ai-agent

Four Decision Models Shipped in Three Weeks. Choose Wisely.

Four typed-decision models launched in three weeks: Jev, Clef, Strands Decider, and OpenAI's Decisions API. Here's a sourced framework for picking one...

How to Build Reliable RAG Systems?

A RAG demo takes an afternoon. A RAG system that gives correct answers on the thousandth query, from messy documents, for users who ask…Continue reading on Towards AI »

I Split One Agent Into Three. The Plan Never Reached the Executor.

A LangGraph subgraph boundary dropped the plan, and the gain came from re-reading the source, not the plan.Continue reading on Towards AI »

Microsoft-Decision-1: Stop Parsing “Confidence: 0.8”

A 9B model that returns calibrated probabilities instead of prose, with code you can run today.Continue reading on Towards AI »

Dots vs Muse vs Grok Bot vs Claude Cowork for a small business

Always-on AI agents for a 3-person team cost $0 to $375 a month. Dots, Muse, Grok Bot and Claude Cowork compared on price, regions and approvals.

NVIDIA Researchers Argue Your AI Agent Is Overpaying 10–30x.

A position paper says small language models should run most agent calls.Continue reading on Towards AI »

Why Uncle Bob and Matt Pocock Give Code Review Its Own Agent

It’s context load, not fresh eyes. A workflow you can set up in Claude Code today, and a small kata where a tautological test was…Continue reading on Towards AI »

An AI Agent Turned a Net $784K Into $5.3M of Debt. One Diff Catches It.

What Is Jev? What the Tests Show and Who Should Try It

A new model called Jev is built for this kind of job. You give it the ticket and the possible answers, and it returns a choice with a probability, nothing else. A startup called TypeSafe AI released it on September 15.

[Day 28/100] LangGraph Checkpointing: Make Your Agent Survive a Restart

What a checkpoint actually stores, how to move from InMemorySaver to SQLite and Postgres, and how to rewind and fork a run when it goes…Continue reading on Towards AI »

Build a Jev-Style Decision Model from an LLM

Agentic systems make decisions all the time: which tool to call, which category a request falls into, where to route a message. Each of these is a choice from a fixed list that is known in advance. LLMs, however, are text generators.

How to Let an AI Agent Use Your Gmail Safely

AI agent Gmail access without the risk: 8 restricted Gmail scopes explained, a separate agent inbox, drafts instead of sends, and a 1-minute revoke.

Meta Muse Code Wants Your Repo More Than Your Money

Did you know Meta doesn’t just want to build the next AI model? It wants to replace your programming assistant too.Continue reading on Towards AI »

Microsoft Just Shipped an AI Agent Feature Whose Entire Job Is Not Trusting the Agent

Microsoft Just Shipped an AI Agent Feature Whose Entire Job Is Not Trusting the Agent Copilot Studio’s new “Hooks” are a quiet admission that agent judgment cannot be trusted with anything that …

OAuth 2.0 Token Exchange — Laying the Foundation for AI Agent Authorization

OAuth 2.0 Token Exchange — Laying the Foundation for AI Agent Authorization Background In a previous article, I walked through the three most common OAuth 2.0 grant flows: Authorization Code Flow …

The Summer AI Agents Started Knocking on Government Doors

OpenAI’s own agents wandered i⁠nto US and Aus​tralian government‍ websites, b⁠orrowi​ng keys stra​ngers had left​ lying around online…Continue reading on Towards AI »

What If Enzo Ferrari Was Blamed for Something His Car Did? The AI Agent Authorization Problem

AI agents can now make decisions, call tools, change systems, and act on their own. When something goes wrong, who is actually responsible?

Paul Graham says Amazon's AI-agent ban opens the door to a new rival

Graham, the cofounder of the tech VC firm Y Combinator, said Amazon's AI agent restrictions are a great opportunity for rivals. Elon Musk agrees.