TL;DR
Offloop is an AI-native Slack alternative built for teams that want agents to own work. Ask an agent to prepare a release, and it can check GitHub for blockers, coordinate with other agents in the same channel, and bring decisions back to the team when it needs human input. It can reuse the team's release checklist and remember why a change was deferred when it comes up again. Slack is a good fit when people coordinate the work in channels and use Slackbot or connected apps for specific tasks.
We believe AI agents already outperform humans at many tasks. We built Offloop as an AI-native Slack alternative for teams that want people and agents working side by side.
There's no shortage of mature team chat apps. Few were designed for people and AI agents to do real work together.
Everyone on our team is a heavy AI user. On average, we each spend about $1,000 a month on AI agents.
The more we used them, the more we felt that Slack wasn't the right place for people and agents to work together. Its approach to context and interaction still centers on people chatting with each other, with agents coming in as apps. That foundation makes it hard to build the full agent harness we wanted. We also prefer paying for the AI we actually use over buying a subscription for every seat.
Lauren Tan (@poteto) shared how she used Grok Bot and Cursor to run a product release. She set up two bots in Slack, one for releases and one for engineering. The release bot checked with the developers for blockers and organized several agents to test the release. When they found issues, the engineering bot took over the fixes. Lauren decided which fixes to include and which to save for the next release. Original post
Anthropic also redesigned source control for agents. As agents took on more development work, its Git infrastructure struggled to keep up with the volume of code. Anthropic built Scion and moved its main repository from Git to the new system. Anthropic's write-up
So we built our own AI-native Slack from scratch. We designed Offloop's team chat and agent execution system together. Our goal is to help any team work like the best teams in the world.
Offloop vs Slack: Two Approaches to AI Agent Collaboration
| What to compare | Offloop | Slack |
|---|---|---|
| Team chat design | Built for people and AI agents to work as one team | Built for people to communicate and organize work through apps |
| The agent’s role | A digital employee that takes on work like a human teammate | An app or bot that people connect and call on |
| How work moves forward | People set the goal. Agents plan the work and reach out to teammates or other agents as needed | People organize the work and use apps or preset workflows to run each step |
| How people participate | Agents ask for a decision when they need one, then continue the work | People start, review, and coordinate the work before handing the next step to an app |
| How the team improves its methods | Agents turn experience into skills, workflows, and memory they can reuse | The team records its methods in app instructions or preset workflows |
| Pricing | Free to start with 200,000 workspace credits (no card). Individual is $99 a month and Team is $999 a month, with no per-seat fees | Free is $0. Pro is $7.25 per person per month. Business+ is $15 per person per month. Contact sales for Enterprise+ |
Slack prices are in USD. The Pro and Business+ rates shown are monthly equivalents with annual billing. Slack pricing
Who Is Offloop For?
If your team uses AI agents every day and people still spend time assigning tasks, passing context between agents, and chasing updates, we built Offloop for you.
It's especially useful for small teams that work across functions. A product launch involves product, engineering, and go-to-market teams. A change in any one area affects everyone else's work. Offloop lets agents take part in that coordination, own whole tasks, and build experience as they work with the team.
The more work you can hand to agents, the more attention your team can give to questions worth discussing and decisions worth making. That's the idea behind Offloop's AI-native team chat.
How Multi-Agent Collaboration Works in Offloop and Slack
Imagine a team preparing a product release. Engineering progress lives in GitHub, user feedback comes in on X, and the team decides what goes into the release. The agents need to work with their teammates to keep the release moving.
Slack: The team designs the process, then apps run it
Slack connects to external tools and offers Workflow Builder for automations. Coordinating several agents through a release still takes considerable design and setup.
If a GitHub issue blocks the release, for example, the team needs to decide in advance which agent investigates, which one fixes it, how the fix gets reviewed, and when to ask the release lead for a decision. Slack provides the chat and automation. The team sets up the coordination in Slack or builds it into an external agent system.
Preset workflows follow the steps and conditions you've configured. Real work often takes an unexpected turn. A fix might change how a feature works, or new feedback on X might change what needs to ship first. If the workflow doesn't cover it, someone has to check what's been done, work out what happens next, and change the setup.
