Thanks! That framing is exactly how I started seeing it too. Once memory, routing, and multi-channel sit in one place, the workflow stops feeling like a script and starts feeling like an environment the agents actually live in.
AGENTS
-
AI-Generated Workflow Structures and Intelligent Branching Logic
By
–
Yeah, Mothership generated the structure from a prompt. For branching, it picks the right block (router for classification, condition for if/else, parallel for fan-out) and wires them up. I usually tweak the routes and prompts after, but the skeleton holds up surprisingly well.
-
Dual Memory Architecture: Short-term Manager and Long-term Supabase Retrieval
By
–
Hey, there are two memory layers running in parallel. Short-term lives on the manager agent (keyed to the user). Long-term embeds each turn into Supabase and pulls relevant past context back before the model sees the new message. State lives outside the model, so swapping
-
Mistral Vide now in Le Chat, new Work Mode preview
By
–
Users can now use Mistral Vide directly in Le Chat!
— 🚨 AI News | TestingCatalog (@testingcatalog) 29 avril 2026
Besides that, Le Chat got a new Work Mode in Preview: an agent that can handle complex tasks across connected tools. https://t.co/XQn3Uo9TPr pic.twitter.com/Kin0tKjhFuUsers can now use Mistral Vide directly in Le Chat! Besides that, Le Chat got a new Work Mode in Preview: an agent that can handle complex tasks across connected tools.
-
Hermes AI Agent: From Concept to Functional AI Agent
By
–
Hermes AI Agent isn't an overnight success. It's the gap between a concept and something that ACTUALLY WORKS. An Agent with skills that grows with you.
-
Deep Agents Launches Per-Model Harness Profiles Feature
By
–
Until today, Deep Agents shipped with a single set of prompts, tools, and middleware aimed to work well across all Large Language Models. With the launch of harness profiles, you can now control these parameters on a per-model basis.
-
9 Steps to Build Functional AI Agents from Scratch
By
–
How to build AI agents from scratch (9 steps): 1. Purpose & scope 2. I/O schemas 3. System instructions 4. Reasoning + tools 5. Multi-agent orchestration 6. Memory & context 7. Multimodal 8. Structured outputs 9. UI / API Ship agents that do work, not just talk.
-
The 8-Layer Architecture of Agentic AI Explained
By
–
The 8-Layer Architecture of #AgenticAI
by @Python_Dv #AI #LLM #ArtificialIntelligence #MachineLearning #ML -
Deep Agents: Optimizing Performance Across Model Families
By
–
great deep dive into how we get deepagents to work well with different families of models
-
Replit Agent Monitors Production Apps, Fixes Issues Automatically
By
–
Building apps is easy- keeping them running isn’t
— Replit ⠕ (@Replit) 29 avril 2026
Introducing Replit Application Monitoring
Replit Agent now watches your app in production, investigates issues, and helps fix them- so you don’t have to pic.twitter.com/NP8blat8awBuilding apps is easy- keeping them running isn’t Introducing Replit Application Monitoring Replit Agent now watches your app in production, investigates issues, and helps fix them- so you don’t have to