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TENET is the context and learning layer for AI agents. It sits between your agents and your project, capturing every decision, accumulating training data, and improving the policy — automatically.

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The Problem

Every AI agent starts from zero. Every session. The agent has no memory of what worked yesterday, no model of the domain it operates in, no learned preferences from the human it serves. Session ends, context gone.

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What TENET Does

TENET provides the closed loop that connects memory, training, policy, and eval into a system that compounds:
  • Memory — every decision, pattern, and learned knowledge persists across sessions via a searchable knowledge graph with embeddings
  • Training — every agent action produces a (state, action, outcome) tuple that feeds the learning loop
  • Policy — an RL-trained action selector that biases agents toward what historically worked for YOUR project
  • Eval — continuous A/B testing that measures real improvement and catches regression

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How It Compounds

1

Week 1: You work, TENET watches

You and your agents work normally using any tool. TENET captures decisions, code change outcomes, and patterns. Journals accumulate. Memory indexes.
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Week 2: The world model forms

TENET knows your naming patterns, architecture preferences, which approaches work in your codebase. Agents get better suggestions from memory search.
3

Month 1: Agents improve overnight

The policy head has enough data. RL agents try improvements while you sleep — eval against your metrics, keep what works, revert what doesn’t. You wake up to PRs.
4

Month 3: Compound intelligence

The world model deeply understands your project. New team members’ agents inherit the full context. The system understands not just what the code does but how and why.

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Works With Any Harness

TENET provides context via MCP. Use it with:
  • TENET harness (built-in TUI with extensions, skills, RPC mode)
  • Claude Code (Anthropic’s CLI agent)
  • Cursor (IDE-native agent)
  • Custom scripts (anything that can call MCP tools)

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For Solo Developers and Teams

Solo developer

One TENET workspace. Your agents learn your patterns, preferences, and codebase. Overnight agents improve your metrics.
tenet init

Team / Organization

Parent TENET workspace scopes child workspaces per service. Each service has its own context and agents. New hire’s agents inherit full context from day one.
tenet init --parent ./platform