Changelog
Release 1.30.0 & 1.31.0
Agent teams & sub-agents
Multi-agent systems often require coordinating groups of agents with specialised roles. We're introducing Agent Teams to make this a reality!
Teams allow you to compose individual agents into a group that can coordinate and work with each other on tasks.
For example, you might assemble a team of agents that specialise in research, content writing and editing to collaborate on a blog post.
To unlock this feature, book a demo with us or upgrade to the business plan and start leveraging the full capabilities of an AI workforce.
Other improvements
Gave our agent editing experience a slick new look
We've reimagined the edit agent interface with a clean, modular layout that makes the set up experience smoother. This huge visual upgrade improves usability by reorganising the panels for more intuitive information hierarchy. Now you can customise more capabilities and build smarter agents with less friction.
Expanded type system
We’ve made a big enhancement to our tool builder by providing type hints for generated outputs from steps.
As you build custom code steps, our tool builder will now infer the data type based on actual outputs once executed. So if your code outputs a string, we'll indicate that downstream steps should expect a string input.
This improvement makes it easier to connect the different parts of your workflow. Now the system itself helps match up the right pieces as you build your tool. You'll spend less time second-guessing or fixing errors, and can focus on seamlessly linking everything into one unified process. We handle more of the tricky details behind the scenes so you can build smoothly and efficiently.
Introducing agent "thoughts"
Here's a powerful new capability - your agents can now share the thoughts they have before executing important actions!
Similar to an internal monologue, agents will surface information about key decisions being made under the hood. You'll gain better insights from understanding an agent's state and motivations before it acts.
Thoughts become an invaluable tool when designing agents serving business critical functions, or managing complex logic flows. Debugging feels easier when you can literally peer into an agent's decision making process.
We believe exposing the reasoning behind AI systems promotes transparency and trustworthiness - exciting capabilities in democratising advanced technology.
Schedule future agent actions
True autonomous assistance means agents that plan ahead, not just respond reactively. We're super excited to introduce scheduled actions - your agents can now make plans and schedule future messages.
Some ways this could be leveraged:
- Schedule follow-up emails to cold sales prospects at optimal send times.
- Plan reminders for upcoming appointments, renewals, latency alerts.
- Build sophisticated recurring alerts, reports, and more.
You can set specific dates and times to control when scheduled messages fire, giving your AI workforce new capabilities to automate complex timed workflows.
Timestamps
To increase transparency into agent functionality, you can now view precise timestamps showing exactly when any task was initiated within Relevance AI.
Fixes
Lastly, we've addressed some smaller pain points and bug fixes:
- Better validation when saving public agents using private tools to avoid failures.
- Resolved input focus frustration from common text input boxes losing focus arbitrarily.
- Numerous app speed optimisations, UI refinements, and automation enhancements.
