Thinking in public.
Perspectives, methodology notes, and field observations from the Deaimer team. We write to sharpen our own thinking — and because the AI data industry is better when practitioners talk openly.
Why calibration sessions matter more than gold sets.
The gold-set-only approach to rater quality is an incomplete picture. Here's what a disciplined calibration cadence actually looks like.
What 248 live workflows taught us about scheduling.
Lessons from running hundreds of parallel annotation workflows — and why the simplest scheduling rule almost always wins.
Rater drift is real. Here's how we catch it.
How we monitor rater agreement over time, what we do when a senior rater starts drifting, and the dashboards that flag it in real time.
The ethics refusal clause — and why we use it.
What our MSA refusal language actually covers, how we make judgment calls, and why this isn't just corporate positioning.
What's actually changing in data operations in 2026.
Three patterns we're seeing across our enterprise and frontier-lab engagements heading into the year.
How to write a useful annotation rubric.
Rubric design is one of the highest-leverage activities in data operations. Here's what separates great rubrics from frustrating ones.
What we got wrong in 2025.
An honest inventory of the mistakes we made, the lessons we took, and what we're doing differently going into 2026.
Why benchmark saturation isn't the whole story.
Public benchmarks are saturating. That doesn't mean evaluation is solved — it means evaluation work is just beginning.
Why we published our labor audit — findings and all.
Transparency is a process, not a PR exercise. What we found in our own operation, what we're changing, and why we shared it publicly.
The consolidation nobody is talking about.
The AI data industry is consolidating — but not in the direction most analysts expect. Here's what we're seeing on the ground.
Evaluation design for agentic systems.
Agentic evaluation is different — multi-step, tool-using, stateful. What we've learned from designing evals for these systems.
How we onboard a new specialist panel in 5 days.
The operational playbook for ramping up a specialized annotator team — whether it's radiologists, attorneys, or CFAs.
Let's make your AI better together.
Tell us what you're training, aligning, or evaluating. We'll map a delivery plan, staffing model, and timeline within one working week.