The 5 Papers Behind Every AI Agent Architecture in 2026
Last Updated on July 30, 2026 by Editorial Team
Author(s): Anubhav
Originally published on Towards AI.
ReAct, Toolformer, Reflexion, Voyager, and the framework paper almost nobody opens. You already ship all five, you just never read where they came from.
Nearly every AI agent shipping today traces back to five research papers, and all five came out in the same 11 months. Between October 2022 and September 2023 the field published the reasoning loop, the tool calls, the self-correction, the skill library, and the architecture that ties them together. Then it spent three years turning them into function names you call without reading.

After introducing the idea of a five-paper lineage, the article walks through each work and what survived into modern agent tooling: ReAct establishes the “think, act, observe, repeat” loop and later replaced brittle string parsing with structured function/tool calls; Toolformer demonstrates learning when to use tools (but is largely obsolete in training and single-step form); Reflexion adds retry-with-verbal critique so agents can recover from failures, foreshadowing judge/verification pipelines while highlighting how reflection can also trap models in repeated dead ends; Voyager introduces a durable skill library so capabilities persist across tasks (while its autonomous curriculum mostly didn’t reach production); and CoALA provides the missing blueprint by organizing memory types and a unified decision loop, explaining why frameworks feel like siblings even when they don’t cite the paper. The piece concludes that recognizing these failure modes and components makes debugging and design more diagnostic—naming which paper’s limitation is showing up when an agent loops, miscalls tools, keeps repeating mistakes, or fails to retrieve the right capability.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ AI Engineering For Production — our new book, coming before the end of 2026. Join the waitlist.
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.