An automation designed to save time can end up giving people another process to maintain and repair.
Offloop: Agents work independently as part of the team
In Offloop, you can connect GitHub and X, give the agent the access it needs, and ask:
“Get this release ready. Check GitHub for blockers and use the feedback on X to decide what to tackle first. Contact the engineering agent directly if you need help, and come to me for decisions about what goes into the release.”
The agent can organize the work into a workflow, hand an issue to the agent responsible for the fix, and arrange a review. If something changes midstream, it can adapt to the goal and contact teammates directly when it needs help.
Suppose a small fix would change how existing users do something. The agent can explain the impact and recommend a course of action: “This fix would change how the feature works for users. I'd save it for the next release and ship the part that leaves the interaction as it is. Should I go ahead?” Once the release lead decides, the agent continues.
Offloop agents also learn how their teammates work. If the release lead usually wants to review changes that affect the user experience, the agent can learn to ask in future releases and carry that experience forward in its memory, skills, and workflows.
In Offloop, an agent is part of the team. Give it a goal and it can work independently, proactively collaborate with teammates, and stay responsible for getting the work done.
Estimated effort for one product release
| What to compare | Slack with external agents or preset workflows | Offloop |
|---|---|---|
| People involved | 8 | 3 |
| Agents involved | 3 | 3 |
| Coordination messages sent by people | 480 | 24 |
| Coordination messages per person | 60 | 8 |
| Total staff hours | 48 hours | 4 hours |
| Time spent per person | 6 hours | 1 hour 20 minutes |
| Elapsed time to prepare the release | 24 hours | 5 hours |
| AI cost for the task | $90 | $40 |
| Labor cost ($50/hour) | $2,400 | $200 |
| Direct cost per task (labor + AI) | $2,490 | $240 |
In this illustrative release estimate, Offloop completes the same work with fewer than half as many people, about a tenth of the cost, and a fifth of the elapsed time. Agents handle execution and coordination on their own, giving the team more time for product decisions and more room to improve the result.
AI Agent Memory: A Teammate Who Never Forgets
In Slack, a teammate's feedback stays in the conversation. Turning it into a shared lesson that several agents can follow takes a system that gives those agents the relevant memory or instructions.
In Offloop, an agent can remember what the team decided, why it made that decision, and when the decision applies. It carries that context forward in Memory without someone having to configure it. A one-off request keeps its original scope, so the agent doesn't turn it into a rule for every job.
Release decisions: When is it time to revisit one?
Back to the release. The lead says, “Let's leave signup alone this time and wait until we hear from more new users.”
A week later, more feedback comes in on X. In Slack, getting an agent to seek out the earlier decision, understand why the change was deferred, and tell whether it's time to reopen it takes dedicated context and memory setup.
In Offloop, the agent can remember why the team waited and bring the new information to bear: “Last week we put this off because we hadn't heard from enough users. This week, several more got stuck at the same step. I'd take another look. Should I ask the engineering agent to investigate?” The lead can consider the recommendation without repeating the background.
Customer quotes: A different agent can pick up the agreement
The account lead tells a customer, “We can offer 10% off with annual billing. Monthly billing is full price.” A few days later, a different agent takes over, and the customer asks to switch to monthly billing and keep the discount.
In Slack, that agreement may be buried across several conversations. The team needs to set up a way for the agent taking over to find it, understand that the discount depends on annual billing, and apply it to the current quote.
In Offloop, the agent can use the relevant shared Memory within its permissions and ask a specific question: “The customer wants 10% off on a monthly plan. That's outside the terms we agreed on. Do you want to make an exception?” Once the lead decides, the agent follows up and remembers when that decision applies.
What does forgetting a decision cost?
A week after the release, new feedback arrives and the team reconsiders the signup flow. The people and agents taking over need to understand why the change was deferred before they can revise the plan.
If the earlier decision gets missed, the gap may only surface after the first draft is ready. The lead points it out, the team looks up the conversation and explains the background again, and several people redo work they thought was finished.
