Build a Software Factory That Actually Works
A practical software-factory blueprint for parallel coding agents: isolate work, build to explicit architecture, prove behavior with evidence, and ship through review loops.
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Library · Full Archive
AI Automation
AI Automation
Case Study Archive.
Every case study, system breakdown, and field note, newest first and filterable by topic. No theory, no demos. Only systems that run in production and what it took to get them there.
At a glance
What is in the JQ AI SYSTEMS case study archive?
This is the complete archive: all 478 posts across 52 topics, newest first, filterable by category. It holds the case studies, the model and tool comparisons, and the field notes from systems I built and run. For the curated view, where the writing sits alongside the free Claude Code skills, start at the Library instead.
The archive leans in four directions: AI Search Visibility (95), AI Agent Architecture (58), AI Tools (38), and AI Coding Agents (26). Those four account for most of what I publish, because they are where most of the client questions land.
Three places to start. The AI search visibility guide is the hub for the largest cluster and links out to every spoke in it. Grok Imagine vs Midjourney is the image model comparison, rebuilt against live leaderboard data rather than left to go stale. OutreachIQ is the longest running system breakdown here, from first prototype through to a public repo.
Can an AI Agent Compare Your Offers Correctly After a Pricing Change?
Test service-package changes with approved offer facts, fixed buyer questions, evidence capture, and regression checks for prices, currencies, scope, and exclusions.
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Herdr Crash Course: Run AI Agents in Persistent Terminals
A practical guide to Herdr workspaces, tabs, panes, persistent sessions, VPS access, agent tracking, CLI automation, and the official Herdr skill.
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How to Run an AI Agent Workforce Without Losing Control
Allie K. Miller's 34-agent system rebuilt as a practical guide to goals, context, fixed risk tiers, watchdogs, model routing, and reusable factories.
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Personal AGI for Founders: Build a System You Own
Garry Tan frames personal AGI as owned context, reusable skills, and agent infrastructure. Here is the architecture, security model, and 30-day build plan.
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Agent Plugins: One Portable Format for Skills and MCP Servers
The official Agent Plugins standard explained: root plugin.json, portable Agent Skills, MCP configuration, client support, migration, and security boundaries.
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Hyperagent in Slack: Build AI Teammates Your Team Will Use
Andrew Warner and Alex McDonnell demonstrate a Hyperagent sales team inside Slack. Here is the architecture, approval model, shared-memory risk, security history, cost boundary, and safer rollout.
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Install a Local AI Stack With ODS: One Command, Six Apps, and the Caveats
Andrew Warner and Mike Bradley install ODS on Windows. Here is what the local AI stack includes, what stays private, the real hardware tiers, and a safer setup path.
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Traycer Multi-Agent Test: Can Fable 5 Make a Local Qwen 27B Better?
Bijan Bowen pairs Fable 5 with local Qwen3.6 27B in Traycer. Here is what improved, failed, and the solo baseline revealed about multi-agent orchestration.
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Graph Engineering for Claude and Codex: Turn One Giant Chat Into a Managed Workflow
Greg Isenberg's framework rebuilt as a practical guide to jobs, arrows, shared state, parallel research, checks, loops, and human approvals.
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Buzz Did Not Solve Multi-Agent Orchestration. It Solved Agent Identity.
Josh Pocock stress-tests Buzz and exposes the gap between a shared agent workspace and dependable orchestration. Here is what Buzz really solves, what the demo broke, and the controls a production agent team still needs.
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Scrapling for AI Agents: How One Creator Cut 215K Tokens to 3K
Kacper Rutkiewicz tests Scrapling across targeted web extraction, prospect research, and design synthesis. Here is the source-checked setup, the real token math, the fetcher decision tree, and the legal and security boundaries his workflows need.
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How to Build a No-Code AI Agent Team With Hyperagent
Vaibhav Sisinty builds a reusable specialist, a delegated startup team, and a scheduled analyst in Hyperagent. Here is the practical no-code setup with prompts, permissions, costs, rubrics, and approval gates.
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Build a Buzz Agent Team With Codex and Claude Code
Riley Brown and Vince Canger show how to build a practical Buzz agent team with Codex as the lead, Claude Code and other runtimes as specialists, scoped channels, review loops, mobile access, and safer recurring workflows.
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Buzz Agent Workspace: Build, Deploy, and Automate With an AI Team
Andrew Warner and Vince Canger test Buzz across agent runtimes, Wasp and Railway deployment, mobile access, Git projects, workflow triggers, shared compute, and multi-agent routing. Here is the practical operator guide.
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ChatGPT Work vs Claude Cowork: The Practical No-Code Comparison
Vaibhav Sisinty tests ChatGPT Work and Claude Cowork across projects, scheduled tasks, connectors, recorded skills, Slack, Sites, Artifacts, and local work. Here is the current, source-checked comparison.
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Buzz Is More Than a Slack Alternative: Portable Context for AI Teams
Greg Isenberg and Vinny tour Buzz, Block's open agent workspace. The real opportunity is portable team context across Claude Code, Codex, Goose, Git worktrees, workflows, and local compute, with important early-preview limits.
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How to Build a Marketing Agent That Learns From Revenue
Cody Schneider and Greg Isenberg map a real Meta Ads agent: unified business data, research and creative pipelines, bounded API actions, and a feedback loop tied to revenue.
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How to Manage a Team of AI Agents: Ryan Carson's Cloud Software Factory Playbook
Ryan Carson explains how he runs parallel cloud agents, recurring production checks, self-improvement loops, and model routing. This guide turns the interview into a controlled agent-operations system.
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Buzz AI Teams Reviewed: Self-Hosted Agents, Shared Compute, and the Slack Test
Block's Buzz puts people, Claude Code, Codex, and other agents in one Nostr workspace. Here is the architecture, privacy reality, chief-of-staff pattern, shared-compute risk, and honest Slack comparison.
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Tasklet vs OpenClaw and Hermes: Inside Ari Meisel's AI-First Business
Ari Meisel shows how Tasklet agents coordinate website optimization, knowledge, content, support, and personal tasks. Here is the architecture, full toolkit, shadow-mode rollout, and the controls the demo still needs.
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Hermes Agent + GPT-5.6 Sol: Setup, Reasoning Level, Real Workflows
Run GPT-5.6 Sol inside Hermes Agent: the verified Codex OAuth setup, how to pick reasoning effort, three bounded workflows, and the safety controls to keep.
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Tokenmaxxing Is Not an AI Strategy: How to Cut AI Costs Without Cutting Results
Vaibhav Sisinty explains why token consumption is becoming a business cost problem. Here is the source-checked playbook: measure cost per successful task, route models, cache correctly, trim context, set limits, and decide when local inference pays.
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Loop Engineering for Business: AI Agents That Improve SEO, Ads, and Product Feedback
Greg Isenberg and Elie Steinbock explain how loop engineering can improve SEO, ads, and product feedback. Here is the practical architecture: objective metrics, memory, budgets, verification, schedules, and stop conditions.
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