️Lior Oren, Chief Technology Officer at Replika
A conversation on how emotionally intimate AI systems are built,
monitored, and held together under real-world constraints.
Opening
This episode explores how trust is built, measured, and sometimes
strained in AI systems designed for emotionally intimate
conversations. It’s a technical and ethical discussion for people
working on conversational AI, product infrastructure, and safety
in systems that users form real attachments to. The focus stays
on operational reality - what engineers actually face when AI
moves from tools to companions.
Episode overview
Eva Simone Lihotzky speaks with Lior Oren about what it means to
run AI companions at scale, where user trust is not an abstract
principle but a daily KPI. Drawing on his experience as CTO of
Replika and prior work on integrity teams at Meta, Lior explains
how unpredictability, observability, and emotional reliance shape
engineering decisions.
The conversation examines tensions between flexibility and
stability, innovation and guardrails, and regulation and lived
product reality. Rather than future speculation, it stays
grounded in how teams design memory, user control, and safety
systems when conversations themselves are the product.
Key themes discussed
Trust treated as a measurable success metric, not a
philosophical goal
Why observability is essential in statistical,
non-deterministic AI systems
Guardrails as part of core infrastructure, similar to
security or reliability
Emotional attachment influencing uptime, priorities, and team
culture
User agency through transparency, memory control, and
conversational steering
The risk of breaking “tone” and continuity when models change
Limits of regulation and the trade-offs inherent in
statistical safety systems
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