2026년 10월 AI 동향

Part 1 Future&Tech

Why AI Agents Work More Reliably When They Remember Their Plans Instead of Rebuilding Them

Instead of replanning from scratch on every run, AI agents are starting to remember the procedures and past experience behind repetitive tasks. Several recent studies point the same way, though each remembers something different.

Part 2 Future&Tech

Do AI Agents' Self-Improvement Gains Hold Up on Tasks They've Never Seen?

Recent studies ask whether the skills and memories AI agents build for themselves carry over to unfamiliar tasks, or whether the agents are being fooled by their own scores.

Part 3 Mgmt&Insight

Verifying AI Output: What Changes When Every Claim Carries Its Evidence, Not a Score

The standard for checking AI results is shifting from a single score to claim-by-claim evidence and sources. Today's papers show what that looks like in agent evaluation, regulatory compliance, tool security, and human-preference rankings.

Part 4 Dev&Data

What Changes When AI Agent Benchmarks Measure the Commands That Actually Run

The scoreboard is shifting from what a model knows about tools to what it can execute and finish.

AI agent benchmarks are moving away from testing what a model knows about tools and toward testing whether the commands it writes actually run and the work actually gets done. As a result, what a score was based on matters as much as how high it is.