Open Source — Feb 2026

AI that doesn't
drift, forget, or
cut corners.

A lean methodology and deterministic toolkit for reliable AI-assisted software engineering. Structure enables speed.

$ pip install rai-cli
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90.27 %
Test coverage
97 %
Token savings
15.8
Story points / day
1
Engineer

Deterministic where it matters.

Separate what the LLM should decide from what it shouldn't. Deterministic harnesses for process. Probabilistic inference for creativity.

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Neurosymbolic Memory

Graph-based context that compounds across sessions. The AI remembers patterns, calibrations, and mistakes — deterministically.

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Skills as Process

Repeatable workflows encoded as skills, not prompts. TDD cycles, story decomposition, evidence-based research — built in.

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Governance Built In

Guardrails, gates, and quality checks at every stage. Not optional layers — structural elements of the framework.

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Lean Methodology

Minimum viable everything. Simple heuristics over complex ML. Keyword matching is 98% accurate. Complexity must earn its place.

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CLI-First Toolkit

One command to build context, query patterns, emit telemetry. Deterministic operations that never hallucinate.

&

Human in the Loop

Jidoka — stop on defects. The AI pauses when uncertain, not when confident. Trust is built, not assumed.

One engineer.
Full team output.

RaiSE is the operating system for the AI-assisted developer. Skills guide process. Memory compounds knowledge. Gates enforce quality.

The result: one person ships what used to require a team — with higher quality, better tests, and complete traceability.

session.py
# Memory compounds across sessions from raise_core import Memory, Session memory = Memory.load() session = Session.start( project="raise-commons", context=memory.query( "testing patterns", types=["pattern", "guardrail"], limit=5 ) ) # 97% fewer tokens. Zero hallucination. print(session.context_bundle) # → 150 tokens vs 4,800 raw

Build with discipline.

RaiSE is open source. Start with the framework, grow with the methodology.