoRA and held-out evaluation fit together.
Articles
Guides, news and explanations about AI and reliable systems.
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.
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.
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.
GuideAI in production
Build an inference compatibility suite before changing the runtime
Pin the model artifact, template, runtime and hardware, then exercise fixed protocol tests and preserve raw differences before approving a serving change.
GuideAI in production
Auditing AI-generated tests and documentation before cleanup
Review the claim each test or document protects, challenge the evidence, and record a keep, rewrite or retire decision before deleting repository history.
GuideObservability
Shadow-testing an AI log classifier before migration
Run a candidate log classifier beside the current route, preserve complete outcomes, and promote only the slices whose mistakes and review cost are understood.
GuideObservability
Measuring streaming LLM latency from first text to completed work
A client-side SSE probe separates first answer text from normal completion. Fixed arrivals and outcome counts show whether a serving change delivers more useful answers.
GuideAI in production
Instinct: from a text or call to a confirmed task
Instinct brings personal tasks into connected services. A hypothetical booking and notification worker show how permission, provider confirmation and uncertain results affect what happens next.