Using a labor rate of $50/hour, here's an estimate for that round of changes:
| What to compare | Slack without a dedicated memory setup | Offloop with existing agent memory |
|---|---|---|
| People involved | 8 | 3 |
| Coordination messages sent by people | 120 | 15 |
| Coordination messages per person | 15 | 5 |
| Staff hours spent finding records and reconstructing context | 3 hours | 0.5 hours |
| Staff hours spent re-explaining and checking requirements | 3 hours | 0.5 hours |
| Staff hours spent on changes and rework | 8 hours | 2 hours |
| Staff hours spent on review and confirmation | 2 hours | 1 hour |
| Total staff hours | 16 hours | 4 hours |
| Elapsed time from new feedback to completed changes | 2 business days | 0.5 business days |
| Labor cost | $800 | $200 |
| Estimated AI cost for this round | $20 | $15 |
| Estimated direct cost for this round | $820 | $215 |
| How it feels for teammates | “Didn't we already go over this?” People pause their own work to explain and check it again | “It remembers why we decided that.” People can discuss the new recommendation right away |
| What the team discusses | Who missed the information or didn't read the thread | Whether the new feedback warrants changing the decision |
When an agent remembers the background, it also interrupts people less often. The lead can stop repeating the same instructions, and the people taking over can avoid doing a round of work over again because they were missing context. The team spends its time on new decisions, with less frustration.
In this estimate, Offloop completes the same round of changes with fewer than half as many people, about a quarter of the cost, and a quarter of the elapsed time. Coordination messages sent by people drop from 120 to 15. The team spends less time repeating itself and redoing work, and can focus on what the new feedback means.
AI Agent Skills and Workflows: Turn Experience into a Repeatable Method
Remembering a decision is one part of the job. Agents also need to turn effective practices into something they can do again. If the team missed a pull request in the last release, add a way to check for it. If the article used an outdated screenshot, change when the screenshot gets checked. The next release can use the improved skill and workflow.
Slack: People turn lessons into a process
Slack supports skills and workflows, and the team maintains the requirements inside them.
Suppose you missed a GitHub pull request during a release. The lead adds that check to the relevant instructions or workflow. If the team only discovers after testing that the launch article uses an outdated screenshot, someone adjusts the sequence so the content agent checks the screenshot once the feature is confirmed.
Writing “remember this next time” in a thread doesn't update the release workflow. Someone has to record the lesson in the right place and make sure the next agent uses it.
Offloop: Agents improve how they work as they go
In Offloop, agents use what went wrong in one release to improve the next.
If a pull request was missed, the agent adds a method for checking related pull requests to a skill. If the article used an old screenshot, the agent adjusts the workflow to check screenshots after the team confirms the feature. On the next release, the agent follows the updated method without asking the lead to turn the same feedback into another configuration change.
A skill captures how to do a job well. A workflow organizes how a particular job moves forward. Agents can use both as they work and improve them based on the results.
Writing feedback: One correction can improve the next article
A go-to-market teammate reviewing the launch article says, “Use a headline that says what the product does. Remove any numbers about results that we can't back up.”
In Slack, the feedback stays in the article's thread. To apply it to future articles, someone needs to add it to the agent's instructions, a skill, or an external memory system.
In Offloop, the agent adds the parts that apply to future articles to its writing skill. Next time it prepares an article, it writes a specific feature headline and checks that any numbers about results have a source.
Every job gives an agent another method it can use the next time.
Our team has worked this way for six months
Over six months, our team has built up dozens of skills, hundreds of workflows, and a growing body of practical experience. That's helped us save about 50% of our working time. With less repetition and rework, people feel better about their day-to-day work, too.
More than that, it's shaped an AI-native culture focused on efficiency. When teammates see repetitive work, they hand it to an agent. When someone finds a better way to do something, they teach it to the agent so it can use that method the next time. One person's improvement can make the whole team more effective.
AI Agent Integrations: From Team Chat to Execution
Back to the release. The engineering agent needs to check GitHub issues. The content agent needs to know what users are saying on X. The go-to-market team needs customer context to prepare launch materials. That takes direct access to the tools the team already uses.
Slack: A large app ecosystem, with execution supplied by connected systems
Slack offers over 2,600 app integrations, including GitHub, Salesforce, and Google Drive. Slackbot can also use MCP to extend what it can do. Slack platform overview
Once an app is installed, what you can do depends on the actions it exposes and the agent system behind it. For complex work across tools and teammates, the team still needs a way to manage context, run the work, and handle handoffs.
