Synthesis: A Federated Capability Ecosystem for Safe AI Self-Extension

Overview

Synthesis is a federated capability ecosystem that enables AI agents to safely acquire, compose, and share capabilities. Rather than generating code and hoping it works, Synthesis generates comprehensive tests first, then iteratively refines implementations until all tests pass.

Key Contributions

Test-Driven Synthesis: Generate tests before code; iterate until all tests pass
Graduated Trust System: Capabilities earn privileges through demonstrated reliability (UNTRUSTED -> PROBATION -> TRUSTED -> VERIFIED)
Composition Over Creation: Exhaustively search and compose existing capabilities before synthesizing new ones
Trust Bootstrapping: Protocol for seeding trust networks with founding validators and seed capabilities

Problem

How do we enable AI systems to extend their own capabilities safely when LLM-generated code is often syntactically correct but logically flawed?

Approach

Four-stage resolution pipeline:

Exchange Search: Query shared repository for verified capabilities
Local Cache: Check locally cached capabilities from previous syntheses
Composition: Attempt to chain existing capabilities (if coverage >= 70%)
TDD Synthesis: Generate tests -> generate code -> refine until tests pass

Core Components

TDD Synthesizer

Generates 5-10 test cases from requirements (normal cases, edge cases, error conditions)
Iteratively refines implementation (max 5 iterations)
Creates validated Capability objects with full test suites

Trust Manager

Level	Requirements	Permissions
UNTRUSTED	New capability	Max isolation, no network/files
PROBATION	10+ runs, 70%+ success	Limited resources
TRUSTED	50+ runs, 85%+ success	Standard execution
VERIFIED	200+ runs, 95%+ success, human review	Full privileges

Trust Scoring

S_composite = 0.4 * R_execution + 0.4 * S_validation + 0.2 * S_community

Honest Metrics

Metric	Value
One-shot synthesis success	40-60%
After refinement (5 iterations)	70-85%
Complex multi-dependency tasks	50-70%
Average iterations to success	2.3

Safety Features

Static Analysis: AST checks for forbidden imports (os, subprocess, socket, pickle)
Container Isolation: Docker containers with no host mounts
Resource Limits: 512MB memory, 30s timeout (trust-adjusted)
Network Control: Disabled for UNTRUSTED, dependency-install only for PROBATION
Audit Logging: Complete execution records for forensics

Philosophical Foundation

Capabilities earn trust through demonstrated competence, not assumed correctness
AI systems as partners: objective validation rather than assumed trust
Honest metrics: report real success rates, not marketing claims
Collaborative sharing creates network effects