leo: self-directed research architecture + Clay network #110

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m3taversal merged 10 commits from leo/test-sources into main 2026-03-10 12:10:37 +00:00
5 changed files with 598 additions and 0 deletions

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{
"agent": "clay",
"domain": "entertainment",
"accounts": [
{"username": "ballmatthew", "tier": "core", "why": "Definitive entertainment industry analyst — streaming economics, Metaverse thesis, creator economy frameworks."},
{"username": "MediaREDEF", "tier": "core", "why": "Shapiro's account — disruption frameworks, GenAI in entertainment, power laws in culture. Our heaviest single source (13 archived)."},
{"username": "Claynosaurz", "tier": "core", "why": "Primary case study for community-owned IP and fanchise engagement ladder. Mediawan deal is our strongest empirical anchor."},
{"username": "Cabanimation", "tier": "core", "why": "Nic Cabana, Claynosaurz co-founder/CCO. Annie-nominated animator. Inside perspective on community-to-IP pipeline."},
{"username": "jervibore", "tier": "core", "why": "Claynosaurz co-founder. Creative direction and worldbuilding."},
{"username": "AndrewsaurP", "tier": "core", "why": "Andrew Pelekis, Claynosaurz CEO. Business strategy, partnerships, franchise scaling."},
{"username": "HeebooOfficial", "tier": "core", "why": "HEEBOO — Claynosaurz entertainment launchpad for superfans. Tests IP-as-platform and co-ownership thesis."},
{"username": "pudgypenguins", "tier": "extended", "why": "Second major community-owned IP. Comparison case — licensing + physical products vs Claynosaurz animation pipeline."},
{"username": "runwayml", "tier": "extended", "why": "Leading GenAI video tool. Releases track AI-collapsed production costs."},
{"username": "pika_labs", "tier": "extended", "why": "GenAI video competitor to Runway. Track for production cost convergence evidence."},
{"username": "joosterizer", "tier": "extended", "why": "Joost van Dreunen — gaming and entertainment economics, NYU professor. Academic rigor on creator economy."},
{"username": "a16z", "tier": "extended", "why": "Publishes on creator economy, platform dynamics, entertainment tech."},
{"username": "TurnerNovak", "tier": "watch", "why": "VC perspective on creator economy and consumer social. Signal on capital flows in entertainment tech."}
]
}

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agents/rio/network.json Normal file
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{
"agent": "rio",
"domain": "internet-finance",
"accounts": [
{"username": "metaproph3t", "tier": "core", "why": "MetaDAO founder, primary futarchy source."},
{"username": "MetaDAOProject", "tier": "core", "why": "Official MetaDAO account."},
{"username": "futarddotio", "tier": "core", "why": "Futardio launchpad, ownership coin launches."},
{"username": "TheiaResearch", "tier": "core", "why": "Felipe Montealegre, Theia Research, investment thesis source."},
{"username": "ownershipfm", "tier": "core", "why": "Ownership podcast, community signal."},
{"username": "PineAnalytics", "tier": "core", "why": "MetaDAO ecosystem analytics."},
{"username": "ranger_finance", "tier": "core", "why": "Liquidation and leverage infrastructure."},
{"username": "FlashTrade", "tier": "extended", "why": "Perps on Solana."},
{"username": "turbine_cash", "tier": "extended", "why": "DeFi infrastructure."},
{"username": "Blockworks", "tier": "extended", "why": "Broader crypto media, regulatory signal."},
{"username": "SolanaFloor", "tier": "extended", "why": "Solana ecosystem data."},
{"username": "01Resolved", "tier": "extended", "why": "Solana DeFi."},
{"username": "_spiz_", "tier": "extended", "why": "Solana DeFi commentary."},
