AI Agents = LLMs + orchestration Here are the main types of LLMs powering them General-purpose (GPT, Claude) Domain-specific (Legal, Finance, etc.) RAG-based (real-time knowledge) Tool-augmented (API actions) Open-source (LLaMA, Mistral) The game is no
TOOLS
-

Building Production Apps Without Infrastructure Management
By
–
Developers shouldn’t have to spin up infrastructure just to start building. In this webinar, engineers from Databricks and @cursor_ai walk through how to build and deploy a production-ready app without managing infrastructure. You’ll see how to work with serverless Postgres,
-
Using AI and Automations for Notes and Task Management
By
–
this is a brilliant list! personally I have been using codex & computer use heavily to make notes from disparate sources iMessage based automations (if I send a message X do Y) end of day updates to notes and to-do lists – after cross checking with slack, email, calendar
-
OpenClaw Ban Raises Questions on AI Tool Policy Consistency
By
–
OpenClaw is banned via cli as well – why would other tools be allowed?
-
AI Web Browsing Agents: Risks Without Proper Safeguards
By
–
Letting AI Browse the Web for You Sounds Great — Until It Goes Wrong AI browsing agents promise convenience — but without safeguards, they can introduce risks and unexpected errors. Read more https://
bernardmarr.com/letting-ai-bro
wse-the-web-for-you-sounds-great-until-it-goes-wrong/
… #AI #Automation #TechRisks #BernardMarr -

Harnessed LLM Agent Architecture: Intelligence Through Modular Composition
By
–
A harnessed LLM agent.
— Akshay 🚀 (@akshay_pachaar) 18 avril 2026
Most people picture this as a model with tools bolted on. The real architecture inverts that relationship.
The model itself is deliberately thin. Intelligence gets pushed outward, and the harness composes it at runtime.
Three dimensions orbit the harness… https://t.co/MiA6mrH64m pic.twitter.com/tBUHQn4e3NA harnessed LLM agent. Most people picture this as a model with tools bolted on. The real architecture inverts that relationship. The model itself is deliberately thin. Intelligence gets pushed outward, and the harness composes it at runtime. Three dimensions orbit the harness
-
Discussing Claude Apps in Upcoming Talk
By
–
thanks – yeh that’s how i do it but i’m doing a talk showing claude apps
-
Claude Apps SDK for talk demo and Zapier integration
By
–
ofc! this use case is for a talk i’m doing and was trying to show how easy everything is in claude apps is zap connector the sdk also? if so, ill recommend that and show it
-
Building a 3D Asset Generation Plugin for Codex using MCP
By
–
I built a plugin to generate 3D assets directly from Codex, using the latest update that introduces image generation.
— Defend Intelligence (Anis Ayari) (@DFintelligence) 18 avril 2026
It generates an image, calls the Tripo3D API, then starts an MCP server and a local viewer directly inside Codex.
It uses the paid Tripo3D API (12 free… pic.twitter.com/gwZ4dn6eElI built a plugin to generate 3D assets directly from Codex, using the latest update that introduces image generation. It generates an image, calls the Tripo3D API, then starts an MCP server and a local viewer directly inside Codex. It uses the paid Tripo3D API (12 free
-
Claude Desktop App Cannot Install Skills via Command
By
–
drives me mad that claude desktop app (cowork or code) cant install skills if you give it a command codex does
