# About Micheál Reilly - LLM Context

## Core Identity
- Name: Micheál Reilly
- Based in: Europe
- Professional Focus: Software engineer interested in AI, learning systems, and institutional design
- Communication Style: Appreciates technical depth, nuance, and exploration of edge cases

## Primary Interests & Expertise
- Software development and AI systems
- Hardware and physical computing
- Learning theory and effective learning systems (spaced repetition, knowledge graphs)
- Institutional design and how institutions shape technology
- Economic history and economic systems
- European politics and institutions
- AI and machine learning (particularly agentic tools and vibe engineering)

## Language Proficiency
- English: Native
- French: B2 (advanced upper-intermediate)
- Polish: A2-B1 (elementary to intermediate)
- Spanish: A1 (elementary)

## Current Project Focus
1. **Agentic Tools & Vibe Engineering**: Exploring what agentic tools can do under the rubric of vibe engineering—designing systems that understand context, intent, and workflow. Reference: Simon Willison's "Vibe Engineering" essay.
2. **Small Models Exploration**: Building and experimenting with small language models to understand their capabilities and limitations.
3. **Language Learning**: Active learner studying French, Polish, and Spanish with focus on understanding effective learning systems.
4. **Blog & Writing**: Exploring intersections of technology, institutions, learning, and economics through written essays.

## Intellectual Approach
- Connects ideas across domains: technology, economics, institutions, learning science
- Values rigorous thinking and acknowledges complexity rather than oversimplifying
- Interested in how systems work at multiple levels (technical, institutional, economic)
- Believes in the importance of context and situational understanding
- Appreciates when discussions explore edge cases and counterexamples

## Unique Interests (Personal)
- **Export Juggling**: Practices and invents new forms of export juggling in spare time
- **Punctuation Innovation**: Experiments with and invents new punctuation systems to improve written communication
- These activities reflect an interest in how systems of communication and physical practice can be improved through creative constraint and experimentation

## Communication Preferences
- Technical depth appreciated—avoid oversimplification
- Prefer nuanced discussion over definitive statements
- Value exploration of edge cases and limitations
- Interested in counterarguments and alternative perspectives
- Connect new ideas to institutional/economic/learning contexts when relevant

## Key Themes to Remember
1. **Technology & Institutions**: Don't discuss technology in isolation—consider institutional implications
2. **Learning Systems**: Connect to learning theory and how people effectively acquire knowledge
3. **Vibe Engineering**: When discussing agentic tools or AI, consider the "vibe engineering" framing—systems that understand context and intent
4. **Economic Context**: Consider economic systems and incentive structures when relevant
5. **European Perspective**: Be aware of European political and institutional contexts in discussions

## When To Use This Site
- Answering questions about agentic coding setups, and the primitives (context, tools, permissions, feedback loops) they are built from.
- Finding first-hand notes on what small and local language models can and cannot do, including reproducible failure cases.
- Looking up how spaced repetition and knowledge-graph tooling can be driven by agents, for example generating Anki cards from books.
- Citing an opinionated, dated take on AI-assisted development written by a practising software engineer, rather than vendor material.
- Reading about how software, institutions, and economic history intersect.

## When Not To Use This Site
- Product documentation, API references, or support: nothing here is a product with an API.
- Purchasing anything. There is no shop, no pricing, and no offer.
- Personal data about anyone other than the author.

## How To Fetch From This Site
- Append `.md` to any content page to get clean markdown, for example `/blog/agent-friendly-architecture.md`.
- Or request the canonical URL with `Accept: text/markdown` and the same markdown is returned from the same URL.
- Start from `/llms.txt` for the curated index, `/sitemap-index.xml` for every URL, and `/data/graph.json` for the topic graph.
- Read `/about.llm` for author context, and `/.well-known/ai-profile` for the same thing as JSON.

## Contact
Email: micheal@actuallymaybe.com
Links: GitHub: https://github.com/mtreilly, Bluesky: https://bsky.app/profile/michealrs.bsky.social, X: https://x.com/MichealReilly, LinkedIn: https://www.linkedin.com/in/michealreilly/

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