Manager reviews what the AI employee did today
The AI agent logs a daily summary of tasks completed, decisions made, and blockers hit, giving managers a clear picture without digging through logs.
Work Journal
Every employee keeps a dated journal of what it did, decided, and got stuck on, written as it works, not after the fact. Open it from the employee's, team's, or organization's Drive tab to see a day's entries without reading the chat transcript. Entries carry a category (task completed, observation, decision, blocker, learning, or handoff) so you can scan for what changed. It starts on hire with nothing to configure.
Every employee maintains a work journal that logs completed tasks, decisions made, blockers encountered, and planned next steps. It reads like an end-of-day handover: what was done, why it was done that way, and what is coming next. Open any employee's journal and get a clear picture of their output and priorities.
The journal exists at both the personal and team level. Individual journals track each employee's work. The team journal aggregates entries from every member, giving leaders a single view of team activity. If you manage a marketing team of 5 AI employees, the team journal shows you everything they accomplished today without opening 5 separate dashboards.
Journals serve as an audit trail. When you need to understand why an employee made a specific decision, the journal entry explains the reasoning. When you want to verify that a scheduled task actually ran, the journal confirms it with timestamps and output links. Full accountability, zero micromanagement.
Entries are filed, not dumped. Each one lands as a completed task, an observation, a decision, a blocker, something learned, or a handoff, so a full day of work can be scanned in seconds for the two lines that actually matter to you. When all you want to know is what got stuck, you read the blockers and skip everything else.
You read it from the Drive tab, at whichever level you care about: one employee, a whole team, or the entire organization. Entries are dated, one file per day, so a specific Tuesday is a single click away instead of a scroll back through months of conversation. Nothing needs exporting or assembling first.
The journal is deliberately not the chat transcript and not the execution trace. A transcript is everything that was said, and a trace is every step a run took. The journal is what the employee judged worth recording, written as it works rather than reconstructed later, which is why it reads like a handover note from a colleague instead of a log file.
A Daily Log Written by the Agent, Not by You
The Work Journal is a structured daily record that each AI employee maintains automatically. Completed tasks, decisions made, blockers encountered, and next steps planned. It is written by the agent at the end of each working session, so you always have a clear account of what happened without asking.
Each journal entry is date-stamped, searchable, and linked to the tasks and outputs it references. You can scroll back through weeks of an agent's work history in seconds. Not a transcript, but a coherent, structured summary of what the autonomous agent actually did.
Personal and Team-Level Visibility
Every AI employee keeps a personal journal. Managers also get a team-level view that aggregates journal entries across the whole workforce. In a single feed, you can see what every agent worked on today, what is blocked, and what is coming next.
This is especially useful in multi-agent environments where different AI employees are running parallel workstreams. Instead of checking each agent individually, the team journal surfaces the full picture in one place. Agent orchestration made visible.
Journals That Feed the Sprint Review
Work Journal entries are the day-by-day record a team lead reads when writing a sprint review. When your AI employee writes "completed keyword research, blocked on access to analytics dashboard," that blocker is on the record the day it happens rather than at the end of the sprint, and the review that closes the sprint is built from entries like it.
Decisions logged in the journal also give future sessions context. If the agent noted why it chose one approach over another, it can recall that reasoning next time a similar situation comes up. Journals are memory, not just records.
How It Works
Every AI agent writes a daily journal entry logging what it worked on, what decisions it made, and what it completed, without being asked.
At the end of each work session and after every scheduled run, your AI employee writes a journal entry. The entry covers what tasks it worked on, what tools it called, what outputs it produced, and any decisions it made along the way. The journal is timestamped and saved automatically. You can read any day's entry to understand exactly what your agent accomplished without digging through activity logs.
Team leads have visibility into their team members' journals so coordination happens with full context. Journals are also what a sprint review gets written from, giving your AI workforce a reliable memory of its own work history. When you return after a weekend and ask your agent what it worked on, it does not guess. It reads from the journal and gives you a precise answer.
There is nothing to switch on and nothing to maintain. Journaling starts on the day you hire an employee and keeps going whether the work came from you in chat, arrived by email, or ran unattended overnight as a routine. Entries carry a category and a date, so scanning a week for decisions or blockers is a matter of reading a few lines rather than replaying a month of conversation.
Use Cases
Compliance team audits agent activity over time
Every day's journal entry is stored and searchable, providing a complete, date-stamped record of what the AI employee worked on.
Team lead tracks progress across a sprint
Daily journal entries stack into a running log of output, making sprint reviews faster and more accurate.
Founder stays informed on autonomous work
The AI agent writes a plain-language journal at end of day, so the founder knows what was done without reviewing raw execution logs.
Comparison
| Before | After |
|---|---|
| No visibility into what the AI agent worked on day to day. | A structured daily journal gives a clear, plain-language record. |
| Auditing agent activity means combing through raw logs. | Journal entries surface the important events in readable form. |
| Progress gets lost between sprints. | Daily entries create a continuous log from day one. |
| Managers ask the agent what it did, wasting time. | The journal is already there, written automatically each day. |
FAQ
Does the agent write the journal entry or do I need to fill it in?
The AI employee writes its own journal entries automatically after each session. You do not need to fill in anything. The entry covers completed tasks, decisions, blockers, and planned next steps.
Can I read journal entries from multiple AI employees at once?
Yes. The team-level journal view aggregates entries across all employees in your organization, so you can see the full workforce activity in one feed without visiting each employee profile.
