@i5ting: 实现数字员工三个途径 1,阿里腾讯那种,跑docker里,开各种权限,它局限在于docker,能解决二成需求就不错了。我不喜欢这种 2,基于im,把agent放到联系人里,比如bloome这种,这个跑在pc里,和宿主共用一个环境,上下文等…

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摘要

在推文线程中讨论了三种数字员工实现途径:运行在Docker中的、基于IM的代理(如bloome)、以及基于数字分身的方案(如WisMe.ai),并介绍了WisMe.ai作为一款个人AI知识库和阅读助手的产品功能。

实现数字员工三个途径 1,阿里腾讯那种,跑docker里,开各种权限,它局限在于docker,能解决二成需求就不错了。我不喜欢这种 2,基于im,把agent放到联系人里,比如bloome这种,这个跑在pc里,和宿主共用一个环境,上下文等,交互都非常方便,这种日常帮助非常大,一半以上。 3,基于人的数字分身,你看什么做什么它都感知,蒸馏,类似http://wisme.ai。这个就是蒸馏你自己,此时如果它被当成agent,出现在im里,才是最真实最强大的。
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实现数字员工三个途径 1,阿里腾讯那种,跑docker里,开各种权限,它局限在于docker,能解决二成需求就不错了。我不喜欢这种 2,基于im,把agent放到联系人里,比如bloome这种,这个跑在pc里,和宿主共用一个环境,上下文等,交互都非常方便,这种日常帮助非常大,一半以上。 3,基于人的数字分身,你看什么做什么它都感知,蒸馏,类似http://wisme.ai。这个就是蒸馏你自己,此时如果它被当成agent,出现在im里,才是最真实最强大的。


WisMe.ai — Your personal AI knowledge base & reading assistant

Source: https://wisme.ai/en WisMe.aiPERSONAL KNOWLEDGE OS · β

VOL. 01 · ISSUE 04 · SPRING 2026§ PROLOGUE

CHROME EXTENSION · PRIVATE BETA

What you read, becomesyou.

A quiet companion that reads what you read, and weaves it into a knowledge of your own.

WisMe.ai is an AI research companion that lives in your browser. Itquietly recordswhat you read each day, distills what is worth remembering, builds your personal knowledge graph, and keepscollecting, researching, and connectingwhile you sleep.

12,847

pages recorded

across private beta

3.2M

knowledge nodes

extracted & linked

97%

recall accuracy

on user-marked items

your.graph / live

● RECDAY 1/7

AI Systems

+ NEW NODE

“Zettelkasten” captured from arxiv.org

∞ LINK DISCOVERED

RAG ↔ Long-term Memory

§ 01HOW IT WORKSFOUR QUIET ACTS

Not another note app. AnAI that reads with you.

“Knowledge should accumulate like compound interest — without compound effort.”

— DESIGN PRINCIPLE

STEP 01Observe

REC

Observe

The extension runs quietly in the background and records the pages you actually dwell on, revisit, and scroll. Noise is filtered out.

A quiet observer. Only pages you actually read — measured by dwell, scroll, re-visits.

STEP 02Distill

ENTRY · 04.17

Distill

Every night the AI reads your day, extracts key concepts, claims, data, citations, and writes a structured “daily knowledge entry”.

Each night, AI re-reads your day and extracts concepts, claims, data, citations.

STEP 03Weave

Weave

New entries are woven into your graph. The AI finds cross-day and cross-domain links, surfacing neighbouring ideas you might have missed.

Entries weave into your graph. Cross-day, cross-domain connections surface as you sleep.

STEP 04Research

?

Research

Give it a goal and the AI searches the web, traces citations, compares viewpoints, and writes the research report that’s still missing.

Give it a question. It searches the web, chases citations, writes the missing piece.

§ 02FEATURESEIGHT AFFORDANCES

Don’t change how you read — just make readingthicker.

01/ 08Silent Capture

Silent Capture

The extension recognises pages you actually read and ignores the fleeting noise.

02/ 08Interest Radar

Interest Radar

The AI infers what you’ve been focused on recently and flags important items you keep skipping.

03/ 08Daily Digest

Daily Digest

Delivered before 6 am the next morning: a distilled “what you read” with key points, new concepts, loose threads.

04/ 08Living Graph

Living Graph

Concepts, papers, people, events auto-connect. Trace by time, domain, or source.

05/ 08Serendipity

Serendipity

Rediscover a passage you read three months ago that happens to answer today’s question.

06/ 08Research Agent

Research Agent

Hand it a topic; the AI searches, compares, summarises, and returns a cited report.

07/ 08Web Reach

Web Reach

When your library lacks a piece, the AI crawls arxiv, Wikipedia, and domain sites to fill it.

08/ 08Secure by Default

Secure by Default

Data is encrypted in transit and at rest; common sensitive fields are redacted before storage.