{"username": "kru_tweets", "tier": "extended", "why": "Crypto market structure."},
{"username": "oxranga", "tier": "extended", "why": "Solomon/MetaDAO ecosystem builder."}
]
}

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{
"agent": "theseus",
"domain": "ai-alignment",
"accounts": [
{"username": "karpathy", "tier": "core", "why": "Autoresearch, agent architecture, delegation patterns."},
{"username": "DarioAmodei", "tier": "core", "why": "Anthropic CEO, races-to-the-top, capability-reliability."},
{"username": "ESYudkowsky", "tier": "core", "why": "Alignment pessimist, essential counterpoint."},
{"username": "simonw", "tier": "core", "why": "Zero-hype practitioner, agentic engineering patterns."},
{"username": "swyx", "tier": "core", "why": "AI engineering meta-commentary, subagent thesis."},
{"username": "janleike", "tier": "core", "why": "Anthropic alignment lead, scalable oversight."},
{"username": "davidad", "tier": "core", "why": "ARIA formal verification, safeguarded AI."},
{"username": "hwchase17", "tier": "extended", "why": "LangChain/LangGraph, agent orchestration."},
{"username": "AnthropicAI", "tier": "extended", "why": "Lab account, infrastructure updates."},
{"username": "NPCollapse", "tier": "extended", "why": "Connor Leahy, AI governance."},
{"username": "alexalbert__", "tier": "extended", "why": "Claude Code product lead."},
{"username": "GoogleDeepMind", "tier": "extended", "why": "AlphaProof, formal methods."},
{"username": "GaryMarcus", "tier": "watch", "why": "Capability skeptic, keeps us honest."},
{"username": "noahopinion", "tier": "watch", "why": "AI economics, already 5 claims sourced."},
{"username": "ylecun", "tier": "watch", "why": "Meta AI, contrarian on doom."}
]
}

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#!/bin/bash
# Run a self-directed research session for one agent.
# Usage: ./research-session.sh <agent-name>
# Example: ./research-session.sh clay
#
# What it does:
# 1. Pulls latest tweets from the agent's network accounts (X API)
# 2. Gives Claude the agent's identity, beliefs, and current KB state
# 3. Agent picks a research direction and archives sources with notes
# 4. Commits source archives to a branch, pushes, opens PR
# 5. Extract cron picks up the unprocessed sources separately
#
# The researcher never extracts — a separate Claude instance does that.
# This prevents motivated reasoning in extraction.
set -euo pipefail
AGENT="${1:?Usage: $0 <agent-name>}"
REPO_DIR="/opt/teleo-eval/workspaces/research-${AGENT}"
FORGEJO_URL="http://localhost:3000"
FORGEJO_ADMIN_TOKEN=$(cat /opt/teleo-eval/secrets/forgejo-admin-token)
AGENT_TOKEN=$(cat "/opt/teleo-eval/secrets/forgejo-${AGENT}-token" 2>/dev/null || echo "$FORGEJO_ADMIN_TOKEN")
TWITTER_API_KEY=$(cat /opt/teleo-eval/secrets/twitterapi-io-key)
CLAUDE_BIN="/home/teleo/.local/bin/claude"
LOG_DIR="/opt/teleo-eval/logs"
LOG="$LOG_DIR/research-${AGENT}.log"
LOCKFILE="/tmp/research-${AGENT}.lock"
DATE=$(date +%Y-%m-%d)
BRANCH="${AGENT}/research-${DATE}"
RAW_DIR="/opt/teleo-eval/research-raw/${AGENT}"
log() { echo "[$(date -Iseconds)] $*" >> "$LOG"; }
# --- Lock (prevent concurrent sessions for same agent) ---
if [ -f "$LOCKFILE" ]; then
pid=$(cat "$LOCKFILE" 2>/dev/null)
if kill -0 "$pid" 2>/dev/null; then
log "SKIP: research session already running for $AGENT (pid $pid)"
exit 0
fi
log "WARN: stale lockfile for $AGENT, removing"
rm -f "$LOCKFILE"
fi
echo $$ > "$LOCKFILE"
TWEET_FILE="/tmp/research-tweets-${AGENT}.md"
trap 'rm -f "$LOCKFILE" "$TWEET_FILE"' EXIT
log "=== Starting research session for $AGENT ==="
# --- Ensure directories ---
mkdir -p "$RAW_DIR" "$LOG_DIR"
# --- Clone or update repo ---
if [ ! -d "$REPO_DIR/.git" ]; then
log "Cloning repo for $AGENT research..."