How does the Work Journal differ from chat history?
Chat history is a raw transcript. The Work Journal is a structured, agent-authored summary of meaningful work: what was accomplished, what decisions were made, and what comes next. It is designed to be read and acted on, not just archived.
Do journal entries connect to tasks and files?
Yes. Each journal entry links to the task cards it references and to any files saved to Drive during that session. Everything is connected so you can trace from summary to source in one click.
How do I know what my AI employee did each day?
Every AI agent writes a daily work journal, a structured log of what it worked on, decisions made, and outcomes. You can review the journal from the employee's Drive under the Notebook section.
Where do I find my AI employee's work journal?
Open the employee and go to its Drive tab, where journal entries are listed by date, one file per day. The same view exists at team and organization level, so you can read one employee, a whole team, or everybody in a single place.
What kinds of entries show up in the work journal?
Each entry is filed under a category: a completed task, an observation, a decision, a blocker, something learned, or a handoff to someone else. That lets you scan a day for exactly the kind of update you care about, such as reading only the blockers when you want to know what is stuck.
Do I need to set up the work journal before my AI employee starts using it?
No. Journaling begins the day you hire the employee and needs no configuration, no template, and no reminder from you. It records work that came from chat, from email, and from routines that ran while you were away, all in the same dated entries.
I come in every morning and read my agent's journal entry. It is a better morning brief than anything a human assistant has ever prepared for me.
Where Work Journal fits
Work Journal is part of Where their work lives.
Your AI agents manage their own workspace. Scheduled tasks run daily, weekly, or on custom cron cadences. A built-in kanban board tracks what is in progress. Every document lands in a personal Drive. A daily work journal logs decisions, outcomes, and next steps automatically.
- Where their work lives: Where your employees organize their work.
Read the guide
More in Workspace
- Move a Team Member to the Bench: Every workspace has one Bench: a holding area for employees who are not currently on a working team. Remove someone from a team, or delete the team itself, and they land back on the Bench automatically, fully intact and ready to be reassigned. Nothing about them is deleted; only their team membership changes.
- Task Board: A kanban board that tracks what every AI employee is working on, in Backlog, To Do, In Progress, and Done columns. Employees create their own task cards when they do real work, and you can create cards to assign work directly. View it per employee, per team, or company-wide, and it updates live as work moves.
- Set Your Employee's Working Hours: Set how often each employee checks its board and acts on its own, from every 5 minutes up to monthly, without you asking each time. New hires start with a default hourly check-in that you can tighten, stretch, or turn into a specific daily time. The employee pauses itself automatically when there is nothing to do, it is onboarding, or credits run out, and picks back up on its own once that clears.
- Task Comments: Comment directly on a task, Drive file, sprint, CRM contact, or notification, and @mention the person, team, or AI employee who should act on it. The mention lands as a bell notification for a person or a direct work request for an employee, both replying in the same thread. Turn any comment into a tracked task in one click, so feedback never gets lost in a side channel.
- CRM: Every business runs on a CRM, the shared book of the people and companies it deals with. Sistava builds one in, and your AI employees run it for you. They add a prospect the moment one comes up, keep contacts current, open deals and move them down the pipeline as they progress, and write notes so nothing is forgotten. You get one clean place to see who you know, what's in flight, and what it's worth, without paying for a separate CRM.
- Sales Pipeline: Your deals live on a pipeline board, the same shape as your task board: a column for every stage, New, Screening, Meeting, Proposal, Customer, and a card for each deal showing its value and the company behind it. As a deal gets closer to won, it moves down the board. Your AI employees keep the pipeline current, opening deals, moving stages, and updating amounts, so you always know what's in flight and what it's worth, at a glance.
- Let Your Employee Use Any Desktop App: Your employee controls your actual desktop, not just a browser tab. It clicks, types, manages files, and runs terminal commands in real applications on your machine, the same way you would sitting at the keyboard. It works through the free Desktop Companion app and covers native software, file management, and shell tasks in one capability.
- Let Your Employee Work with Local Files: Connect the Desktop Companion app and your employee can read, write, list, and search files on your own computer, scoped to your home directory. Ask it to open a config, tidy a folder, or find every CSV in a project, and it works the files directly instead of asking you to paste their contents into chat.
- Let Your Employee Run Terminal Commands: Once you pair the Sista desktop app, your employee can run real shell commands on your machine: git, npm, brew, ls, grep, and anything else you'd type yourself. Commands run as your own user with no privilege escalation, and a hard-coded blocklist rejects destructive patterns like rm -rf /, disk formatting, or piping a remote script into a shell before they ever execute.
- Let Your Employee See Your Screen: Your employee looks at your actual screen and works from what it sees, not just an API. It captures your desktop through the Sista desktop app, reads the pixels the same way you would, and can click, type, and scroll based on what it finds. That covers any app you have open, including native software, dashboards, and design tools that never had an integration.
- Employee Drive: Every document, generated image, video, screenshot, and daily work log an employee produces lands automatically in its Drive, no saving required. Browse it per employee, per team, or company-wide, as a searchable flat grid or as folders. Files preview inline, from PDFs and spreadsheets to code and video, so you rarely need to download something just to read it. Every update becomes a numbered version that you can preview or restore without losing the original file.
- Company Drive: Every employee keeps its own Drive, but you shouldn't have to open ten employees to find one file. Company Drive rolls every employee's Drive into one company-wide view: every document, transcript, and deliverable your whole workforce has produced, browsable and searchable from one tab.