Write the problem hypothesis
For [specific user], completing [job] is difficult because [missing capability], causing [measurable consequence].
You can name one user, one situation and one measurable consequence without proposing a feature.This page is preserved so old links and saved research still work. Verify the original GitHub Issue before taking action, or choose a current signal from Opportunity Radar.
Browse current opportunities →[RFC] Evaluation-calibrated adaptive KL for online policy updates
Evidence observed in Human-Agent-Society/reef, a Agent Infrastructure project.
3 comments1 positive reactions11 days openProject Radar 91
enhancementarea: trainingRFCstatus: ready
Browse current opportunitiesArchived brief · verify the original Issue
REPEATED ACROSS 8 PROJECTS
Related friction appears in 8 independent repositories. This is stronger than one backlog item, but still requires direct user validation.
Project strength and demand confidence are measured separately.SOURCE EVIDENCE
Read original GitHub Issue ↗Start with what users actually said
Reporter context: Primary area Training and runtime Summary and decision to make Add an opt-in, bounded adaptive-KL controller whose inner loop stabilizes online policy updates and whose outer loop is calibrated by held-out evaluation. The smallest decision is whether Reef should expose a controller/evaluator contract that can adjust…Excerpted from the public Issue. Read the complete thread before interpreting it.
Recruit: Recruit teams with live traces, tool calls or deployment constraints from a real agent workflow.
Guardrail: Test observable state transitions, permission boundaries and recovery from partial failure.
Interview five agent-platform engineers or technical operators
- When did you last need this?
- What outcome were you trying to reach?
- What did you use instead?
- How often does this occur?
- What commitment would prove it matters?
Run the smallest experiment
Deliver the outcome manually or with a narrow prototype before building a reusable feature.
A user completes the real workflow and commits time, data, distribution or budget to repeat it.Test observable state transitions, permission boundaries and recovery from partial failure.Make a build decision
- Build: repeated pain and active commitment
- Narrow: pain is real but the audience or job differs
- Stop: weak frequency or no behavioral proof
Why this brief exists
Information has value only when it changes action. This page turns one public signal into a bounded validation exercise. It is a research aid, not proof of demand, investment advice or a product recommendation.