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Agentic AI Flywheels

Aurimas Griciūnas· ·12 min read · 0 reactions · 0 comments · 34 views
#ai#engineering#machine learning
Agentic AI Flywheels
TL;DR · WeSearch summary

The article discusses the lifecycle of agentic AI systems, emphasizing the importance of a feedback loop after initial deployment. It outlines the pre-production phase and the recurring improvement cycle known as the Agentic AI Flywheel. The author also highlights an upcoming workshop aimed at teaching AI engineers how to effectively manage and improve their systems using evaluations.

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Hacker News (AI / LLM) files mainly under ai. We currently carry 3,083 of its stories.

Original article
Hacker News (AI / LLM) · Aurimas Griciūnas
Read full at Hacker News (AI / LLM) →

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Record

Original publisherHacker News (AI / LLM)
Canonical URLhttps://www.newsletter.swirlai.com/p/agentic-ai-flywheels
Publication timeWed, 27 May 2026 12:08:01 +0000
Retrieval time2026-05-27T12:22:59.294Z
Last seen2026-05-27T12:22:59.294Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
ClusterNone
Cluster logicNot yet clustered, or no peer story found in the clustering window.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

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WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
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Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Agentic AI FlywheelsThe production loop after your agent ships, and the eval set that grows with it.Aurimas GriciūnasMay 27, 2026151Share👋 I am Aurimas. I write the SwirlAI Newsletter with the goal of presenting complicated Data related concepts in a simple and easy-to-digest way. My mission is to help You UpSkill and keep You updated on the latest news in AI Engineering, Data Engineering, Machine Learning and overall Data space.SwirlAI Newsletter is a reader-supported publication. To receive new posts and support my work, consider becoming a subscriber.SubscribeMost agentic systems ship with a small initial eval set, accumulate production failures the eval set does not catch, and end up getting debugged from forwarded user complaints.

Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News (AI / LLM).

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