# lens Published articles for lens. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Profunctor Optics DevFeed: [Profunctor Optics]() Original publisher: [Read original article]() Author: Bartosz Milewski Published: 2026-07-19T11:39:02Z Content type: article Language: en Sources: [Bartosz Milewski's Programming Cafe]() Topics: [Haskell](), [Programming language](), [Programming](), [modules]() Tags: [category-theory](), [haskell](), [language](), [lens](), [mapping](), [modules](), [optics](), [profunctors](), [programming-language](), [tambara-modules]() ### AI overview This article explains profunctor optics through Tannakian reconstruction. It presents optics as a category, describes lenses and their composition in Haskell, and introduces Tambara modules as a representation that simplifies optic composition. ### Source excerpt You may think of Tannakian Reconstruction as an example of redundant encoding. It lets you replace a simple hom-set with a much more complex end that is taken over an entire functor category. Why would anyone want to do it? The answer is simple: composition! Morphisms on the left compose according to the rules of [...] ## How Chainguard monitors a fleet of AI coding agents with Lens DevFeed: [How Chainguard monitors a fleet of AI coding agents with Lens]() Original publisher: [Read original article]() Published: 2026-07-02T00:00:00Z Content type: opinion Language: en Sources: [Chainguard: Unchained]() Topics: [agent observability](), [Artificial Intelligence](), [observability](), [coding](), [monorepo]() Tags: [ai-agents](), [chainguard-agent-skills](), [chainguard-ai-agents](), [chainguard-engineering-blog](), [coding](), [lens](), [observability]() ### AI overview Chainguard describes Lens, a visibility layer for monitoring a fleet of AI agents that open pull requests in a large monorepo. It brings token use, model calls, evaluation results, and agent decisions into view so people can investigate costs, failures, and changes in agent behavior. ### Source excerpt See how Chainguard uses Lens to monitor AI agents in real time with traces, evals, costs, and safeguards that make autonomous coding trustworthy. ## Actegories DevFeed: [Actegories]() Original publisher: [Read original article]() Author: Bartosz Milewski Published: 2026-06-30T11:45:46Z Content type: tutorial Language: en Sources: [Bartosz Milewski's Programming Cafe]() Topics: [Programming](), [Haskell](), [Code]() Tags: [actegories](), [category-theory](), [class](), [haskell](), [lens](), [optics](), [programming](), [types]() ### AI overview This tutorial introduces actegories, explaining their relationship to monoidal categories and their role in programming optics such as lenses, prisms, and traversals. It develops the concepts through Haskell models, including tensor products, unit objects, constraints, associators, unitors, and categorical actions. ### Source excerpt Previously: Kan Extensions in Double Categories. In programming, actegories play a central role in optics: lenses, prisms, traversals, etc. To understand actegories, let's start with the definition of a monoidal category. Monoidal Category A monoidal category is a category equipped with a tensor product. A tensor product is a functor . We assume that this [...] ## Building On-call: Our observability strategy DevFeed: [Building On-call: Our observability strategy]() Original publisher: [Read original article]() Author: Martha Lambert Published: 2024-08-22T15:33:00Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [observability](), [incident](), [Availability](), [User experience (UX)](), [dashboards](), [log management]() Tags: [availability](), [building](), [dashboards](), [engineering](), [health](), [high-availability](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [infra](), [lens](), [logs](), [observability](), [on-call](), [outage](), [post](), [post-mortem](), [reactive](), [slack-incident](), [ux]() ### AI overview incident.io explains how observability supports its on-call product by helping engineers proactively detect degrading systems and react quickly when incidents occur. The article emphasizes that effective observability depends not only on collecting data, dashboards, and logs, but also on making the information easy for engineers to find and use. It presents a user-focused, product-like approach intended to improve adoption and make observability a shared engineering responsibility. ### Source excerpt Our customers count on us to sound the alarm when their systems go sideways--so keeping our on-call service up and running isn't just important; it's non-negotiable. To nail the reliability our customers need, we lean on some serious observability (or as the cool kids say, o11y) to keep things running smoothly. ## A birds-eye view of Arrow: Data Immutability with Arrow Optics DevFeed: [A birds-eye view of Arrow: Data Immutability with Arrow Optics]() Original publisher: [Read original article]() Published: 2022-12-19T00:15:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [Functional programming](), [Kotlin](), [Programming](), [API](), [Code]() Tags: [arrow](), [code](), [functional-programming](), [immutability](), [kotlin](), [ksp](), [lens](), [workshop-learning-programming]() ### AI overview This tutorial introduces Arrow Optics for transforming nested immutable data in Kotlin. It explains how Arrow Optics uses a basic library and a compiler plug-in built with Kotlin Symbol Processing, with annotations generating lenses that combine getters and setters. ### Source excerpt Learn to use Arrow Optics to support working on immutable objects.