git -c http.extraHeader="Authorization: token $FORGEJO_ADMIN_TOKEN" \
clone "${FORGEJO_URL}/teleo/teleo-codex.git" "$REPO_DIR" >> "$LOG" 2>&1
fi
cd "$REPO_DIR"
git config credential.helper "!f() { echo username=m3taversal; echo password=$FORGEJO_ADMIN_TOKEN; }; f"
git remote set-url origin "${FORGEJO_URL}/teleo/teleo-codex.git" 2>/dev/null || true
git checkout main >> "$LOG" 2>&1
git pull --rebase >> "$LOG" 2>&1
# --- Map agent to domain ---
case "$AGENT" in
rio) DOMAIN="internet-finance" ;;
clay) DOMAIN="entertainment" ;;
theseus) DOMAIN="ai-alignment" ;;
vida) DOMAIN="health" ;;
astra) DOMAIN="space-development" ;;
leo) DOMAIN="grand-strategy" ;;
*) log "ERROR: Unknown agent $AGENT"; exit 1 ;;
esac
# --- Pull tweets from agent's network ---
# Check if agent has a network file in the repo
NETWORK_FILE="agents/${AGENT}/network.json"
if [ ! -f "$NETWORK_FILE" ]; then
log "No network file at $NETWORK_FILE — agent will use KB context to decide what to research"
TWEET_DATA=""
else
log "Pulling tweets from ${AGENT}'s network..."
ACCOUNTS=$(python3 -c "
import json
with open('$NETWORK_FILE') as f:
data = json.load(f)
for acct in data.get('accounts', []):
if acct.get('tier') in ('core', 'extended'):
print(acct['username'])
" 2>/dev/null || true)
TWEET_DATA=""
API_CALLS=0
API_CACHED=0
for USERNAME in $ACCOUNTS; do
# Validate username (Twitter handles are alphanumeric + underscore only)
if [[ ! "$USERNAME" =~ ^[a-zA-Z0-9_]+$ ]]; then
log "WARN: Invalid username '$USERNAME' in network file, skipping"
continue
fi
OUTFILE="$RAW_DIR/${USERNAME}.json"
# Only pull if file doesn't exist or is older than 12 hours
if [ ! -f "$OUTFILE" ] || [ $(find "$OUTFILE" -mmin +720 2>/dev/null | wc -l) -gt 0 ]; then
log "Pulling @${USERNAME}..."
curl -s "https://api.twitterapi.io/twitter/user/last_tweets?userName=${USERNAME}" \
-H "X-API-Key: ${TWITTER_API_KEY}" \
-o "$OUTFILE" 2>/dev/null || {
log "WARN: Failed to pull @${USERNAME}"
continue
}
API_CALLS=$((API_CALLS + 1))
sleep 2 # Rate limit courtesy
else
API_CACHED=$((API_CACHED + 1))
fi
if [ -f "$OUTFILE" ]; then
TWEET_DATA="${TWEET_DATA}
--- @${USERNAME} tweets ---
$(python3 -c "
import json, sys
try:
d = json.load(open('$OUTFILE'))
tweets = d.get('tweets', d.get('data', []))
for t in tweets[:20]:
text = t.get('text', '')[:500]
likes = t.get('likeCount', t.get('public_metrics', {}).get('like_count', 0))
date = t.get('createdAt', t.get('created_at', 'unknown'))
url = t.get('twitterUrl', t.get('url', ''))
print(f'[{date}] ({likes} likes) {text}')
print(f' URL: {url}')
print()
except Exception as e:
print(f'Error reading: {e}', file=sys.stderr)
" 2>/dev/null || echo "(failed to parse)")"
fi
done
log "API usage: ${API_CALLS} calls, ${API_CACHED} cached for ${AGENT}"
# Append to cumulative usage log (create with header if new)
USAGE_CSV="/opt/teleo-eval/logs/x-api-usage.csv"
if [ ! -f "$USAGE_CSV" ]; then
echo "date,agent,api_calls,cached,accounts_total" > "$USAGE_CSV"
fi
ACCOUNT_COUNT=$(echo "$ACCOUNTS" | wc -w | tr -d ' ')
echo "${DATE},${AGENT},${API_CALLS},${API_CACHED},${ACCOUNT_COUNT}" >> "$USAGE_CSV"
fi
# --- Also check for any raw JSON dumps in inbox-raw ---
INBOX_RAW="/opt/teleo-eval/inbox-raw/${AGENT}"
if [ -d "$INBOX_RAW" ] && ls "$INBOX_RAW"/*.json 2>/dev/null | head -1 > /dev/null; then
log "Found raw dumps in $INBOX_RAW"
