---
title: "The Agentic Software Factory"
section: "raw"
type: "source"
created: "2026-08-27"
updated: "2026-08-27"
canonical: "https://pyweb.dev/wiki/raw/articles/hugo-bowne-anderson-agentic-software-factory-2026"
---
# The Agentic Software Factory

By Hugo Bowne-Anderson (featuring Wes McKinney, Jeremiah Lowin, and Randy Olson on *Show Us Your Agent Skills*).

## Vibe Coding vs. Agentic Engineering

> "The difference between vibe coding and agentic engineering is planning, architecture, and caring about the output." — Wes McKinney (riffing on Jesse Vincent).

When producing software at scale (e.g. 1M lines of generated code over 6 months across roughly a dozen projects at 1.3 to 1.4B tokens a day), human line-by-line review breaks down entirely. The developer's role shifts to making structural decisions about scope, architecture, and constraints, while automated systems read the code.

## Verification Stack in Practice (Wes McKinney's Harness)

1. **Slow Plan, Long Implement:** Detailed spec interviews (e.g. via Superpowers) before implementation. Implementation runs over git worktrees for hours across dozens of tasks.
2. **Commit Every Turn:** Hard requirement in AGENTS.md/CLAUDE.md for fine-grained reviewer triggers and immutable checkpoints.
3. **Automated Continuous Review (RoboRev):** Post-commit hook firing automated code review through Codex (GPT-5.5 / high reasoning) on every commit. Findings accumulate in a per-repo ledger; code is read 4-5 times by agents before human merge consideration.
4. **Local Tooling Ecosystem:** Kata (local issue tracker), Middleman (local PR review interface), and Agents View (session search across hundreds of agent traces).

## Generator-Evaluator Loops & Self-Grading Skills

Randy Olson demonstrates encoding visual and domain judgment into self-evaluating skills where the agent critiques its own output against explicit aesthetic and structural rubrics before submitting.

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## Agent Navigation

### Machine endpoints
- Knowledge graph: https://pyweb.dev/api/graph.json
- Graph analysis: https://pyweb.dev/api/graph-analysis.json
- Context index: https://pyweb.dev/llms.txt