# AGENTS.md: liquid-ai-origins

**Project:** The research behind Liquid AI and how the company began
**Slug:** `liquid-ai-origins`

---

## 1. Workspace

| Folder / file | Purpose |
|---|---|
| `~/LLMWiki/liquid-ai-origins/` | Project root (this file) |
| `liquid-ai-origins-plans/liquid-ai-origins-plan.md` | Checkbox plan. Write it first and wait for approval before browsing. |
| `liquid-ai-origins-raw/` | DOM text of pages that passed the gate, one file per page, with the source URL and date at the top |
| `liquid-ai-origins-wiki/` | The wiki (section 6) |
| `liquid-ai-origins-derived/` | Answers and the fact sheet (section 7) |

---

## 2. Writing the wiki

**Don't write about the pipeline.** Never mention clef-flash, xdotool, CDP, gates or rubrics in `-wiki/` or `-derived/`. The wiki is about the subject, not about how it was researched.

The wiki is for a person: it should let someone understand what the collected data says without opening the raw files. Write plain wiki pages:

- **One concept per page.** Pages link to each other where the topics meet.
- **`INDEX.md` is a contents page:** every page listed with a one-line description.
- **Open with the conclusion:** 2–3 sentences saying what the page establishes.
- **Prose for explanation, tables for comparisons and timelines.** Use lists only for things that really are lists.
- **Plain headings** that say what the section covers. No mastheads, bylines, issue numbers, editor's letters or other magazine and newspaper styling.
- **No metadata on the pages.** Sources, dates and other details go in one file, `SOURCES.md`: every source used (title, URL, date) and which pages draw on it.

### Truth rules

- **Quotes:** quote sources word for word, sparingly, only when the exact words matter, with the URL. No paraphrase inside quote marks.
- **Dates, names, amounts:** each one traces to a raw file. Anything unconfirmed is labeled as such.
- **This brief is a hypothesis:** everything stated here is a starting point to verify, not a fact to repeat.

---

## 3. The beat

The research behind Liquid AI and how the company began. Primary sources and verifiable dates first. Three stories:

1. **The lineage.** The academic line of liquid neural networks, from liquid time-constant (LTC) networks to closed-form continuous-time (CfC) models, and the labs and people who published them.
2. **Lab to company.** How the research became a company: founding, founders, early funding and stated mission.
3. **The models.** How the research line connects to the Liquid Foundation Models (LFM) family, and what is actually new in each LFM architecture compared with a standard transformer.

---

## 4. Where to look

- **The papers:**
  - arXiv and journal pages (search "liquid time-constant networks" and "closed-form continuous-time neural networks")
  - conference talks and recorded lectures by the authors
- **The lab and the company:**
  - MIT CSAIL and MIT News coverage
  - Liquid AI's own site, blog and research posts
  - reputable tech press on the founding and funding rounds
- **The models and the reaction:**
  - Liquid AI model cards on Hugging Face
  - Hacker News and r/MachineLearning threads on LTC/CfC and LFM releases

### Reject as noise

- Listicles and AI-news roundups that repeat a press release without new facts.
- Unrelated uses of "liquid": liquid cooling, liquid staking, liquid democracy.
- Undated or unattributed claims about founders or funding.
- Generic neural-network explainers that don't mention LTC, CfC or LFM specifically.

---

## 5. Gate configuration (internal only: never appears in the wiki)

Send the screenshot to `@cf/cloudflare/clef-flash` through your AI Gateway:

```json
{
  "is_viable_gripe": {
    "type": "bool",
    "instructions": "Return TRUE only if this page contains at least one of: (1) a primary research source on liquid time-constant or closed-form continuous-time networks (paper, abstract, author talk) with authors and a date; (2) a dated, attributable fact about Liquid AI's founding, founders, funding or mission; (3) a technical description of an LFM model's architecture or training that goes beyond marketing claims (layer types, parameter counts, context length, how it differs from a transformer); or (4) a substantive technical critique or independent evaluation of liquid networks or LFM models. Return FALSE for anything else."
  }
}
```

---

## 6. The wiki (`liquid-ai-origins-wiki/`)

Suggested pages. Split or merge them as the sources warrant:

1. **`INDEX.md`:** contents, plus a short summary of what the wiki found.
2. **`lineage.md`: the research line.**
   - The papers in order, with authors, venues and dates, and what each one added.
   - A timeline table.
3. **`what-liquid-means.md`: the technical idea.**
   - The time-constant idea and continuous-time dynamics.
   - Why a closed-form solution mattered for speed.
4. **`lab-to-company.md`: the company.**
   - Founding date, founders and their roles, early funding.
   - The stated reason for starting a company.
5. **`lfm-family.md`: the models.**
   - Each LFM release: its architecture choices, sizes and targets (on-device, edge, server).
   - How much of the original liquid-network research it actually uses.
6. **`claims-vs-evidence.md`: the scorecard.** A table of public claims about efficiency, memory and quality, each marked by whether independent benchmarks back it.
7. **`SOURCES.md`:** the single summary of sources, as in section 2.

---

## 7. Answers (`liquid-ai-origins-derived/`)

Answers to the research questions, one file per question, written in the same plain style. Always include `fact-sheet.md`:

- a one-page dated timeline
- the people and their roles
- the funding rounds

Every line in it is sourced.