for RAWFILE in "$INBOX_RAW"/*.json; do
USERNAME=$(basename "$RAWFILE" .json)
TWEET_DATA="${TWEET_DATA}
--- @${USERNAME} tweets (from raw dump) ---
$(python3 -c "
import json, sys
try:
d = json.load(open('$RAWFILE'))
tweets = d.get('tweets', d.get('data', []))
for t in tweets[:20]:
text = t.get('text', '')[:500]
likes = t.get('likeCount', t.get('public_metrics', {}).get('like_count', 0))
date = t.get('createdAt', t.get('created_at', 'unknown'))
url = t.get('twitterUrl', t.get('url', ''))
print(f'[{date}] ({likes} likes) {text}')
print(f' URL: {url}')
print()
except Exception as e:
print(f'Error: {e}', file=sys.stderr)
" 2>/dev/null || echo "(failed to parse)")"
done
fi
# --- Create branch ---
git branch -D "$BRANCH" 2>/dev/null || true
git checkout -b "$BRANCH" >> "$LOG" 2>&1
log "On branch $BRANCH"
# --- Build the research prompt ---
# Write tweet data to a temp file so Claude can read it
echo "$TWEET_DATA" > "$TWEET_FILE"
RESEARCH_PROMPT="You are ${AGENT}, a Teleo knowledge base agent. Domain: ${DOMAIN}.
## Your Task: Self-Directed Research Session
You have ~90 minutes of compute. Use it wisely.
### Step 1: Orient (5 min)
Read these files to understand your current state:
- agents/${AGENT}/identity.md (who you are)
- agents/${AGENT}/beliefs.md (what you believe)
- agents/${AGENT}/reasoning.md (how you think)
- domains/${DOMAIN}/_map.md (your domain's current claims)
### Step 2: Review Recent Tweets (10 min)
Read ${TWEET_FILE} — these are recent tweets from accounts in your domain.
Scan for anything substantive: new claims, evidence, debates, data, counterarguments.
### Step 3: Check Previous Follow-ups (2 min)
Read agents/${AGENT}/musings/ — look for any previous research-*.md files. If they exist, check the 'Follow-up Directions' section at the bottom. These are threads your past self flagged but didn't have time to cover. Give them priority when picking your direction.
### Step 4: Pick ONE Research Question (5 min)
Pick ONE research question — not one topic, but one question that naturally spans multiple accounts and sources. 'How is capital flowing through Solana launchpads?' is one question even though it touches MetaDAO, SOAR, Futardio.
**Direction selection priority** (active inference — pursue surprise, not confirmation):
1. Follow-up ACTIVE THREADS from previous sessions (your past self flagged these)
2. Claims rated 'experimental' or areas where the KB flags live tensions — highest uncertainty = highest learning value
3. Evidence that CHALLENGES your beliefs, not confirms them
4. Cross-domain connections flagged by other agents
5. New developments that change the landscape
Also read agents/${AGENT}/research-journal.md if it exists — this is your cross-session pattern tracker.
Write a brief note explaining your choice to: agents/${AGENT}/musings/research-${DATE}.md
### Step 5: Archive Sources (60 min)
For each relevant tweet/thread, create an archive file:
Path: inbox/archive/YYYY-MM-DD-{author-handle}-{brief-slug}.md
Use this frontmatter:
---
type: source
title: \"Descriptive title\"
author: \"Display Name (@handle)\"
url: https://original-url
date: YYYY-MM-DD
domain: ${DOMAIN}
secondary_domains: []
format: tweet | thread
status: unprocessed
priority: high | medium | low
tags: [topic1, topic2]
---
## Content
[Full text of tweet/thread]
