Methodology
How FISTA Delivers AI Projects That Ship
How does FISTA actually deliver AI? The process—discovery, spec-driven build, evaluation, adoption, and documented handoff—that turns AI projects into shipped systems.
1 min
FISTA field notes / Methodology
Methodology
6 field notes on methodology.
Archive
Methodology
6 field notes
Methodology
Spec-Driven Development in Practice
The theory of spec-driven development is simple; the practice is where reliability is won. How a specification shapes real AI delivery, step by step.
1 min
Methodology
AI Quality Assurance: Testing Probabilistic Systems
You can't unit-test probability the old way. How AI quality assurance—evaluation, adversarial testing, and monitoring—keeps AI systems reliable in the real world.
1 min
Methodology
How We Scope AI Projects (Discovery Done Right)
A good AI project is won or lost in scoping. How FISTA's discovery defines the outcome, assesses data reality, and surfaces risks—before a line of code.
2 min
Methodology
Verification-Led Engineering for AI
In the AI era, the scarce skill isn't producing output—it's verifying it. How verification-led engineering makes AI reliability provable, not hopeful.
2 min
Methodology
AI Project Management: What's Different
AI projects don't run like traditional software projects. The differences—uncertainty, data, evaluation gates, adoption—and how to manage them without nasty surprises.
1 min
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