Software factories and agent swarms, from coding teams to banks, manufacturers and research labs. Explore how the work gets done, how widely these systems are used, and what the numbers mean.
A practical guide to combining bounded production lines, Huntley's embedded Ralph loop, and Yegge's multi-agent work graph.
Read the field analysis
A personal manifesto about building more software by improving the system around coding agents.
The details that make each approach work: its tools, feedback, division of labor and review.
A trading firm's approach to coding agents puts the development environment and the quality of feedback at the center of the story.
Read the caseAn employee delegates once. Minions prepares a development computer, changes code, runs checks, and returns the result for two stages of human review.
Read the caseEmployees work with River in shared Slack threads. Shopify's Aquifer design keeps the work history separate from temporary computers so sessions can survive interruptions.
Read the caseCompare the work, the scale and the evidence. Software development is the starting point; operations and research widen the picture.
Find a relevant workflow and compare its implementation, review and public evidence.
Inspect reported worker counts, runs, output and adoption, with the units and limits beside each number.
Follow the uses emerging in finance, automotive software, industrial planning and scientific research.
Clear explanations for understanding a proposal, planning an experiment or judging its results.
A plain-English guide to the people, agents, checks, and learning loop behind an AI software factory.
How requests reach agents, how results are checked and released, and how the team learns from the work. A practical map of the system around the model.
Choose a recurring job, compare it with today's process, prepare the agent's tools and tests, and measure what it takes to deliver an accepted result.
Five numbers for judging speed, rework, quality, human attention, and the real cost of AI-assisted delivery.
Built by
SWFT is built and published by Ben Guo, a musician and builder, formerly a founder and engineering leader at companies including Venmo and Stripe, now building from Puerto Rico. He publishes it through Hraness as an independent, free-to-read project. The guides and company cases are AI-drafted by SWFT Editorial and labeled as such; his own essay carries his byline.