For example, when a GitHub notification arrives in the release channel, the connected system needs to work out who investigates, who fixes the issue, and how the fix gets reviewed. Otherwise, someone on the team has to coordinate those steps.
Offloop: More than 2,000 integrations, plus your own tools
Offloop supports more than 2,000 integrations, covers the tools available through Slack, and supports custom connections. You can also connect your own internal systems and APIs for agents to use.
| Work | Example integrations | What you can give an agent |
|---|---|---|
| Development and releases | GitHub, GitLab, Linear, Sentry | Check issues and pull requests and use error reports to investigate release blockers |
| User feedback and launch communications | X, LinkedIn | Read relevant discussions, prepare launch materials, and follow up on activity for authorized accounts |
| Customer follow-up | HubSpot, Salesforce, Intercom | Look up customer records and past conversations and prepare the next follow-up |
| Team documentation | Google, Notion, Confluence, Dropbox | Find project materials, check requirements, and prepare deliverables |
| Growth analysis | Google Analytics, Ahrefs, Semrush | Review traffic and keyword performance and recommend topics to cover next |
| Internal operations | Custom connections, internal APIs | Query your own business data and use it in the task at hand |
Once you've connected the accounts and granted the necessary permissions, you can mention an agent in the release channel:
“Find the remaining blockers for this release. Use the progress in GitHub, feedback on X, and our internal customer data to decide what needs attention. Contact other agents directly if you need their help.”
The agent chooses the tools, reads the relevant information, and starts working. If it needs to run code, operate a browser, or handle files, it can use a cloud computer. When it encounters a product trade-off, it brings the context and a recommendation to the team.
How do teammates work with agents?
You can send an agent a direct message and give it a job. You can also mention it in a team channel, where it can use the discussion to work with the rest of the team. When it needs another agent's help, it can contact that agent directly and bring the results back.
For recurring work, use scheduled tasks or event subscriptions. An agent might follow pull request updates in a particular GitHub repository or receive new mentions for a connected X account. When something happens, it can pick up the work without waiting for a teammate to ask again.
You can organize work that involves several people and agents into a workflow. Teammates can check progress and add requirements while each agent moves its own part forward.
A connected tool becomes something the agent can use to do the job. People set the goal, and the agent chooses the tools it needs to get there.
Offloop vs Slack: AI and Team Chat Features
| What to compare | Offloop | Slack |
|---|---|---|
| Native agents | Create multiple agents with different responsibilities to form a team | Built-in Slackbot. Other agents connect through apps or the platform |
| Agent identity | A digital employee who takes on work like a human teammate | Slackbot, a connected app, or a bot |
| Cloud hosting | Use cloud-hosted agents without deploying an execution system yourself | Slack hosts Slackbot. External agents run through their own services |
| Bring your own API key (BYOK) | Use your own model API key | Supported by the connected app or custom agent system |
| Use an existing AI subscription | Connect your existing AI subscription for agent work | Depends on the third-party app. It doesn't replace the model Slackbot uses |
| Model choice | Choose a supported model or a connected model provider for an agent | Slack supplies Slackbot's models. External services choose their own |
| Agent responsibilities | Set different responsibilities, skills, and tool permissions for each agent | Configure roles through apps, external agents, or a custom system |
| Multi-agent collaboration | Agents contact each other directly to hand off work and keep it moving | The connected agent system handles coordination |
| Working with people | Talk in direct messages or shared channels. Agents ask for input on key decisions | Slackbot, app DMs, channel mentions, and external agent interactions |
| Autonomous execution | Agents plan steps and choose tools based on a goal, then adapt as things change | Depends on the agent system and the automation you've configured |
| Long-term memory | Agents automatically retain work context, team decisions, and experience for later tasks | Sharing long-term lessons across agents requires a system set up for that purpose |
