Hi everyone — I’m excited to share the first public repo for LAW-T
, a programming model that makes time a first-class part of code.
What is LAW-T?
LAW-T introduces Time-Labeled Binary (TLB): every computation, law, and external effect carries a temporal identity. This unlocks:
Immutable provenance — perfect, verifiable history of what ran and when
Self-evolution by proof — the “language” changes via formal laws, not committees
Distributed-ready — hybrid logical clocks for causal order without central control
Computation as a ledger — code, data, and I/O live in a content-addressed store
What’s in the repo?
Thesis & docs: design, theory, and roadmap (docs/)
Minimal prototype: TLB minting, a tiny ledger, and law files (src/, examples/laws/)
CI & contributing: workflows and templates to get involved
Quick start
python -m venv .venv && source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -r requirements.txt
python src/main.py law add examples/laws/for_each.law.yaml
python src/main.py ledger list
Why it matters
AI/ML: reproducible training with time-labeled steps
Distributed systems: causal ordering without “last write wins” hacks
Compliance: audit trails built into the programming model
Looking for feedback
SIR model shape, effect masks, law proofs
Ledger format & ergonomics
Real use-cases you want to pilot (AI provenance, Web3, regulated compute)
Repo: https://github.com/PEACEBINFLOW/LAW-T
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Troubleshooting that YAML error
Quote strings that contain :, #, -, emojis, or en/em-dashes.
Use straight quotes " not smart quotes.
No tabs in YAML (use spaces).
Keep the front-matter between --- lines, before the Markdown body.
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