AI Evaluation Must Follow the Workflow
Why production AI should be evaluated across the entire workflow, including retrieved evidence, tool use, permissions and final business outcomes.
Fynro Labs explores engineering ideas that may shape the next generation of business software.
Each paper takes one architectural assumption and examines its trade-offs without product marketing, hype or claims of a final answer.
Software changes constantly. Frameworks evolve, platforms appear and disappear, and best practices are regularly rewritten. Yet the most important changes often begin with a new question.
We prefer depth over volume, clarity over hype and thoughtful discussion over fashionable conclusions. If a paper makes you look at a familiar problem differently, it has done its job.
Why cloud is no longer the only right answer for enterprise software—and why the authoritative copy of business data deserves to become a deliberate design decision.
Local-first and on-premise software are not the same: one relocates infrastructure while the other redistributes data authority.
Why uptime cannot describe business continuity, and why resilient software must preserve usable, interpretable data.
Why useful enterprise AI autonomy begins with explicit permissions, observable decisions and reversible actions.
An API is not only a development convenience. Its completeness, limits and portability shape whether a business can recover outside a vendor platform.
A confirmation screen does not create human control by itself. Effective approval changes permissions, presents evidence and leaves time for a real decision.
We publish ideas worth discussing.