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Merge pull request #3 from recursionlab/content/initial-pages
Merging seed content PR to publish About and Projects pages.
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.github/workflows/jekyll-build.yml

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name: Jekyll Build
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on:
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pull_request:
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push:
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branches: [ main ]
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Ruby
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uses: ruby/setup-ruby@v1
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with:
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ruby-version: '3.2'
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- name: Install dependencies
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run: |
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gem install bundler
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bundle config set --local path 'vendor/bundle'
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bundle install --jobs 4 --retry 3
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- name: Build site
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run: bundle exec jekyll build --trace
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- name: Upload site (artifact)
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uses: actions/upload-artifact@v4
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with:
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name: site
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path: _site

ARCHITECTURE.md

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# Architecture Notes — Recursion Lab
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This file distills a short Architect Guide for module authors who want to design and manage whole projects.
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Principles
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- Encapsulate intent: module boundaries should reflect responsibilities and invariants, not only file layout.
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- Standardize interfaces: use explicit, stable contracts (schemas or API specs).
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- Observability from the start: logs, traces, and metrics make integration problems visible.
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- Design for graceful failure: define how modules degrade and recover.
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- Evolve safely: version contracts and provide deprecation paths.
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Quick checklist
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- One-line ownership for each module (who owns what).
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- Explicit contract for each integration (inputs, outputs, errors).
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- Failure modes documented and practiced.
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- Integration tests in CI (contract tests and a small end-to-end smoke test).
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- Observability: structured logs + a couple of business metrics for key flows.
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Mini example (blog)
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- Content API owns canonical content and emits `content.updated` events.
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- Admin UI talks to Content API synchronously for editing flows.
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- Search service subscribes to events to index content asynchronously.
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- CDN serves static builds; preview mode reads content directly for staging.
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Practical next steps (minimal edits you can do now)
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- Add one-sentence ownership lines to module READMEs.
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- Add a contract checklist entry to PR templates (if you have them).
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- Ensure CI runs the Jekyll build (already present) and add a smoke test for a public route.
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If you want, I can convert this into a more detailed `ARCHITECTURE.md` with diagrams, or add a small PR template and a README checklist. For now this is kept minimal so you can add your content later.

README.md

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- Base theme sparrow by [lingxz](https://github.com/lingxz/sparrow)
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- Icon made by [Freepik](https://www.freepik.com/) from www.flaticon.com
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## Local development
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To preview the site locally you can use Bundler and Jekyll. From the repository root run:
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```bash
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# install gems
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bundle install
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# build the site and serve locally
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bundle exec jekyll serve --livereload
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```
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Open http://127.0.0.1:4000 in your browser to preview changes. When creating posts, add files to `_posts/` with a filename like `YYYY-MM-DD-title.md` and appropriate front matter.
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See `_qa/pagination-snippet.txt` for a quick build verification note I added earlier.
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### Drafts
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Place in-progress posts in the `_drafts/` folder (no date in filename). To preview drafts locally, run:
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```bash
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bundle exec jekyll serve --drafts --livereload
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```
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---
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title: "Case Study: Emergent Recursive Cognition"
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author: Recursion Lab
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tags: [case-study, emergence]
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---
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Reported experiments (e.g., OnToLogic V1.0) where recursive loops produced unexpected behaviors.
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- What worked / what didn’t
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- Lessons and reproducible setups
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Draft notes:
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- Setup and assumptions
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- Observed behaviors and metrics
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- Failure analysis and iteration plan
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---
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title: "The Interface Between Mind and Recursive Systems"
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author: Recursion Lab
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tags: [cognition, systems, interaction]
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---
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How interacting with recursive AI/systems changes the way people think.
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- Cognitive reshaping, adaptation, feedback
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- Case references to discuss (e.g., observation effects)
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Draft notes:
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- Interaction patterns (what users see, how they adapt)
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- Risks (overtrust, loop amplification)
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- Design implications (affordances, transparency)
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---
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title: "Recursive Reasoning in Language Models"
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author: Recursion Lab
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tags: [llm, recursion, prompting]
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---
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How LLMs currently do recursion (prompts, self-critique, looped tasks)
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- Pitfalls & limits (hallucinations, coherence collapse)
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- Best practices / experiments
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Draft notes:
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- Prompt patterns (plan → draft → critique → revise)
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- Tooling patterns (scratchpads, checklists, verifiers)
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- Metrics and failure cases
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---
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title: "What Is Symbolic Recursion and Why It Matters"
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author: Recursion Lab
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tags: [recursion, cognition, ai]
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---
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Define symbolic vs. syntactic recursion.
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- Examples from cognition, prompt engineering, and AI
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- Implications: self-reflection, emergent behavior, memory
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Draft notes:
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- Working definition(s)
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- Short examples (language, programs, representations)
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- Where it breaks or misleads
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- Open questions

_pages/projects.md

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---
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title: Projects
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layout: page
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permalink: /projects/
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---
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## Projects
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This page lists prototype ideas exploring recursive systems. Replace or expand these with your own projects as they evolve.
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### Recursive Self-Reflection Engine
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- Goal: Prototype a system that self-evaluates outputs, detects contradictions, and regenerates improved responses.
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- Sketch: Combine a language model with lightweight symbolic rules to create a feedback loop for critique → revise → verify.
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- Notes: Inspired by work on emergent recursive cognition via language-encoded symbolic systems. Add links and code when available.
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### Recursive Reasoning Tools for LLMs
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- Goal: Build tools or prompt frameworks that enforce recursive reasoning (multiple passes with critique and revision).
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- Sketch: Design a reusable protocol (plan → draft → critique → revise) and measure quality gains on target tasks.
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- Notes: Start with prompt-only approaches; evolve into lightweight libraries if useful.
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### Visualization of Feedback Systems
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- Goal: Create visual/interactive models of recursive systems from biology, cognition, or social domains.
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- Sketch: Show how loops amplify, stabilize, and collapse; let users tweak parameters to see phase changes.
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- Notes: Consider small web demos or notebooks.
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### Cognitive Architecture Comparisons
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- Goal: Compare architectures (e.g., CLARION and others) to locate where explicit vs. implicit recursion plays a role.
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- Sketch: Build small simulations to highlight differences in learning and control loops.
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- Notes: Collect references (papers, Wikipedia) and plan a minimal, comparable benchmark.

_posts/2025-09-14-welcome.md

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---
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title: "Welcome — Recursion Lab"
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date: 2025-09-14 09:00:00 +0000
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author: Recursion Lab
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tags: [welcome, meta]
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---
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This is the first post on Recursion Lab. Replace this content with your own writing, sketches, or notes. Posts live in the `_posts/` folder — their filename controls their published date and URL.
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Write in Markdown, set front matter variables (title, date, tags), and push to `main` or open a PR.

about.md

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---
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title: About
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layout: page
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permalink: /about/
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---
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## About
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Recursion Lab studies the interplay of recursion, cognition, and systems. We publish public notes and working prototypes that test ideas about feedback, self‑reference, and emergent behavior.
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We believe recursion is a core mechanism — in learning, in feedback, and in self‑reference. Through notes, experiments, and open-source prototypes we explore:
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- How recursive architectures enable emergent cognition
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- How biological, computational, and social systems stabilize via feedback loops
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- What happens when recursion is applied to meaning, memory, and identity
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This site is a research‑and‑prototype space. Browse the Blog for ongoing notes, and Projects for experiments you can try. Replace this paragraph with your contact or newsletter link when ready.
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---
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title: About
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layout: page
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---
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## About

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