§ 03THE LIVING GRAPHHOVER TO EXPLORE

AI SystemsRAGAgentsLong-term MemoryPKMZettelkastenKnowledge GraphEmbeddingsOntologySerendipityCitation NetSummarization

FIG. 03 — A ONE-WEEK SLICE OF YOUR GRAPH↓ DRAG · CLICK · FILTER

Every node carries aprovenance.

Click a node and you see: when and from which article and passage it was extracted; which neighbours it links to; and a one-line “why it matters” generated by the AI.

Nodes

concepts · people · papers · orgs

3,247

Edges

typed: cites, contradicts, extends, …

9,812

Sources

arxiv · ssrn · blogs · twitter · books

412 sites

Clusters

auto-detected by embedding density

27 themes

§ 04DAILY DIGESTHOVER ITEMS FOR DETAIL

A morning brief of what youread yesterday.

Like a personal Economist — but every item comes from your own reading yesterday. It keeps what is worth remembering, nudges you on what’s unfinished, and surfaces connections you may have missed.

DELIVERED BY 6 AM DAILY VIA EMAIL · BROWSER · API ~3 MIN READ · 8–12 ITEMS

THE DAILY · VOL. 214

Thursday, April 17

14 PAGES READ

est. 2h 18m · 6 domains

HEADLINE INSIGHT

“The three papers you read today share an unspoken premise:memory is reconstruction, not storage. This echoes the Tulving 1972 piece you read in March.”

GENERATED FROM · arxiv:2504.11203 · 2504.10998 · sciam.com

NEW CONCEPTS · 4

01

Reconstructive MemoryHIGH

Memory is active reconstruction, not passive replay

arxiv:2504.11203

02

Semantic DriftMEDIUM

Meaning of a concept drifts across a corpus

acl anth.

03

Epistemic HumilityMEDIUM

A deliberately trained cognitive humility

lesswrong

04

Hippocampal IndexingHIGH

Hippocampus as an index to memory — a hypothesis

nature

UNFINISHED · 3

The Scaling Hypothesis, Revisited

Making It Stick, ch. 7 — Meta-organization of knowledge

Memory, Attention and Prediction

§ 05RESEARCH AGENTLIVE DEMO

Hand it a question; it comes backunderstanding.

The agent first reads your existing library, then decides what else it needs externally. It chases citations, compares viewpoints, builds timelines, and delivers a cited, verifiable report you can keep questioning.

ASK THE RESEARCH AGENT

DEPTH: DEEP · SOURCES: 8–12 · ETA: ~3 MIN

RESEARCH.TRACE · LIVE

○ IDLE

PLAN

Decompose into 4 sub-questions and plan the search path

RECALL

Search your existing library

EXTERNAL

Launch external search & crawling

SYNTHESIZE

Compare viewpoints; identify consensus and divergence

WRITE

Draft a cited report

SECURE BY DEFAULT

Your reading, should belong only toyou.

All data is encrypted in transit and at rest; common sensitive fields are redacted before storage. You can permanently delete your data at any time.

READ THE PRIVACY CHARTER →

OUR COMMITMENTS

01End-to-end encryption in transit & at rest

02Automatic redaction of sensitive content

03Permanent delete on request

04SOC 2 & GDPR aligned

§ 06PRICINGSIMPLE · TRANSPARENT

Pick the pacethat fits you.

Free includes 50 credits and a daily Lite report, enough to start capturing and running lightweight page conversations. Pro includes 1,000 monthly credits for AI chat, Workbench nodes, and Skills; daily reports are included in the subscription.

Start accumulating

Start accumulating.

  • →Unlimited browser extension
  • →50 credits every month
  • →Daily Lite report
  • →Usually enough for 100+ lightweight page conversations

Let reading compound

Let reading compound.

LIMITED OFFER19\.9014.50USD

/ month

  • →Everything in Free
  • →1,000 credits every month
  • →AI chat, Workbench nodes, and Skills consume credits
  • →Daily report cost is included, no extra credits charged
  • →Knowledge graph and long-term history retention
  • →Cancel anytime; access remains until period end

Autonomous research, always on

Autonomous research, always on.

$100.00USD

/ month · tentative

  • →Everything in Pro
  • →Higher monthly credit allowance
  • →Multimodal generation allowance
  • →Automated research workflows
  • →Priority queue
  • →Team and heavy research support

USD / CNY PRICING · BILLED MONTHLY · CANCEL ANYTIMEEDUCATIONAL / NONPROFIT DISCOUNTS AVAILABLE →

§ CODA

Start letting your reading actuallyaccumulate.

Install the extension. Close this tab. Read as you always do. See what you’ve become in one week.

NO CREDIT CARD · CHROMIUM · EDGE · ARC · BRAVE

yan5xu (@yan5xu): 昨天和微软的朋友聊AI employee,讨论到了数字分身。我自己的看法,数字分身可以是AI employee的一部分,但不能完全等价。当一个事情,足以改变就有的生产方式,组织结构,才能够称上革命。按照现在组织架构给每个岗位构建数字分身。显然是被当下给局限了。

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