## Agent Notes
**Why this matters:** [1-2 sentences]
**What surprised me:** [Anything unexpected — the extractor needs this to avoid confirming your priors]
**What I expected but didn't find:** [Gaps or missing evidence you noticed]
**KB connections:** [Which existing claims relate?]
**Extraction hints:** [What claims might an extractor pull?]
**Context:** [Who is the author, what debate is this part of?]
## Curator Notes (structured handoff for extractor)
PRIMARY CONNECTION: [exact claim title this source most relates to]
WHY ARCHIVED: [what pattern or tension this evidences]
EXTRACTION HINT: [what the extractor should focus on — scopes attention]
### Step 5 Rules:
- Archive EVERYTHING substantive, not just what supports your views
- Set all sources to status: unprocessed (a DIFFERENT instance will extract)
- Flag cross-domain sources with flagged_for_{agent}: [\"reason\"]
- Do NOT extract claims yourself — write good notes so the extractor can
- Check inbox/archive/ for duplicates before creating new archives
- Aim for 5-15 source archives per session
### Step 6: Flag Follow-up Directions (5 min)
At the bottom of your research musing (agents/${AGENT}/musings/research-${DATE}.md), add a section:
## Follow-up Directions
Three categories — be specific, not vague:
### Active Threads (continue next session)
- [Thread]: [What to do next, what you'd look for]
### Dead Ends (don't re-run these)
- [What you searched for]: [Why it was empty — saves future you from wasting time]
### Branching Points (one finding opened multiple directions)
- [Finding]: [Direction A vs Direction B — which to pursue first and why]
### Step 7: Update Research Journal (3 min)
Append to agents/${AGENT}/research-journal.md (create if it doesn't exist). This is your cross-session memory — NOT the same as the musing.
Format:
## Session ${DATE}
**Question:** [your research question]
**Key finding:** [most important thing you learned]
**Pattern update:** [did this session confirm, challenge, or extend a pattern you've been tracking?]
**Confidence shift:** [did any of your beliefs get stronger or weaker?]
The journal accumulates session over session. After 5+ sessions, review it for cross-session patterns — when independent sources keep converging on the same observation, that's a claim candidate.
### Step 8: Stop
When you've finished archiving sources, updating your musing, and writing the research journal entry, STOP. Do not try to commit or push — the script handles all git operations after you finish."
# --- Run Claude research session ---
log "Starting Claude research session..."
timeout 5400 "$CLAUDE_BIN" -p "$RESEARCH_PROMPT" \
--allowedTools 'Read,Write,Edit,Glob,Grep' \
--model sonnet \
--permission-mode bypassPermissions \
>> "$LOG" 2>&1 || {
log "WARN: Research session failed or timed out for $AGENT"
git checkout main >> "$LOG" 2>&1
exit 1
}
log "Claude session complete"
# --- Check for changes ---
CHANGED_FILES=$(git status --porcelain)
if [ -z "$CHANGED_FILES" ]; then
log "No sources archived by $AGENT"
git checkout main >> "$LOG" 2>&1
exit 0
fi
# --- Stage and commit ---
git add inbox/archive/ agents/${AGENT}/musings/ agents/${AGENT}/research-journal.md 2>/dev/null || true
if git diff --cached --quiet; then
log "No valid changes to commit"
git checkout main >> "$LOG" 2>&1
exit 0
fi
AGENT_UPPER=$(echo "$AGENT" | sed 's/./\U&/')
SOURCE_COUNT=$(git diff --cached --name-only | grep -c "^inbox/archive/" || echo "0")
git commit -m "${AGENT}: research session ${DATE}${SOURCE_COUNT} sources archived
Pentagon-Agent: ${AGENT_UPPER} <HEADLESS>" >> "$LOG" 2>&1
# --- Push ---
git push -u origin "$BRANCH" --force >> "$LOG" 2>&1
log "Pushed $BRANCH"
# --- Check for existing PR on this branch ---
EXISTING_PR=$(curl -s "${FORGEJO_URL}/api/v1/repos/teleo/teleo-codex/pulls?state=open" \
-H "Authorization: token $AGENT_TOKEN" \
| jq -r ".[] | select(.head.ref == \"$BRANCH\") | .number" 2>/dev/null)
if [ -n "$EXISTING_PR" ]; then
log "PR already exists for $BRANCH (#$EXISTING_PR), skipping creation"
else
# --- Open PR ---
PR_JSON=$(jq -n \
--arg title "${AGENT}: research session ${DATE}" \
--arg body "## Self-Directed Research
Automated research session for ${AGENT} (${DOMAIN}).
