When a team moves from a monolith into microservices and event-driven, asynchronous systems, it inherits a class of problems that used to be someone else's: work that fails halfway through, steps that must not run twice, calls that return before the work is done. Temporal is a durable execution engine that handles a lot of this - you define a multi-step process, and it guarantees the process runs to completion... - Source: dev.to / 7 days ago

Durable execution — the pattern implemented by Temporal, Inngest, Rivet Actors, and now Cloudflare Workflows — treats waiting as a continuation rather than a loop:. - Source: dev.to / 12 days ago

Two specific moves stand out in Duncan's account. The first is durable execution, via Temporal — Mercury replaced fragile cron-and-database state machines with workflow code whose failure semantics are platform-handled (replay, retry, timeout, cancellation). Mercury open-sourced its hs-temporal-sdk, which wraps Temporal's official Rust Core SDK via FFI and provides a Haskell-native API. The dovetail with Haskell's... - Source: dev.to / about 1 month ago

We picked Temporal as the first reference engine on purpose. Temporal has the strictest execution model we know of – a V8 sandbox, determinism constraints, replay-driven recovery. If our port contract holds up against that, easier engines – an in-memory test double, a BullMQ queue, or JSON-first platforms like Inngest or Restate – plug in through the same two interfaces. We're shipping Temporal first; the rest is... - Source: dev.to / 2 months ago

The trick is to find whatever metadata channel the queue already gives you and use that and thankfully, almost every mature queue has one (probably because of this scenario). SQS has message attributes, Temporal has context propagators built into the SDK, and Hatchet (which we use to run our workflows) has a metadata field called additionalMetadata. - Source: dev.to / 3 months ago

We wire everything up with Vision Agents as the voice agent framework, Stream for WebRTC audio and video, OpenAI Realtime for speech in and speech out, Anam so the agent shows up as a face on the video, and Supermemory so answers come from search over your uploaded documents instead of guesswork. The code stays small and most of the behavior lives in one registered function that asks the memory store for relevant... - Source: dev.to / 3 months ago

In this tutorial, we build exactly that kind of AI teammate. Instead of piecing together complex infrastructure (audio pipelines, transcription, NLP, TTS, avatars), we'll use Vision Agents to tie everything together, using Stream's WebRTC APIs, and give the AI both a voice and a human-like video presence using ElevenLabs voice and Anam avatars. The system we’ll create can listen, query Postgres, and respond during... - Source: dev.to / 3 months ago

Stream provides real-time video, audio, and chat APIs with a strong emphasis on developer experience, in-app interactivity, and reliability at scale. Instead of trying to cover every possible engagement feature, Stream focuses on building high-quality, low-latency communication with clean SDKs, polished UI kits, built-in moderation, and consistent cross-platform behavior. Product teams choose Stream when they want... - Source: dev.to / 7 months ago

Do you need more than moderation? Some providers offer additional APIs for real-time communication features, like chat, video, audio, and feeds. This allows you to unify engagement and moderation within the same platform. If you’re already building interactive or community-driven experiences, an all-in-one ecosystem may reduce overhead and simplify your stack. - Source: dev.to / 7 months ago

Stream is a platform that provides APIs and SDKs for developers to build real-time chat, video, and activity feeds into their applications. - Source: dev.to / 7 months ago