Kubernetes Austin’s Post

Very informative with clear step-by-step path. The router, state machine, and “autonomous agent” could be done with Double Deep Q-Network (DDQN): "First is just code - everything is hard coded. Next is just a single LLM call. Some data preprocessing before and/or after. Next is a chain of LLM calls. This sequence can be either breaking the problem down into different steps, or just serve different purposes. After that, a router. Prior to this, you knew all the steps the application would take ahead of time. Now, you no longer do. The LLM decides which actions to take. This adds in a bit more randomness and unpredictability. The next level is what I call a state machine. This is combining an LLM doing some routing with a loop. This is even more unpredictable, as by combining the router with a loop, the system could (in theory) invoke an unlimited number of LLM calls. The final level of autonomy is the level I call an agent, or really an “autonomous agent”. With state machines, there are still constraints on which actions can be taken and what flows are executed after that action is taken. With autonomous agents, those guardrails are removed. The system itself starts to decide which steps are available to take and what the instructions are: this can be done by updating the prompts, tools, or code used to power the system."

🧠What is a "cognitive architecture"? This is a term we've been using a bunch recently. All credit for coming up with it goes to Flo Crivello We tried to write down a bit what exactly we mean by this & how to think about and explore different options here https://lnkd.in/gwyTyUdP

- Modular Architecture - Cosmos Network - EVM Engine Is what shapes CrossFi Chain! Message me for access to the full talk. #scalability #security #L1 #modular #cosmos #ethereum #evm #futureproof #blockchain #crossfi

Learn how Signals shape a pull-based architecture with Matthieu Riegler! 👉 https://lnkd.in/eHK3BMBE #ngbe

🛠️ Learn how Signals shape a pull-based architecture with Matthieu Riegler! 👉 https://lnkd.in/eHK3BMBE #ngbe

The Gigamon VÜE community page just got a glow up 💁♀️ Introducing our Zero Trust group! What to expect: ⭐ #ZeroTrust architecture updates ⭐ Best practices ⭐ Latest news Get all your Zero Trust questions answered today: https://ow.ly/qgiP30szPUK

From Hagia Sophia to Ayasofya: Architecture and the Persistence of Memory The Met https://lnkd.in/gU4zDhnk

The Gigamon VÜE community page just got a glow up 💁♀️ Introducing our Zero Trust group! What to expect: ⭐ #ZeroTrust architecture updates ⭐ Best practices ⭐ Latest news Get all your Zero Trust questions answered today: https://ow.ly/R8z030szW3m

Some good stuff in these thoughts on scalable architecture, and highly aligned with my approach. My take… being event driven then event sourcing entities and materialising views lends itself to great scale, and can also result in a great user experience if propagated to the front. Being able to consume events at the pace the consuming services can go is important for scaling. Immutable logs with flexible forms of compaction are key for managing storage and controlling the latency of sourcing events from scratch, and simpler to program for instead of snapshots. Also, events are the closest thing to the end user’s language we find. So there’s that additional, and perhaps most crucial benefit. I see a lot of this mentioned in the slides, so restating only as my own summary based on my experiences. One final thing: scale isn’t about running at scale on day 1; it’s about enabling your system to evolve should your project be successful. Engineering scale encompassing these ideas doesn’t cost though, so there’s no real reason to avoid being event driven at the core.

The Gigamon VÜE community page just got a glow up 💁♀️ Introducing our Zero Trust group! What to expect: ⭐ #ZeroTrust architecture updates ⭐ Best practices ⭐ Latest news Get all your Zero Trust questions answered today: https://ow.ly/eEVe30szQpY