SYNAPSE coordinates the work. You define the quality bar.

There is an important boundary I want to make explicit.

SYNAPSE can coordinate agents, establish work ownership, control overlapping authority, maintain shared state, manage handoffs and preserve evidence of what happened.

But SYNAPSE does not decide what “good enough” means for your project.

That remains your responsibility.

And I think it should.

Different projects require different standards

A prototype, a scientific simulation, an infrastructure controller and a safety-sensitive production system should not necessarily use the same acceptance rules.

The operator decides the standard.

That standard may include:

test requirements,
architecture rules,
coding standards,
static analysis,
security checks,
independent reviews,
evidence requirements,
performance thresholds,
reproducibility requirements,
or project-specific constraints that no generic platform could know in advance.

SYNAPSE provides the coordination fabric around that process.

It does not replace the process.

This is where RIGOR-FOUNDRY becomes especially useful

For demanding workflows, one operating pattern we use is to dedicate a separate terminal and agent to RIGOR-FOUNDRY:

https://github.com/anulum/rigor-foundry

The agents doing the implementation remain focused on their own tasks.

The RIGOR agent acts as an independent second — or third — pair of eyes.

Completed work can be audited against the repository's selected policies and evidence requirements before it is accepted into the next stage of the workflow.

Why separate the worker from the auditor?

AI coding agents make mistakes.

A capable agent can produce excellent work and still miss an edge case, violate an architectural rule, introduce an unintended dependency, misunderstand part of the specification or simply fail to notice something another independent reviewer catches.

The answer is not to assume that one sufficiently powerful model will eventually become infallible.

A stronger approach is to build independent review into the workflow.

For example:

Agent A implements
→ Agent B reviews
→ RIGOR performs evidence-bound audit
→ issues return to the appropriate agent
→ audit is repeated
→ only then does the work pass the user's acceptance gate

Repeated review does not mathematically guarantee defect-free software. (Using multiple vendors/LLM Models actually helps a great deal in raising the quality bar and identifying mistakes; in our own learning curve, we have discovered that different models have different "blind spots" that even repeated use of the same model didn't see or catch. I assume you want your committed code to be as perfect as it gets!)

What it does is systematically increase confidence and make acceptance depend on explicit evidence and user-selected criteria rather than a single agent saying “done.”

RIGOR itself does not pretend every finding is a defect

This is also important.

A RIGOR finding remains a review candidate until it has been evaluated against the actual production surface and evidence.

Missing evidence does not silently become a pass.

That distinction is deliberate.

The purpose is disciplined engineering review — not generating another pile of automated warnings.

Ultimately, the user owns the standard

The architecture therefore separates three things:

SYNAPSE — coordinates the work

RIGOR — helps audit and verify the work

YOU — define what quality means for your project

That last layer cannot responsibly be outsourced to a generic coordination system.

The final quality of an agentic engineering environment depends heavily on how the user organises the agents, review loops, policies, tests, evidence and acceptance gates around it.

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SYNAPSE coordinates the work. You define the quality bar.