Features & Capabilities FAQs

Yes, our platform supports several users accessing the same agents – it's even something we recommend when re-engineering processes with the help of agents.

Access rights can be set per agent, starting from completely private agents to agents accessible to the entire team.

You can invite team members to access your agents in two ways: at the team level or for individual agents.

Team-level access

1. Log into your Abundly account
2. Navigate to Members in the main menu
3. Add new team members who can then access agents based on their permissions

Agent-specific access

For more granular control over individual agents:

1. Select the specific agent you want to share
2. Go to Settings for that agent
3. Click on Team Access tab
4. Choose the appropriate access level:
   • Admin: Team members can do anything, including deleting the agent or changing access rules
   • Edit: Team members can interact with and modify the agent (instructions, capabilities, docs, etc.)
   • Use: Team members can interact with the agent but cannot make changes
   • None: Team members cannot see the agent exists

Best practices

• Start with 'Use' access for most team members to prevent accidental changes
• Grant 'Edit' access only to team members who need to modify agent behavior
• Reserve 'Admin' access for project owners or IT administrators
• Review access permissions regularly as your team and projects evolve

Getting started with team collaboration

Team access is particularly useful when re-engineering processes with AI agents, as multiple stakeholders can collaborate on the same agent while maintaining appropriate access controls.

The recommended approach for fine-tuning AI agents is to:

1. Chat directly with the agent and update instructions with more specific details
2. Be very explicit about requirements (companies, time periods, etc.)
3. Try this method for 1-2 attempts
4. If you don't see improvement after 1-2 tries, contact Abundly support for additional assistance

This iterative approach of refining instructions through direct interaction is generally effective for improving agent performance.

Common issues and solutions

Date handling problems: If your agent includes wrong dates or information from outside specified time periods, this is often caused by a known issue where Claude (the underlying language model) can "hallucinate" dates when they are not explicitly provided.

Current solutions:

• Be very explicit with date ranges in your instructions
• Double-check that today's date is clearly specified in agent instructions
• Abundly is working on a platform-level fix to automatically provide dates to agents

When to escalate

If you've tried updating instructions 1-2 times and still experience issues:

1. Contact Abundly support with specific examples of the problems
2. Include details about what the agent should vs. shouldn't include
3. Provide examples of incorrect outputs
4. Support can help identify technical issues or provide advanced troubleshooting

Best practices for effective instructions

• Be very explicit about criteria (specific companies, date ranges, content types)
• Include examples of what should and shouldn't be included
• Specify the current date clearly in instructions
• Test changes iteratively rather than making many changes at once
• Document what works and what doesn't for future reference