# YAML Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/yaml
> Markdown URL: https://aitinkerers.org/technologies/yaml.md
> Technology record last updated: 2026-02-24T00:35:05Z
> Generated: 2026-09-23T05:39:50Z

YAML (YAML Ain't Markup Language) is a human-friendly data serialization language prioritizing readability and ease of use.

YAML is a human-readable data serialization language, primarily used for configuration files and inter-process data exchange. It employs a minimal, indentation-based syntax (like Python) to define structure, utilizing colons for key-value pairs (mappings) and hyphens for list items (sequences). YAML is a superset of JSON, offering key benefits like support for comments and reusable data references (anchors). This clarity and feature set make it the standard for major DevOps tools, including Kubernetes deployments and Ansible Playbooks.

- Official technology site: https://yaml.org
- Public AI Tinkerers demos and talks: 11
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Nika - Intent as code](https://paris.aitinkerers.org/talks/rsvp_6XBmEC8IoVA)

Nika is an open source workflow language + Rust engine where AI pipelibe is a siNGle YAML file woth 4 verb

- Event context: Offstage w/ Docker feat ClickHouse — 2026-07-07 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_6XBmEC8IoVA

### [Building an AI publishing platform with an AI dev squad](https://tokyo.aitinkerers.org/talks/rsvp_CzSJETAJ9-4)

CloudAuthor — a full-stack AI authoring platform, 14 agents, 27 skills, 300+ tests, built in 2 months on .NET Aspire and TypeScript/Vite. Live demo in two halves. First, I'll run the end-to-end publishing pipeline through CloudAuthor's agents: ideation → research → quote-finding → drafting → editing → banner creation → Japanese translation → carousel generation. Each stage is a specialized agent handing off to the next, all streaming in front of you. Then I'll switch to Visual Studio Code and show the squad of 7 specialized coding agents I actually use to build CloudAuthor itself — the agents that wrote the agents.

- Event context: AI Tinkerers Tokyo - Shinagawa: May 26th Meetup — 2026-05-26 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_CzSJETAJ9-4

### [Agents require executive function](https://toronto.aitinkerers.org/talks/rsvp_8my42K3UIdc)

I'm building out an open source YAML specification for agent orchestration. Based on a hundred years of human cognitive science, the metaphor is the construction of an artificial Neocortex. Specifically working on improving executive function in agents.

- Event context: AI Tinkerers Toronto - April 2026 - hosted by Shopify — 2026-04-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_8my42K3UIdc

### [Docker Sandboxes](https://paris.aitinkerers.org/talks/rsvp_q-ziE0PuCC8)

AI is everywhere and easier to use. We think it can be even simpler. With AI, we either write a prompt, use a pre-built agent, or code complex agents. We think there's room for ad hoc agents written in seconds, without code. Why? Because AI is often useful for tasks never seen before, and it's a superpower to assemble models, prompts, and tools into a team of agents created for that task.

- Event context: AI Tinkerers Paris: Docker Agentic Workflows (Devoxx Kickoff) — 2026-04-21 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_q-ziE0PuCC8

### [Docker Agent: Simplifying AI Agent Creation](https://paris.aitinkerers.org/talks/rsvp_5hoKr2cgNMw)

AI is everywhere and easier to use. We think it can be even simpler. With AI, we either write a prompt, use a pre-built agent, or code complex agents. We think there's room for ad hoc agents written in seconds, without code. Why? Because AI is often useful for tasks never seen before, and it's a superpower to assemble models, prompts, and tools into a team of agents created for that task.

- Event context: AI Tinkerers Paris: Docker Agentic Workflows (Devoxx Kickoff) — 2026-04-21 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_5hoKr2cgNMw

### [Docker Agent: Simplifying AI Agent Creation](https://paris.aitinkerers.org/talks/rsvp_QMDTiAwXhfE)

AI is everywhere and easier to use. We think it can be even simpler. With AI, we either write a prompt, use a pre-built agent, or code complex agents. We think there's room for ad hoc agents written in seconds, without code. Why? Because AI is often useful for tasks never seen before, and it's a superpower to assemble models, prompts, and tools into a team of agents created for that task.

- Event context: AI Tinkerers Paris: Docker Agentic Workflows (Devoxx Kickoff) — 2026-04-21 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_QMDTiAwXhfE

### [Evaluation-Driven Skill Development](https://nyc.aitinkerers.org/talks/rsvp_kRiiAXuZymg)

Live demo of skillet, an open-source framework for developing Claude Code skills through evals. I'll walk the full loop: capture a failure as a YAML eval, run an evaluation baseline, generate a skill, then auto-tune it until it passes.

- Event context: March Demo Day, hosted by Flowglad — 2026-03-18 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_kRiiAXuZymg

### [rm -rf salesforce — Claude Runs Deal Flow Now](https://seattle.aitinkerers.org/talks/rsvp_qa7m-04lrlg)

I built a git-backed knowledge base that replaces both my CRM and Google Docs for running an early-stage fund. Every entity — founders, companies, deals — lives as a folder of markdown and YAML. Claude agents are first-class participants: they process inbound emails, run entity resolution, create records, log notes, and commit directly to the repo. A GitHub Actions cron runs nightly, calling Claude Sonnet to synthesize each entity's raw files into a structured materialized summary. I'll demo the full live workflow: forward a pitch email → agent resolves the entity → creates the records → generates a materialized view → commits to git. No database. No SaaS. Just files, Claude, and git.

- Event context: AI Tinkerers Seattle: GTM Engineering Kickoff — Building AI for Growth — 2026-02-26 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_qa7m-04lrlg

### [Custom Self Improving Subagents with Claude Code](https://seattle.aitinkerers.org/talks/rsvp_Hc7X3ifdjnw)

Most Claude Code setups are static—your agents do the same thing every time. But what if they could learn from their own execution? In this talk, I'll demo a self-improving subagent architecture running in Claude Code that uses a plan→build→improve cycle where agents update their own knowledge after every workflow, maintains expertise.yaml files (500-1000 lines per domain) that evolve based on real execution patterns, and shares learnings across domains via a collective knowledge registry so when one agent discovers something, all agents can benefit. Live demo: I'll show agents improving themselves in real-time, including the .shared/ folder pattern for cross-domain knowledge propagation.

- Event context: AI Tinkerers Seattle Meetup: Dev Tools Track — February 9th, 2026 — 2026-02-10 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_Hc7X3ifdjnw

### [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

### [Microsoft Agent Framework Accelerator](https://dubai.aitinkerers.org/talks/rsvp_RzTHaRY6k-0)

Showcasing how the open-source accelerator built on Microsoft Agent Framework enables rapid, low-code creation of multi-agent systems via YAML configuration and plugin-based tool discovery. The talk will cover architecture, demo (tool definition → agent definition → workflow orchestration), and how users can adopt it in their projects.

- Event context: AI Tinkerers Dubai Demo Day - November 15, 2025 — 2025-11-15 — Dubai
- Public talk page: https://dubai.aitinkerers.org/talks/rsvp_RzTHaRY6k-0

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