iFeeling Daily
Daily curated AI insights you can't miss.
39 Agents, No Framework: Building a Digital Brain for a Manufacturing Company
Rushabh Doshi shared how he built a 39-agent AI operating system called Ira for a traditional mechanical manufacturing company without using any existing frameworks, detailing the complete architecture from document digestion, agent orchestration, immune system safeguards, to nightly dream cycles, and proposed the 'Fork My Brain' enterprise AI delivery model.
Your agent architecture has a half-life of 6 months
Inngest CTO Dan Farrelly shows how to build with durable primitives so architecture trends don't force a rebuild.
AI and Knowledge: Pablo Castro on Microsoft’s AI Knowledge Systems
Pablo leads the AI Knowledge team in Microsoft's CoreAI division, focusing on information understanding and retrieval systems for AI apps and agents.
NVIDIA Nemotron 3 Embed Ranks #1 on RTEB with Open 8B and 1B Models
NVIDIA Nemotron 3 Embed models rank #1 on RTEB, with an 8B flagship scoring 78.5% and 1B variants reducing error rates over 27% vs predecessors.
Don’t Build Agents You Can’t Answer For — Addy Osmani
As AI agents automate more coding, the engineer's core value shifts from code production to accountability, judgment, and system ownership.
OpenAI is shutting down Atlas, but its AI browser ambitions are still growing
OpenAI is sunsetting its Atlas browser but redistributing its agentic browsing features across ChatGPT's desktop app and a new Chrome extension.
The AI Preflight Check: A Memory Architecture for Agents
A memory architecture for AI agents: preflight retrieves the right skill, a local model executes, and a watchdog reads the trail overnight to update the library.
Rollouts as the Core Primitive for Agent Evaluation and Training
Alex Shaw and Ryan Marten argue that rollouts — structured agent-environment interaction traces — should be the core primitive for evaluating, debugging, and training AI agents.
How Evals and Prompts Shape Agent Behavior — Google Team Lessons
A Google team shares how a seed-asset agent for ad creatives taught them that behavior emerges from a loop of prompts, evals, and iteration.