# Actor The actor model is a model of computation supporting parallel and distributed computing. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Enterprise Architecture Quietly Depended on Humans in Far More Places Than We Realised DevFeed: [Enterprise Architecture Quietly Depended on Humans in Far More Places Than We Realised]() Original publisher: [Read original article]() Author: flashdba Published: 2026-06-08T14:19:07Z Content type: opinion Language: en Sources: [flashdba]() Topics: [Enterprise Architecture](), [Architecture & Design](), [Artificial Intelligence](), [Actor](), [properties]() Tags: [actor](), [agentic](), [agentic-ai](), [ai](), [architecture](), [cloud](), [databases](), [databases-and-agentic-ai](), [enterprise-architecture](), [inferencing](), [performance](), [properties]() ### AI overview This article argues that enterprise architecture depended on implicit properties supplied by human participants, including predictable workload, intent, accountability, feedback, and limited capacity. It concludes that agentic AI exposes pressure across multiple technical and organisational domains by removing those assumptions simultaneously. ### Source excerpt Enterprise architecture was built around a human actor whose presence provided properties nobody designed and nobody priced. Agentic AI is the first technology to remove those properties simultaneously - and the absence is now visible across every domain. ## Player sessions that survive anything DevFeed: [Player sessions that survive anything]() Original publisher: [Read original article]() Author: Cecil Phillip Published: 2026-05-28T00:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [sessions](), [Actor](), [backends](), [Processes](), [Server](), [Python]() Tags: [actor](), [backends](), [build](), [crashes](), [database](), [distributed](), [how-to](), [python](), [server](), [sessions](), [temporal-concepts](), [workflow]() ### AI overview This article presents a Temporal Python pattern for modeling each multiplayer player session as a durable, uniquely addressable Actor Workflow. The workflow keeps player state, resumes after server failures, coordinates game actions, and uses Continue-As-New to prevent unbounded history. ### Source excerpt Build multiplayer player sessions that survive server crashes. See how to model each player as a durable Actor Workflow in Temporal Python. ## The agentic passive voice. DevFeed: [The agentic passive voice.]() Original publisher: [Read original article]() Published: 2026-03-29T14:30:00Z Content type: opinion Language: en Sources: [Will Larson - Irrational Exuberance]() Topics: [Actor](), [ChatGPT](), [Claude]() Tags: [agentic](), [chatgpt](), [claude](), [model](), [writing]() ### AI overview This commentary humorously proposes calling sentences that attribute mistakes to AI models an "agentic passive voice." It argues that writers should use active voice and avoid unclear attribution when describing model behavior. ### Source excerpt At some point, you will have learned about the passive voice, where the actor in a sentence is unclear. For example, my software didn't compile. That's a good example of the passive voice. However, you might not know the full set of rules, because here are some sentences in the passive voice that you might not recognize: Claude made an error in my writeup. ChatGPT messed up the commitment. Gemini didn't write tests. You might think those are active sentences, but those are in fact examples of the agentic passive voice. The rule here is: whenever the actor in a sentence is a model, then it's a passive sentence. I'm sorry if your grammar instructor never taught you this rule, but this is just the way it works now. This is an important grammatical distinction to make, because I'm increasingly seeing folks say that Claude made a mistake, without recognizing that they're writing unclear, nearly ungrammatical sentences that their grade-school teacher would reject. So please, aspire higher. Write in the active voice, avoiding all passive variants. ## Operation "Trolling Stone": Russia-linked influence activity DevFeed: [Operation "Trolling Stone": Russia-linked influence activity]() Original publisher: [Read original article]() Published: 2026-02-01T00:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [Artificial Intelligence](), [ChatGPT](), [Actor]() Tags: [actor](), [ai](), [chatgpt](), [news](), [openai](), [safety]() ### AI overview OpenAI describes banning ChatGPT accounts linked to "Trolling Stone," a Russia-linked influence operation that used AI to generate social media comments and articles about the arrest of an alleged Russian cult leader in Argentina. The activity involved coordinated users and content published across Facebook, YouTube, Medium, and some Argentine news websites. ### Source excerpt OpenAI banned accounts linked to a previously unreported operation we dubbed "Trolling Stone", using AI to generate comments about an alleged Russian cult leader's arrest in Argentina. ## Durable Digest: October 2025 DevFeed: [Durable Digest: October 2025]() Original publisher: [Read original article]() Author: Temporal Technologies Published: 2025-10-30T00:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [SDKs](), [Ruby](), [Logging](), [audit](), [MCP](), [Actor](), [time