The author tests Doubao Work Agent's new local Office editing feature on ICML 2026 paper data, demonstrating automated pivot table creation, chart generation, and PPT style unification without manual formatting, completing a 6500-row Excel analysis in 3 minutes and rescuing a messy presentation.
The author walks through a full equity research workflow on A-share optical communication stocks using Doubao Work's financial data plugin and built-in skills, demonstrating automated hotspot analysis, conditional stock screening, research report digestion, multi-stock financial comparison with formula-driven Excel output, daily monitoring, and a contrarian risk review via the Stock Analyst work partner, highlighting cross-device collaboration and source-cited rigor.
The article reviews Panshi SciencePro, a Chinese AI research platform built on a scientific foundation model with 1.7B papers, offering innovation evaluation, literature analysis, hypothesis generation, simulation, and project management to streamline the entire research workflow.
The author shares a 10-run experiment showing that structured Codex Skills reduce research draft time from 40 to 20 minutes, cut manual corrections from 5–7 rounds to 2–3, and improve first-pass rates by codifying input rules, processing flows, and output contracts for repetitive tasks.
The article argues that investing time in creating Codex research skills is worthwhile only for repetitive tasks like weekly paper tracking, experiment reproduction, and team onboarding, advising researchers to start small, validate with real runs, and prioritize traceability over automation speed.
This guide presents a practical file naming convention (Project_Topic_Date_vVersion_Status) and a five-folder directory structure (00_Description, 01_Materials, 02_Working, 03_Delivery, 99_Archive) to eliminate version chaos, with rules for version increments, Git-based code collaboration, and a 3-2-1 backup strategy for researchers and developers.
In his ICM 2026 talk, Fields Medalist Tao Xue Zhan argues that AI is turning mathematical proofs from scarce, high‑value achievements into abundant, hard‑to‑digest commodities, and he outlines a four‑stage roadmap and concrete safeguards for the community.
The author explains how ten carefully curated AI research skills can handle everything from literature review and experiment design to data analysis, manuscript drafting, mock peer review, and rebuttal preparation, dramatically reducing the repetitive work that normally consumes most of a scholar's time.
Gemini Notebook adds cloud code execution to its AI‑driven document reader, enabling a closed‑loop workflow where evidence, computation, and conclusions are linked, allowing analysts to audit, recompute, and collaborate on research while preserving data provenance and privacy.
AgentSociety² combines literature review, hypothesis generation, experiment design, large‑scale simulation, result analysis, and paper drafting into a unified platform where silicon‑based participants and AI social scientists collaborate, enabling fully traceable, reproducible social science experiments from micro‑behaviour to city‑scale scenarios.
The article shares a six‑step workflow for leveraging Codex in research tasks—read the codebase first, define long‑term AGENTS.md rules, always plan complex changes, verify before coding, start a new session after each task, and never trust the final output without a detailed audit.
The article outlines a six‑step workflow for leveraging Codex in research tasks—starting with reading the codebase, defining clear long‑term rules, planning complex changes, verifying assumptions, resetting the session after each task, and demanding explicit validation output—to make AI‑assisted development reliable and reproducible.
The article surveys AI‑assisted research across the full lifecycle—creation, writing, validation, and dissemination—detailing the capabilities of prompt engineering, retrieval‑augmented generation, training‑free agents and hybrid methods, reporting benchmark numbers, failure modes, and governance challenges that dictate when human oversight remains essential.
Timothy Gowers shows that GPT‑5.5 Pro can solve open additive‑number‑theory problems in minutes, prompting a deep analysis of how AI will reshape mathematical research, PhD training, publishing norms, and the need for new collaborative workflows such as DeepMind's AI Co‑Mathematician.
The author details how they assembled a multi‑agent AI research team on the Moxt platform, defined specific roles, ran a full literature‑review workflow for Harness Engineering, compared it with a prior OpenClaw‑Discord setup, and highlighted observability and scheduling benefits.
The article dissects the karpathy/autoresearch project, explaining its autonomous experiment loop design—single mutable file, fixed 5‑minute budget, read‑only evaluator, and systematic logging/rollback—to show how teams can automate research cycles and continuously improve without manual overhead.
This guide walks graduate researchers through a step‑by‑step workflow—collecting papers with Zotero, translating them via an LLM plugin, generating structured markdown notes, and then using Obsidian’s bidirectional links and Canvas to build a local, visual knowledge graph that ties individual citations into a coherent research map.
