we have seen many companies launch managed agent products recently. today, we released 𝚖𝚊𝚗𝚊𝚐𝚎𝚍-𝚍𝚎𝚎𝚙𝚊𝚐𝚎𝚗𝚝𝚜 0.8 I have been asked a few times why managed agent frameworks are useful in an era where "code is free". here is my take: generating code is easy, this is a fact. but as a developer, you still need to decide how your system should behave and apply those decisions consistently across your codebase: whose credentials does the agent use? what information can it share? what changes when another person joins the conversation? your auth, memory and channel integrations need to follow the same rules, including as you add features. this is hard to scale without a solid, opinionated foundation I do not think every team needs to solve these problems from first principles. there is value in building on decisions that other people have thought through, implemented and tested MDA is our managed service built on our open source Deep Agents harness. we build those decisions into managed primitives with sensible, configurable defaults, and handle the supporting infrastructure that is why I think Managed Deep Agents should be the default starting point for new agents. start with a foundation that we've thought through, and take on more of the system as your requirements demand it if you hit a limit with MDA, dm me. I want to understand what is missing and see if we can fix it. either way, MDA is built on our open source Deep Agents framework, so if you still need more control, you can move off MDA and use Deep Agents directly with your own integrations and infra re: diagram ~ this is one of those decisions we made: user memory is available in slack dms, but not in shared channels by default. fully configurable btw