Subject
20 entries
Workflow
Bookmarks
Fabro: AI agent workflow graph orchestrator
Fabro defines AI agent workflows as Graphviz DOT graphs with git checkpointing, cloud sandboxes, and human-in-the-loop gates. It occupies the space between micromanaging an agent line-by-line and blindly accepting a 500-line diff.
Claude Interactive Documentation Workflow: markdown before code
A structured interview-to-implementation workflow using Claude Code: document first, then code. The methodology produces specs that keep LLMs guardrailed and documentation that doesn't require clarifying questions.
Jujutsu For Busy Devs: Practical Intro to jj
A pragmatic intro to Jujutsu (jj), the new version control system that's git-compatible but fixes many of git's ergonomic frustrations — written for developers who don't have time for a deep-dive. jj's working-copy-as-a-commit model and first-class conflict handling make it worth adopting.
Sim Studio: Visual Agent Workflow Builder
Sim Studio is an open-source visual agent workflow builder — connect LLMs, tools, and vector stores on a canvas, then deploy immediately. An AI copilot generates nodes and fixes errors from natural language, and 1000+ integrations are supported.
Writing in Obsidian and Publishing Instantly
A workflow for writing in Obsidian and publishing to a blog instantly — using iCloud sync for cross-device drafting (phone to laptop), the Minimal theme for distraction-free writing, and a pipeline that converts vault notes to published posts. The local-first model is the key advantage.
The Workflow Pattern
A blog post describing the Workflow Pattern — an architectural pattern for modeling multi-step business processes as explicit state machines rather than tangled procedural code. Argues that making workflow state explicit and persistent improves reliability, observability, and testability.
Git Organized: A Better Git Flow
A simple git workflow improvement: make changes freely on a branch with WIP commits, then git reset to the branch point and recommit in logically grouped chunks before opening a PR. Separates the messy work of development from the clean artifact of a review-ready commit history.
Data Science Project Lifecycle Infographic
A visual reference guide covering the full data science project lifecycle from problem framing through deployment. Practical one-pager for practitioners needing a structured reminder of pipeline phases.
Flowy: The Simple Flowchart Engine
Flowy is a minimal JavaScript library for creating drag-and-drop flowchart UIs in the browser — designed to be embedded in web apps, not as a standalone tool. Lightweight alternative to React Flow or jsPlumb for simple workflow builder features.
Approaching (Almost) Any Machine Learning Problem
Abhishek Thakur's systematic framework for tackling any supervised ML problem — from data cleaning and feature engineering through model selection and stacking. One of the most-shared practical ML workflow guides from the Kaggle blog era.
Git Pretty — Recovery Flowchart
Justin Hileman's flowchart for deciding which git command to run when you're in a mess — a decision tree that starts with 'did you push?' and branches into the right cleanup command. The most-shared git recovery reference of its era.
Why is
Stack Overflow thread on why git pull creates problems in divergent branches — advocates for git pull --rebase or a fast-forward-only alias instead. A workflow habit that eliminates unnecessary merge commits from shared history.
Why You Should Be Spot-Checking Algorithms on Your Machine Learning Problems
Jason Brownlee's Machine Learning Mastery argument for spot-checking — trying 10-15 algorithms quickly on a new dataset before committing to tuning any single one. Saves time by letting the data tell you which algorithm families are worth investing in.
Git Tips from the Trenches
A practitioner's collection of git tips beyond the basics — covering aliases, bisect, stash, reflog, and workflow patterns learned from actual team use. The kind of git knowledge that only comes from running into the same problems repeatedly.
Data Analysis Architecture Workflow Diagram
VentureBeat/DataBeat data analysis architecture diagram circulated on Twitter in 2013 — a workflow schematic showing the layers of a big data pipeline from collection through analysis to visualization. Snapshot of how practitioners were thinking about data infrastructure.
Six Steps in Data Science
A 2013 blog post laying out six practical steps in a data science workflow — from problem framing through data collection, exploration, modeling, evaluation, and deployment. A snapshot of how practitioners were thinking about the discipline before MLOps and production ML tooling matured.
Improving Your Python Productivity
Oz Katz's guide to Python productivity improvements — covering virtual environments, IPython, better REPL workflows, and tooling choices. A 2012-era reference that established many practices still standard today.
Legit: Git Workflow for Humans
Legit is a Python-based git extension by Kenneth Reitz that wraps git branch management in more human-friendly commands. It fills a real gap: git's branch model is powerful but the command interface is notoriously user-hostile.
Modern Web Development, Part 1
Jamil Taber's 2012 post on modern web development practices — covering the emerging toolchain of Git, package managers, testing, and JavaScript frameworks that were redefining what 'professional' front-end development looked like.
GTDFH: Getting Things Done for Hackers
GTD for Hackers adapts David Allen's Getting Things Done methodology for command-line-oriented developers — plain text files, version control, and shell scripts instead of dedicated GTD apps. An attempt to bring systematic personal productivity into the terminal workflow where developers already live.