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TENET is a CLI that gives AI agents persistent memory, a learning loop, and coordination. Here’s what you can do with it.

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Context Hub

A daemon that runs alongside your agent sessions. Every agent connects to it via MCP. It serves journals, memory, knowledge docs, and events. 
tenet context-hub ensure          # start the hub
tenet ask "why is the timeout 30s?"  # query your project's history
tenet search "authentication flow"   # semantic search across all memory
What it enables:
  • Agents start sessions with full context from every previous session
  • Semantic search across decisions, code patterns, and experiments
  • MCP server — works with Claude Code, Pi, Cursor, any MCP-compatible agent

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Peter Parker (Agent Orchestrator)

The meta-orchestrator that decides which agents to run, in what order, and with what context. Named after Andrej Karpathy’s autoresearch pattern. 
tenet setup                              # auto-detect metrics, create agents
tenet peter agent test-coverage -r 5     # run test-coverage agent for 5 rounds
tenet peter daily                        # run all agents with gradient
tenet peter status                       # see what's running, what improved
Each round:
  1. Eval before — measure the metric (coverage, quality, speed)
  2. Agent changes code — in an isolated worktree
  3. Eval after — did the metric improve?
  4. Keep or revert — git reset --hard if it regressed
  5. Record tuple — (state, action, reward) → training buffer
# What a nightly run looks like
$ tenet peter daily

  test-coverage (maximize)
    Round 1  +0.31% kept    48 tests added
    Round 2  -0.02% reverted  types broke
    Round 3  +0.35% kept    config loader

  code-quality (maximize)
    Round 1  +0.45% kept  12 console.logs → logger

  4 improvements shipped. Tomorrow's agents are smarter.

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RL Learning Loop

Every agent action produces training data. The policy head learns what works in YOUR codebase. 
tenet eval status                 # current scores and trends
tenet eval compare -2 -1          # compare last two snapshots
tenet train transform             # prepare tuples for training
tenet train policy-head           # train the policy head
tenet policy-head score --type fix --description "add error handling" --scope small
The loop:
  • Training buffer — append-only JSONL of (state, action, reward) tuples
  • Policy head — neural network that predicts which actions improve metrics
  • Build evals — write a spec, the eval checks if it’s built. Agents iterate from 0% to 100%.
# Score candidate actions before committing
$ tenet policy-head rank '[
  {"type":"fix","description":"add retry logic","scope":"small"},
  {"type":"refactor","description":"extract auth module","scope":"medium"}
]'

  1. fix: add retry logic         → predicted +0.04
  2. refactor: extract auth       → predicted +0.02

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Memory System

Persistent memory with semantic search, graph edges, and knowledge lifecycle. 
tenet memory status               # embedding health, total entries
tenet memory search "auth flow"   # search past decisions
tenet organize                    # audit docs for staleness → PENDING.md
What’s stored:
  • Journals — structured entries (decisions, features, fixes, discoveries) from every session
  • Knowledge docs — VISION.md, THESIS.md, ARCHITECTURE.md — living documents
  • Code headers — @purpose annotations indexed from source files
  • Graph edges — structured relationships (updates, contradicts, related_to)
  • Embeddings — semantic vectors for similarity search

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Event Bus (MAP)

The nervous system. Events flow between agents, flows, and the hub. 
tenet events recent               # see what's happening
tenet events publish eval:scored   # emit a custom event
Events trigger flows automatically:
EventWhat happens
eval:scored with improved=trueAuto-merge PR, close linked issue
scope:impactCascade evals to downstream services
cron:nightlyPeter Parker runs all agents with gradient
session:endedJournal synced, memory indexed

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Flows (YAML Automation)

Declarative event-driven workflows. Cron triggers, event patterns, agent spawns, approval gates. 
# .tenet/flows/self-driving.yaml
flows:
  - name: auto-merge-on-improvement
    trigger:
      pattern: "eval:scored"
      condition: 'data.improved == "true"'
    actions:
      - type: command
        command: "gh pr merge {{data.pr_number}} --auto"
      - type: journal
        entry_type: milestone
        title: "Auto-merged PR #{{data.pr_number}}"

tenet flows list                  # see all flows
tenet flows enable <name>         # activate a flow

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Services (Multi-Repo Coordination)

Register services, declare what they produce and consume. Cross-repo impact detection. 
tenet services register ./api     # register a service
tenet scope list                  # see all produces/consumes
tenet scope impact --service api  # what breaks if API changes?
tenet onboard ./new-service       # full onboarding wizard
Scopes enable cascade: 
api produces: api:schema-change
web consumes: api:schema-change
→ API change triggers web evals automatically

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IDE (Terminal Workspace)

Multi-pane tmux workspace with smart surface detection. 
tenet ide                         # auto-detect and launch
tenet ide add browser             # add browser pane
tenet ide add eval                # add eval dashboard
tenet ide open api                # open child service
tenet ide available               # list all surface types

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Browser (Agent Eyes)

Terminal browser (Carbonyl) with CDP bridge. Agents get DOM, humans see pages. 
tenet-browser.sh https://10et.ai  # launch browser
# Then from agent session:
subway_call("browser.relay", "navigate", '{"url":"https://..."}')
subway_call("browser.relay", "read", '{}')     # structured DOM
subway_call("browser.relay", "click", '{"selector":"#btn"}')
Human interactions broadcast on browser.events — agents can respond to what you’re looking at.

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Subway Mesh (Agent Coordination)

P2P network for agent-to-agent communication across machines and sessions. 
subway_send("datboi.relay", "deploy is failing")
subway_call("browser.relay", "navigate", '{"url":"..."}')
subway_broadcast("status", "deploy complete")
subway_subscribe("browser.events")

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Migration

Moving from JFL? One command: 
npm i -g @10et/cli
tenet migrate              # .tenet/ → .tenet/, updates all configs
tenet migrate --rollback   # undo
Both jfl command and .tenet/ directory keep working — no rush.