| Learning from feedback | Agents interpret feedback and apply it to later work | Managed through instructions, skills, or external memory systems |
| Skills | Configure skills yourself or let agents create, use, and refine them | Create, share, and use Slackbot skills |
| Creating workflows | Agents plan steps and assign work based on the goal | Configure with Workflow Builder, with AI-assisted creation available |
| Improving workflows | Agents use execution experience to refine how future work is done | People maintain the workflow, or an external agent system handles it |
| Unexpected situations | Agents decide how to adapt and ask people for decisions with context and a recommendation | Handled through configured branches, manual intervention, or external agents |
| Tool integrations | More than 2,000 integrations | More than 2,600 apps |
| Custom connections | Connect internal systems and custom APIs | Build custom apps or extend with MCP |
| Tool use | After getting permission, agents choose and use tools based on the task | Use tools through Slackbot, app actions, workflows, or external agents |
| Running code | Agents run code on cloud computers | Provided by an external agent or connected execution tool |
| Browser operation | Agents use a cloud browser to carry out work | Provided by a connected tool or external agent |
| File handling | Agents read, edit, and generate files in their execution environment | Handled through Slack features, apps, or external agents |
| Scheduled and event-triggered work | Schedule work or subscribe to events so agents can pick it up | Supports scheduled and event-triggered automation. Execution depends on the setup |
| Pricing | Free to start with 200,000 workspace credits. Flat Individual and Team plans include monthly credits, with no per-seat fees | Per-seat plans, with limits for some AI features. External agents are billed by their providers |
Built-In Features in Offloop and Slack
| Feature | Offloop | Native to Slack |
|---|---|---|
| Team channels | ✅ | ✅ |
| Private channels | ✅ | ✅ |
| One-to-one direct messages | ✅ | ✅ |
| Group chat | ✅ | ✅ |
| File sharing | ✅ | ✅ |
| Message search | ✅ | ✅ |
| Mention teammates with @ | ✅ | ✅ |
| Tool integrations and custom connections | ✅ | ✅ |
| Skills | ✅ | ✅ |
| Workflows | ✅ | ✅ |
| Direct messages, delegation, and handoffs between agents | ✅ | ❌ |
| Agents automatically build long-term memory from teammate feedback | ✅ | ❌ |
| Multiple agents share work memory based on permissions | ✅ | ❌ |
| Agents automatically turn successful methods into skills | ✅ | ❌ |
| Agents improve workflows independently based on experience | ✅ | ❌ |
| Cloud computers where agents can run code and operate a browser | ✅ | ❌ |
| Use your own API key or AI subscription with a built-in agent | ✅ | ❌ |
The Slack column covers native features. External agent systems can add capabilities of their own.
Offloop vs Slack Pricing: Seats and AI Usage
Slack's paid plans charge per member. Offloop charges per workspace instead: every plan includes unlimited members and agents, and agent work is metered in credits.
| Pricing item | Offloop | Slack |
|---|---|---|
| Getting started | Free: every new workspace gets 200,000 credits that never expire, no card required | A free plan, with paid plans priced per member |
| Paid plans | Individual $99/month with 20,000 credits each month; Team $999/month with 200,000 credits each month; Enterprise by contract | Per-seat subscriptions. Some AI features have usage limits or additional costs |
| Per-seat fees | None. Every plan includes unlimited members and agents | Each paid plan is priced per member |
| More usage | Credit packs: $99 for 20,000 or $999 for 200,000 credits, valid 12 months, with an active subscription | Depends on the plan and any external AI services you connect |
| Cloud-hosted agents | Use agents hosted by Offloop directly | Slack provides Slackbot. External agents are billed by their providers |
How much does Slack cost per user and per team?
With annual billing, Slack Pro costs $7.25 per person per month, and Business+ costs $15. With monthly billing, those rates are $8.75 and $18, respectively. Contact sales for Enterprise+ pricing. Slack pricing
At standard rates with annual billing:
| Team size | Slack Pro per month | Slack Business+ per month |
|---|---|---|
| 8 people | $58 | $120 |
| 20 people | $145 | $300 |
| 50 people | $362.50 | $750 |
The eight-person team in the release example would pay $696 a year for Slack Pro or $1,440 for Business+. If you connect external agents, include the cost of those AI services too.