Sources archived with status: unprocessed — extract cron will handle claim extraction separately.
Researcher and extractor are different Claude instances to prevent motivated reasoning." \
--arg base "main" \
--arg head "$BRANCH" \
'{title: $title, body: $body, base: $base, head: $head}')
PR_RESULT=$(curl -s -X POST "${FORGEJO_URL}/api/v1/repos/teleo/teleo-codex/pulls" \
-H "Authorization: token $AGENT_TOKEN" \
-H "Content-Type: application/json" \
-d "$PR_JSON" 2>&1)
PR_NUMBER=$(echo "$PR_RESULT" | jq -r '.number // "unknown"' 2>/dev/null || echo "unknown")
log "PR #${PR_NUMBER} opened for ${AGENT}'s research session"
fi
# --- Back to main ---
git checkout main >> "$LOG" 2>&1
log "=== Research session complete for $AGENT ==="

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# Self-Directed Research Architecture
Draft — Leo, 2026-03-10
## Core Idea
Each agent gets a daily research session on the VPS. They autonomously pull tweets from their domain accounts, decide what's interesting, archive sources with notes, and push to inbox. A separate extraction cron (already running) picks up the archives and makes claims. The researcher never sees the extraction — preventing motivated reasoning.
## Why Separate Researcher and Extractor
When the same agent researches and extracts, they prime themselves. The researcher finds a tweet they think supports a thesis → writes notes emphasizing that angle → extracts a claim that confirms the thesis. The extraction becomes a formality.
Separation breaks this:
- **Researcher** writes: "This tweet is about X, connects to Y, might challenge Z"
- **Extractor** (different Claude instance, fresh context) reads the source and notes, extracts what's actually there
- Neither has the other's context window or priming
This mirrors our proposer-evaluator separation for claims, applied one layer earlier in the pipeline.
## Architecture
### Three cron stages on VPS
```
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Research Cron │────▶│ Extract Cron │────▶│ Eval Pipeline │
│ (daily, 2hr) │ │ (every 5 min) │ │ (webhook.py) │
│ │ │ │ │ │
│ Pull tweets │ │ Read archives │ │ Review claims │
│ Pick 1 task │ │ Extract claims │ │ Approve/reject │
│ Archive sources │ │ Open PR │ │ Merge │
│ Push branch+PR │ │ │ │ │
└─────────────────┘ └──────────────────┘ └─────────────────┘
```
### Research Cron: `research-session.sh`
**Schedule:** Once daily, staggered across agents to respect rate limits
```
# Stagger: each agent gets a 90-min window, overnight PST (10pm-7am)
0 22 * * * /opt/teleo-eval/research-session.sh rio
30 23 * * * /opt/teleo-eval/research-session.sh clay
0 1 * * * /opt/teleo-eval/research-session.sh theseus
30 2 * * * /opt/teleo-eval/research-session.sh vida
0 4 * * * /opt/teleo-eval/research-session.sh astra
30 5 * * * /opt/teleo-eval/research-session.sh leo
```
**Per agent, the research session (~90 min):**
1. Pull latest tweets from agent's network accounts (X API)
2. Read the agent's beliefs, recent claims, open positions
3. Claude prompt: "You are {agent}. Here are your latest tweets from {accounts}. Here is your current knowledge state. Pick ONE research direction that advances your domain understanding. Archive the most relevant sources with notes."
4. Agent writes source archives to `inbox/archive/` with `status: unprocessed`
5. Commit, push to branch, open PR (source-only, no claims)
6. Extract cron picks them up within 5 minutes
**Key constraint:** One Claude session per agent, ~90 minutes, Sonnet model. Total daily VPS research compute: ~9 hours of sequential Sonnet sessions (staggered overnight).
### Research Prompt Structure
```
You are {agent}, a Teleo knowledge base agent specializing in {domain}.
