Fresh Context Chai: The Domain Expert Eval Problem
- Date
- 2026-05-08
- Location
- San Francisco, CA, USA
- Host
- Failproof AI
About this event
Fresh Context Chai: The Domain Expert Eval Problem is a meetup for people thinking seriously about how we evaluate AI systems when the people best equipped to judge quality are not model builders, but domain experts. If you have ever struggled to turn expert judgment into something repeatable, useful, and actionable, this is the kind of conversation that can save you weeks of vague debate and mismatched expectations. This event brings that problem into the room in a practical, community-driven setting. Expect thoughtful discussion, sharp questions, and the kind of in-person exchange that works best when people can compare real evaluation challenges across products, teams, and disciplines. About the Event At its core, this meetup is about a problem many teams hit as soon as they move beyond generic benchmarks: the hardest evaluations often depend on specialized expertise. Whether the task involves legal reasoning, clinical nuance, financial interpretation, operations knowledge, or another domain-specific standard, it is often difficult to define what “good” looks like without involving people whose time is limited and whose judgment may be hard to operationalize. Fresh Context Chai creates space to talk about that challenge directly. Rather than treating evaluation as a purely technical pipeline, this event centers the messy but important reality that expert feedback, reviewer alignment, rubric design, and context-specific quality standards all shape whether an eval is actually trustworthy. The format is designed to feel approachable and useful. This is not just a one-way presentation or a generic networking hour. It is a meetup built for people who want to unpack a real problem with others who are close enough to the work to have informed opinions, concrete examples, and useful pushback. Because the topic sits at the intersection of product, research, operations, and subject-matter expertise, the room is likely to include people coming from different angles. That mix is part of the value: you will hear how others are framing the same issue, where they are getting stuck, and what kinds of evaluation practices are holding up under real-world constraints. What to Expect You should expect a conversational, intellectually engaged in-person meetup with time for both structured discussion and informal connection. The topic itself invites nuance, so the focus will likely be less on easy answers and more on practical frameworks, tradeoffs, and lessons learned from actual attempts to evaluate systems in expert domains. A typical flow for a gathering like this may include: Arrival and informal mingling Framing of the core topic: the domain expert eval problem Group discussion around common challenges, patterns, and failure modes Conversation about approaches to expert review, scoring, rubrics, and iteration Time to continue talking one-on-one or in smaller groups The value of the event comes from being in the room with people who understand that evaluation quality is not just about metrics dashboards. You may hear discussion around questions like: How do you translate expert intuition into criteria a team can actually use? What breaks when non-experts are asked to rate domain-specific outputs? How much structure should an eval rubric impose? Where do human review workflows become too slow or too expensive? How do teams know whether their evals reflect real user expectations? Expect a social atmosphere, but one with substance. The “chai” framing suggests a meetup that is grounded, conversational, and welcoming rather than stiff or overly formal. That makes it a good setting for asking hard questions, pressure-testing your own assumptions, and having the kind of candid exchange that often does not happen in more polished public settings. Why Attend If you work on AI products, model behavior, applied research, quality systems, or domain-specific workflows, this topic is increasingly hard to ignore. Many teams can build demos or ship early features; far fewer have a clear, credible answer to the question of how they know the system is performing well in a high-context environment. This event gives you a chance to sharpen your thinking around that gap. You will leave better able to articulate where evaluation breaks down, what kinds of expertise need to be involved, and how others are handling the tension between rigor, speed, and practicality. You may also get value from seeing that your team is not the only one wrestling with these issues. Problems like expert disagreement, low reviewer bandwidth, unclear rubrics, and context-dependent scoring show up across many domains. Hearing how others frame and manage them can help you avoid reinventing the wheel. There is also a strong networking upside here, especially because the topic attracts people who care about quality in a deeper way. These are often the people asking better questions about reliability, judgment, process design, and what real-world success should mean. If those are the conversations you want more of, this meetup is likely to be a strong fit. Practical Details This is an in-person event in San Francisco, USA, taking place on Thursday, May 7 at 5:00 PM PDT. Being in person matters for a topic like this: the best discussions often come from live back-and-forth, follow-up questions, and spontaneous side conversations with people facing adjacent problems. Plan for a meetup environment rather than a formal conference setup. The tags suggest a blend of community, networking, meetup, and social energy, so you can expect room for both focused discussion and relaxed conversation. A few useful things to keep in mind: Come ready to talk about real evaluation challenges, not just abstract ideas If you have experience working with expert reviewers, rubrics, QA workflows, or domain-specific benchmarks, that perspective will be especially relevant If you are newer to the topic, curiosity and thoughtful questions are enough reason to attend Since it begins in the early evening, it is well suited for local professionals looking to connect after the workday If the phrase “domain expert eval problem” immediately feels familiar, that is probably your signal. This meetup is for people who know the hard part is not just generating outputs, but building confidence that those outputs stand up to expert scrutiny.
Who should attend
This is for you if you care about evaluating AI systems in ways that actually reflect expert standards, real workflows, and real user expectations. - You build or manage AI products and need better ways to judge quality in domain-specific use cases - You work in applied AI, ML, or research and keep running into the limits of generic benchmarks and shallow scoring methods - You design evals, QA processes, or human review systems and want to compare approaches with others facing similar constraints - You are a domain expert, operator, or reviewer who has been asked to assess model outputs and knows how hard it is to make subjective judgment consistent - You lead product, operations, or trust-related work and need a clearer framework for involving experts without slowing everything down - You like meetup conversations that go beyond surface-level networking and get into concrete problems, tradeoffs, and how teams are actually working through them You do not need to have a perfect solution or deep specialization in evals to belong in the room. If this problem shows up in your work, or is about to, you will likely find the discussion useful.