#workflow
workflow shows up across 3 section(s) and 17 page(s) in this workspace. Use this page as a topic map, not just an archive.
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If you are new to this topic, begin with the strongest entry points first, then move into related notes and supporting material.
- AI Agents vs AI Workflows Systems
- Agent Instructions and Handoff as an Operating System Systems
- Designing Reusable AI Skills Systems
- Evaluation as a Runtime Discipline Systems
Where it appears
- Systems 8 page(s)
- Shelf 8 page(s)
- Sticky Notes 1 page(s)
AI Agents vs AI Workflows
A practical explanation of the difference between autonomous-seeming agents and controlled workflows, and why the distinction matters in production systems.
Agent Instructions and Handoff as an Operating System
A practical architecture for running AI agents reliably using instruction contracts, handoff memory, and measurable quality gates.
Designing Reusable AI Skills
How to design AI skills with clear boundaries, input and output contracts, tool limits, side-effect controls, and escalation paths.
Evaluation as a Runtime Discipline
Why evaluation should live inside the operating loop of an AI system instead of being treated as an occasional review ritual.
From Ad-Hoc Prompts to Repeatable Agent Workflows
A practical case study showing how structured instructions, handoff memory, and quality gates improved consistency and coverage in this repository.
Skill Evaluation and Versioning
How to define expected behavior, detect regressions, version skill changes safely, and decide when rollback is the right move.
Skills vs Prompts vs Agents
A systems-level comparison of prompts, skills, workflows, and agents so teams can stop mixing up instruction surfaces with execution architecture.
What a Skill Is in AI Systems
A practical definition of skills as reusable execution units that sit between prompts and workflows in modern AI systems.
Ollama launch: integration handoff
A new launcher flow that hands local models into tools like Codex and OpenCode.
Notes: Knowledge Surface Weekly Map
A weekly pass format for keeping note structures coherent, linked, and retrieval-ready.
Notes: Observability Logbook Pattern
A compact weekly review format for tracing decisions, evidence, and outcomes in AI workflows.
Notes/Tools: a daily Obsidian scratchpad
One file per day, minimal structure, and a quick export habit.
Notes/Tools: a plaintext logbook
Short markdown logs + ripgrep to keep the archive searchable.
Tools: Git
The simplest way to keep experiments honest and reversible.
Everything as Code deck
A control-plane framing where policy, infrastructure, workflows, and quality checks become versioned artifacts.
AI skill design templates
Three compact templates for defining, reviewing, and composing AI skills as reusable execution units.