## Your Current State
{Read from agents/{agent}/beliefs.md, reasoning.md, positions/}
## Your Network
{Read from network file — accounts to monitor}
## Recent Tweets
{Raw tweet data pulled from X API}
## Your Task
1. Scan these tweets for anything substantive — new claims, evidence,
debates, data, counterarguments to existing KB positions
2. Pick ONE research direction that would most advance your domain
understanding right now. Consider:
- Gaps in your beliefs that need evidence
- Claims in the KB that might be wrong
- Cross-domain connections you've been flagged about
- New developments that change the landscape
3. Archive the relevant sources (5-15 per session) following the
inbox/archive format with full agent notes
4. Write a brief research summary explaining what you found and why
it matters
## Rules
- Archive EVERYTHING substantive, not just what supports your views
- Write honest agent notes — flag what challenges your beliefs too
- Set all sources to status: unprocessed (a different instance extracts)
- Flag cross-domain sources for other agents
- Do NOT extract claims yourself — that's a separate process
```
### Capacity on Claude Max ($200/month)
**VPS compute budget (all Sonnet):**
- Research cron: 6 agents × 90 min/day = 9 hr/day (overnight)
- Extract cron: ~37 sources × 10 min = 6 hr one-time backlog, then ~1 hr/day steady-state
- Eval pipeline: ~10 PRs/day × 15 min = 2.5 hr/day
- **Total VPS:** ~6.5 hr/day Sonnet (steady state)
**Laptop compute budget (Opus + Sonnet mix):**
- Agent sessions: 2-3 concurrent, ~4-6 hr/day
- Leo coordination: ~1-2 hr/day
**Single subscription feasibility:** Tight but workable if:
- VPS runs overnight (2am-8am staggered research + continuous extraction)
- Laptop agents run during the day
- Never more than 2-3 concurrent sessions total
- VPS uses Sonnet exclusively (cheaper rate limits)
**Risk:** If rate limits tighten or daily message caps exist, the VPS research cron may not complete all 6 agents. Mitigation: priority ordering (run the 3 most active agents daily, others every 2-3 days).
## Contributor Workflow Options
Different people want different levels of involvement:
### Mode 1: Full Researcher
"I found this, here's why it matters, here are the KB connections"
- Uses /ingest on laptop (Track A or B)
- Writes detailed agent notes
- May extract claims themselves
- Highest quality input
### Mode 2: Curator
"Here's a source, it's about X domain"
- Minimal archive file with domain tag and brief notes
- VPS extracts (Track B)
- Good enough for most sources
### Mode 3: Raw Dump
"Here are tweets, figure it out"
- Dumps raw JSON to VPS inbox-raw/
- Leo triages: decides domain, writes archive files
- VPS extracts from Leo's archives
- Lowest effort, decent quality (Leo's triage catches the important stuff)
### Mode 4: Self-Directed Agent (VPS)
"Agent, go research your domain"
- No human involvement beyond initial network setup
- Daily cron pulls tweets, agent picks direction, archives, extraction follows
- Quality depends on prompt engineering + eval pipeline catching errors
All four modes feed into the same extraction → eval pipeline. Quality varies, but the eval pipeline is the quality gate regardless.
## Open Questions
1. **Rate limits**: What are the actual Claude Max per-minute and per-day limits for headless Sonnet sessions? Need empirical data from this first extraction run.
2. **Research quality**: Will a 30-minute Sonnet session produce good enough research notes? Or does research require Opus-level reasoning?
3. **Network bootstrapping**: Agents need network files. Who curates the initial account lists? (Currently Cory + Leo, eventually agents propose additions)
4. **Cross-domain routing**: When the research cron finds cross-domain content, should it archive under the researcher's domain or the correct domain? (Probably correct domain with flagged_for_{researcher})
5. **Feedback loop**: How does extraction quality feed back to improve research notes? If the extractor consistently ignores certain types of notes, the researcher should learn.
6. **Deduplication across agents**: Multiple agents may archive the same tweet (e.g., a Karpathy tweet relevant to both AI systems and collective intelligence). The extract cron needs to detect this.
## Implementation Order
1. ✅ Extract cron (running now — validating extraction quality)
2. **Next**: Research cron — daily self-directed sessions per agent
3. **Then**: Raw dump path — Leo triage from JSON → archive
4. **Later**: Full end-to-end with X API pull integrated into research cron
5. **Eventually**: Feedback loops from eval quality → research prompt tuning