tracking](), [clients]() Tags: [actor](), [ai](), [announcements](), [audit](), [events](), [logging](), [mcp](), [ruby](), [sdk](), [workflow]() ### AI overview Temporal's October 2025 newsletter covers Ruby SDK general availability, Server v1.29.0, Eager Workflow Start in public preview, a Langfuse integration, Cloud Audit Logging in public preview, Saved Views general availability, field guidance, an adoption spotlight, AI guides, and upcoming events. ### Source excerpt Temporal's latest updates: Ruby SDK GA, Server v1.29.0, Eager Workflow Start, Langfuse integration, Cloud Audit Logging, and Saved Views. Plus AI guides, and live events! ## Designing a hierarchical Authorisation system DevFeed: [Designing a hierarchical Authorisation system]() Original publisher: [Read original article]() Author: Authorisation Published: 2025-09-20T00:00:00Z Content type: tutorial Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Actor](), [object](), [structure](), [service](), [properties]() Tags: [actor](), [apis](), [billing](), [finance](), [object](), [recursion](), [service](), [structure]() ### AI overview This article explains how to design a hierarchical authorization system for Goiter. It contrasts a flat mapping of users, objects, and actions with a hierarchical model in which groups can have multiple parents and inherit rules. The article notes that recursive parent lookup can reduce rule bloat, while assuming a maximum recursion depth of 10. ### Source excerpt . [Designing a Hierarchical Authorisation System](designing-a-hierarchical-authorisation-system-cover... ## Customer Workflows: Building a loyalty program with Temporal DevFeed: [Customer Workflows: Building a loyalty program with Temporal]() Original publisher: [Read original article]() Author: Fitz Published: 2023-08-03T17:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [Actor](), [fly](), [Code](), [Framework](), [GitHub](), [Go](), [Java](), [Python]() Tags: [actor](), [customers](), [github](), [go](), [how-to](), [java](), [loyalty-account](), [python](), [workflows]() ### AI overview This tutorial explains how Temporal Workflows can represent Actors through a customer loyalty account example. It reviews the Actor Model's requirements--message handling, creating Actors, and maintaining state--and describes how a loyalty account tracks points and rewards. The article includes Go, Java, and Python implementations. ### Source excerpt Discover how Temporal optimizes customer workflows in loyalty programs, managing actors and tasks efficiently to enhance customer engagement and retention. ## Workflows as Actors: Is it really possible? DevFeed: [Workflows as Actors: Is it really possible?]() Original publisher: [Read original article]() Author: Fitz Published: 2023-06-27T22:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [Actor](), [systems](), [Object-oriented programming (OOP)](), [Complex Systems]() Tags: [actor](), [blog-post](), [concurrent](), [design-patterns](), [object-oriented](), [parallel](), [temporal-concepts](), [workflows]() ### AI overview This article introduces the Actor Model and compares actors with objects, focusing on message passing, state, actor creation, and encapsulation. It then explains how Temporal Workflows can be built to behave like actors. ### Source excerpt An overview on how to use Temporal Workflows in the form of an Actor Model ## Why the author stopped using the term "actors" when explaining the Actor Model DevFeed: [Why the author stopped using the term "actors" when explaining the Actor Model]() Original publisher: [Read original article]() Author: Sergey Bykov Published: 2021-05-05T07:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [Actor](), [Concurrency](), [Scalability](), [.NET](), [Java]() Tags: [actor](), [c-sharp](), [concurrency](), [distributed-system](), [java](), [net](), [temporal-voices]() ### AI overview The author explains why he stopped using the term "actors" when discussing the Actor Model, focusing on conflation between local and distributed actors and their differing roles in concurrency. ### Source excerpt While it may have taken me quite some time to get around to answering it, 2020 wasn't an ordinary year by any measure. ## Proofpoint's TA410 Report Shows How Attack Details Can Inform Better Defenses DevFeed: [Proofpoint's TA410 Report Shows How Attack Details Can Inform Better Defenses]() Original publisher: [Read original article]() Author: Adam Published: 2020-06-14T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Threat Research](), [proofpoint](), [Malware](), [Actor](), [Code](), [execution](), [file]() Tags: [actor](), [attacks](), [code](), [commands](), [defender](), [delivery](), [execution](), [file](), [malware](), [proofpoint](), [report](), [research](), [threat-research]() ### AI overview The article praises Proofpoint's report on TA410 attacks against U.S. utilities for its factual analysis and detailed explanation of the attack chain. It argues that details such as malicious macros, file renaming, cmd use, certutil execution, and delivery infrastructure can help defenders design better protections. ### Source excerpt I want to call out some impressive aspects of a report by Proofpoint.