Automated verification pipeline
Every site change runs a unit-test suite, Astro type checking, content validation, internal-link checks, Kayla golden-question checks, and archive checksum verification before it can be called done.
FDS Lab // Engineering
Build through experimentation.
FDS projects are developed through iterative experimentation. Systems are built, tested, measured, challenged, and refined before ideas become reusable architecture — and the evidence is public wherever it can be.
FDS // Engineering Evidence
What the work actually produces
Publishable proof from the release record and the automated pipeline — process claims stay tied to verifiable artifacts.
Accessibility & UI gates
Browser tests with axe-core accessibility scanning, UI contract tests for the homepage and ecosystem, and a signature accessibility check run alongside the unit suite.
Packaged-app validation
Earlier CodeForge release artifacts were built and consumer-verified on GitHub-hosted Windows runners. Current installer and portable downloads are paused while the release is updated.
Fail-closed reliability engineering
CodeForge's ForgeZero boundary refuses paid, local, unknown-cost, and unverified model routes instead of silently falling back; command risk classification and secret scanning run before model context leaves the machine.
Game development verification
Owner-reported Dead Trails West simulation work has not been independently verified here; live visual verification in Unreal Engine 4.27 is also unverified. No public playable build is claimed.
Efficiency research
ForgeGreen — in active development — reduces measurable computational work upstream of verification and completion authorities without weakening any of them.
FDS // Public Release History
Shipped software
Release history is shown with its current distribution status. Availability can change while release records remain preserved.
FDS // Engineering Philosophy
How FDS approaches the work
Evidence over assumptions
Systems are not considered successful simply because they executed. Results should provide evidence that the intended objective was achieved.
Adaptive computation
Software should understand and adapt to the hardware and compute environments available to it.
Governed intelligence
Training, evaluation, experimentation, and deployment should leave understandable evidence.
Build through experimentation
Research findings should become reusable architecture only after surviving meaningful real-world use.
FDS // Decision Loop
Question to iteration
Execution is not the same as success. Results matter. This loop is how the lab establishes what is true.
Question
Work begins from a specific, testable objective — not activity for its own sake.
Experiment
A bounded experiment is designed with controlled inputs and a defined success condition.
Evidence
Results are measured against that condition. Execution alone is not evidence.
Decision
The finding is accepted, revised, or rejected based on what the evidence supports.
Iteration
Accepted findings are refined and challenged again before they become reusable architecture.
The development loop applies the same discipline to daily work
IdeaBuildTestMeasureLearnEvolve
The decision loop determines what the evidence supports; the development loop turns what survives into better systems. These principles describe FDS engineering philosophy, not universal scientific law or a certification claim.