Dev Journal
Technical notes from the Fitlane AI team — development, AI matching, product decisions, transparent experiments.
-
How We Made Candidates Private by Default
We changed candidate privacy settings to ensure greater protection of personal information.
Read → -
How We Rethought Our Approach to Calculating Match Score
We optimized the match score calculation algorithm, enhancing the quality of recommendations for users.
Read → -
Why We Don't Send the Entire Candidate Database to GPT
We decided not to send the entire candidate database to GPT to avoid issues with privacy and the quality of recommendations.
Read → -
How We Taught AI to Distinguish a Real Senior Go Developer from AI Hallucinations
We implemented deterministic filters and qualification signals to reduce AI errors in candidate evaluation.
Read → -
Development note: synthetic example
This article documents an internal experiment related to a small product decision at Fitlane AI.
Read →