# PyYAML Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/pyyaml
> Markdown URL: https://aitinkerers.org/technologies/pyyaml.md
> Technology record last updated: 2026-05-18T01:37:07Z
> Generated: 2026-09-20T16:36:18Z

PyYAML is the essential YAML parser and emitter for the Python programming language.

PyYAML delivers a full-featured YAML framework for Python, supporting a complete YAML 1.1 specification and robust Unicode. It handles everything from complex configuration files (e.g., Ansible) to object serialization across platforms. Crucially, always use `yaml.safe_load()`: the default `yaml.load()` function is powerful, allowing arbitrary Python object construction, which poses a significant security risk with untrusted data. The latest stable version is 6.0.3 (as of late 2025), and the project operates under the permissive MIT License.

- Official technology site: https://pyyaml.org
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [From .md Dump to DAG: Rethinking Skills for Multi-Step Workflows](https://doha.aitinkerers.org/talks/rsvp_pXmYX7paZjs)

A new paradigm for Claude Code Agent Skills whose steps actually depend on each other. The current pattern - what every Skill on the market does- is dump a long SKILL.md into the agent's context and hope it follows the instructions in order. It mostly doesn't: the agent skips prereqs, hallucinates outputs that "look right," can't resume after /compact, and produces a different run every time you ask. ClawBio 2.0 replaces the hope with a contract: each skill ships a pipeline.yaml DAG, and a ~500-line CLI exposes start → next → open → done → bundle as the only legal moves. Instead of trying to read prose & remember, the agent calls CLI next, gets told exactly which step is unblocked, and is physically refused if it tries to skip ahead. State lives in one atomic state.json that survives /compact and /clear. Live I'll show: starting a multi-step run, the CLI rejecting an out-of-order step, the agent recovering cleanly from a forced /clear, and the reproducibility bundle (commands.sh + checksums + env) that a Stop hook refuses to let the agent skip. Bioinformatics is just the testbed - the pattern is for any skill where order matters and outputs feed inputs.

- Event context: AI Tinkerers – Doha Inaugural Meetup — 2026-05-18 — Doha
- Public talk page: https://doha.aitinkerers.org/talks/rsvp_pXmYX7paZjs

### [Encoding Regulation: A Minimal Policy-as-Code Engine for Transaction Screening](https://bremen.aitinkerers.org/talks/rsvp_QUe96TzohsM)

I will demo a small policy-as-code engine I built to explore how regulatory rules can be expressed as executable logic. The system takes human-readable YAML rules (e.g., thresholds, jurisdictions, prohibited transaction types), parses them into an internal structure, and evaluates each incoming transaction through a deterministic constraint pipeline. The core of the demo is the implementation: the rule parser, the abstract syntax tree used to normalise heterogeneous conditions, and the evaluator that resolves multiple matching rules into a single “allow/block/flag” decision. Instead of slides, I will walk through the code that loads rules, interprets conditional operators, handles conflicts, and surfaces intermediate evaluation steps. I’ll also show a tiny sandbox where modifying a rule immediately changes system behaviour, illustrating how policy logic propagates through the engine. The goal is not to pitch a product but to share the technical challenges of translating messy institutional rules into a minimal, functioning execution model.

- Event context: AI Tinkerers Bremen — 2025-12-10 — Bremen
- Public talk page: https://bremen.aitinkerers.org/talks/rsvp_QUe96TzohsM

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