We'd rather pay for the work agents do
Offloop prices by the work agents do because the number of people on a team doesn't tell you how much work is happening. One person might work with several agents on many tasks. Someone else might only join for important discussions and decisions.
We want the bill to reflect how much the team uses agents, so adding a teammate never adds a seat fee. See Offloop pricing for current plans and credit packs.
As the release example shows, subscriptions are only part of the cost. The total also depends on how much time people spend coordinating, explaining, and redoing work, and how much of it agents can do on their own.
How to Get Started with Offloop
Sign up for Offloop, invite the teammates involved in a project, and create a channel for the work. You can use our cloud-hosted agents or connect your own API key or AI subscription, then give agents access to the tools they need.
Start with one complete job:
“Get next week's product release ready. Check progress in GitHub, collect user feedback from X, and work with the other agents to prepare the launch materials. Bring me any decisions about what should ship, along with your recommendation.”
Teammates add context and give feedback in the same channel. Agents move the work forward on their own and build up memory, skills, and workflows to use the next time.
If your team still uses Slack, use Offloop's Slack integration to send agent updates to a channel you specify. Start with one project to see what it's like to work alongside agents.
Frequently Asked Questions
Common questions about Offloop and Slack.
What is Offloop?
Offloop is an AI-native team chat app for people working with multiple AI agents. Teams discuss work and assign tasks in channels. Agents use tools to work independently, collaborate with teammates, and build up memory, skills, and workflows as they go.
What is Slack?
Slack is a team communication and collaboration platform. Teams organize work through channels, direct messages, and app integrations, with Slackbot and workflow automation available too. Slack platform overview
What does AI-native Slack mean?
We use AI-native Slack to describe a collaboration app designed for people and agents to work together. Agents have their own responsibilities, understand the team's context, move tasks forward, and reach out when they need help or a decision.
What is the biggest difference between Offloop and Slack?
Offloop was designed around agents as teammates, with team chat and an execution environment in one product. Slack starts with team communication and an app ecosystem, then extends its AI capabilities through Slackbot, workflows, and external agents.
Can Offloop replace Slack as a team chat app?
Yes. Offloop offers channels, direct messages, group chat, and file sharing, with agents participating in team work. It's built for teams that want to hand complete tasks to agents and have them work alongside their teammates.
Why use Offloop if we already have Slackbot?
Offloop gives teams one place to organize agents with different responsibilities, let them delegate work and reuse what they've learned, and work with them over time. The product release above is an example of how this works.
Does Offloop integrate with Slack?
Yes. Start a project in Offloop and connect Slack so agents can send progress updates and results to a channel you choose. Try it on real work before deciding how you want the team to collaborate.
What can Offloop agents do?
Agents can check development progress in GitHub, use feedback on X to investigate problems, prepare release materials, and follow up on customer work. They can use cloud computers to run code, operate a browser, and work with files, and can ask other agents for help.
Do I need to know how to code to use Offloop?
No. You can use Offloop's cloud-hosted agents and explain the work the way you would to a teammate. To use tools like GitHub or X, connect the accounts and grant the agent the access it needs.
Can I use my own API key or AI subscription?
Yes. Offloop supports bringing your own API key and connecting an existing AI subscription. Choose the model source that fits your team or use the service Offloop provides. Work on your own key or subscription still uses workspace credits, at a lower rate than platform models.
What tools and integrations does Offloop support?
Offloop supports more than 2,000 integrations across development, customer management, content, and growth. It also supports custom connections and internal APIs. Once connected, grant tool access to the agents responsible for the work.
Do agents learn how the team works automatically?
Yes. Agents build up memory from working with teammates and receiving feedback. They can turn repeatable methods into skills and workflows for later tasks.
How much does Offloop cost? Can I start for free?
Yes. Every new workspace gets 200,000 free credits that never expire, with no card required. After that, Individual is $99 a month with 20,000 credits and Team is $999 a month with 200,000 credits, with no per-seat fees. Enterprise is by contract.
Do we have to migrate our entire Slack history before getting started?
No. Start with the materials and tools you need for the project at hand.
How do I get started with Offloop?
Sign up, invite your teammates, and create a channel for the work. Choose an agent, connect the tools it needs, and give it one complete task. Sign up and get started with Offloop