Heavybit Skill
AI Observability
Continuous validation and production monitoring for AI systems. Covers the unique challenges of observing non-deterministic outputs, bridging technical and business metrics, and connecting observability data to code and user experience. Drawn from practitioners at Deepchecks, PlayerZero, and others.
Built from what these operators shared
- +16
AI Observability
Built from twenty-one library resources
What a skill is
A skill is a set of working instructions your agent loads when you need it, built from the strategies operators shared in the Heavybit Library. It guides the work and you still do it. Heavybit reads and approves every skill before it ships, and keeps updating skills as new content enters the Library. Skills are plain text, so you or your agent can read any skill in full before acting on it. Your agent decides how to apply a skill, so check its work; if a skill gets something wrong, ask your agent to report it or email platform@heavybit.com.
Connect your agent
- Add the endpoint below to your harness: Claude Code, Codex, Claude, Cursor, ChatGPT, or another that supports MCP.
- Sign in to your Heavybit account with Google or GitHub when your agent asks. It's free, and your first sign-in creates the account.
- Tell your agent what you're working on. It finds the right skill, or you can ask for one by name.
MCP endpointhttps://crucible.heavybit.com/mcp
Built from the Heavybit Library
The operators behind this skill shared what they know in these talks, podcasts, and articles. Every one is free in the Heavybit Library.
- Podcast
Evaluating LLM-based Apps with Shir Chorev of Deepchecks
JUN 20, 2024With Shir Chorev
In Episode 71 of o11ycast, Jessica Kerr and Austin Parker sit down with Shir Chorev to delve into the nuances of incorporating Generative AI into applications and testing the outcomes. Shir shares her journey from a data scientist to founding Deepchecks,…
O11ycast · Ep. 71
Evaluating LLM-based Apps with Shir Chorev of Deepchecks
Listen40 MIN
- Podcast
Augmented Coding with Kent Beck
APR 30, 2025With Kent Beck
In episode 80 of o11ycast, Ken Rimple and Jessica Kerr chat with Kent Beck about the emerging world of AI-assisted coding. Beck shares his experiences with "augmented coding," discussing the benefits, challenges, and the evolving relationship between…
O11ycast · Ep. 80
Augmented Coding with Kent Beck
Listen39 MIN
- Podcast
Putting LLMs to Work with Liz Fong-Jones and Phillip Carter of Honeycomb
DEC 12, 2023With Liz Fong-Jones and Phillip Carter
In episode 2 of Generationship, Rachel Chalmers speaks with Liz Fong-Jones and Phillip Carter of Honeycomb. Together they explore use cases for LLMs, insights on navigating AI hallucinations, the tradeoffs between prompt engineering and fine-tuning, and the…
Generationship · Ep. 2
Putting LLMs to Work with Liz Fong-Jones and Phillip Carter of Honeycomb
Listen36 MIN
- Podcast
Rethinking AI Evals with Adam Hevenor
DEC 11, 2025With Adam Hevenor
On episode 27 of Open Source Ready, Brian Douglas and John McBride speak with Adam Hevenor, creator of Vibecheck. Together they explore the fundamentals of evals, how teams can run structured experiments across model variations, and why cost-efficient design…
Open Source Ready · Ep. 27
Rethinking AI Evals with Adam Hevenor
Listen40 MIN
- Video
AI-First Organization Design feat. Raza Habib
SEP 24, 2025With Raza Habib
Raza Habib argues that successful LLM-powered products depend far more on people, evaluation, and product practices than on model size alone.
Video
AI-First Organization Design feat. Raza Habib
Watch23 MIN
- Article
Why On-Device Inference Needs Custom Observability
AUG 25, 2026With Andrew Park
Founder Chris Karani explains how hardware state becomes part of the application state when inference goes on-device.
Article
Why On-Device Inference Needs Custom Observability
Read13 MIN