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#AI55 discussing

Hi everyone,

I'm planning to run a production pilot of Agentforce Coworker

with a small group of users. Before we start, I need a way to monitor adoption, usage, logs, and key metrics to better understand how users are interacting with the solution. 

 

I'm looking for answers to questions such as: 

 

  • How can I track who is using Coworker and how often?
  • Is there a way to capture user prompts, responses, and interactions?
  • What logs are available for troubleshooting and auditing?
  • Are there any built-in dashboards, analytics, or monitoring tools for Agentforce/Coworker?
  • What metrics do you recommend collecting during a pilot (adoption, success rate, user satisfaction, etc.)?

My goal is to have enough observability to evaluate the pilot's success and identify opportunities for improvement before a broader rollout. 

 

Any guidance, best practices, or real-world examples would be greatly appreciated. 

 

Thank you! 

 

#Agentforce  #AI

2 comments
  1. Oct 28, 8:50 AM

    Hi Hellen, a quick check-in before the community goes read-only on Oct 30. Did the observability approach I outlined help with your Coworker pilot? If it did, marking it as the best answer would help others later. Happy to go deeper on any layer.

The loop that hit me hard:Web Agent types wrong value in field. 

I manually correct it. 

Web Agent continues: "Great, I typed it correctly" → moves to next step. 

Everything after that fails because it thinks it made my edit. It had no idea I touched the browser at all. Built ActionTrace to fix this exact blind spot: 

[AI] typed "ABC" → wrong 

[HUMAN] typed "XYZ" → this is the real value now 

Now the Web Agent knows that an error didn't happen magically, human made the change - without human needing to explicitly say it. 

🔗 GitHub:

https://github.com/nvaishnavisriyaa/ActionTrace

 

🎥 45-sec demo:

https://youtu.be/WKw3Eqf8n_E

 

Question: When human edits a field mid-flow in Service Cloud, does Agentforce get live context that "human made this change"? Or does it assume it made the change itself? Anyone seen this? 

 

#Agentforce  #AI  #AgenticAI  #AgentforceBuilder  #Mvp-agentforce-prompt-builder-team

2 answers
  1. Oct 28, 8:48 AM

    Hi NARASIMHADEVARA, checking in before the community goes read-only on Oct 30. Did this answer solve it for you? If so, marking it as the best answer would help others who find this thread later. Happy to dig further if something's still off.

Hello all! Has anyone managed to set up the Salesforce MCP with Claude so that it can read documents, such as PDFs and Word docs, stored in Salesforce? 

 

Example usecase - I have docs stored in opportunties (notes & attachments) I'd like to query in Claude. 

 

I don't believe this is available out of the box, so any tips / workarounds are appreciated! 

 

Many thanks. 

 

 

#AI  #Salesforce Admin

3 answers
  1. Oct 20, 10:30 AM

    Hi @Dan Humphries,

    This is not available out of the box. The Salesforce hosted MCP tools work on records (SOQL and sObject reads). Files are stored in ContentVersion, and the actual content sits in the binary field VersionData. Claude can find the file, but it cannot read the text inside a PDF or Word doc.

    Practical workaround:

    1. Download the file with the REST API (/sobjects/ContentVersion/<id>/VersionData).
    2. Extract the text with an external script or service (for example Python).
    3. Save the text in a Long Text Area field on the Opportunity, or in a custom object.
    4. Claude can then read that field through MCP like any normal field.

    You can also build a Flow or Apex action that returns this text, and expose it as an MCP tool.

    Official docs:

Hi Trailblazers,

I missed  the event code of today’s AI Force workshop. My org has since closed, and to reopen it and try the hands-on exercises, I need that code.

If you attended the event today, could you please share the event code with me?

Thanks in advance for your help! 

 

#Salesforce Developer  #Agentforce  #Trailhead  #AI  #Hands On Workshop

1 answer
  1. Oct 22, 3:41 PM

    For events or workshops that require active orgs, the best approach is to reach out directly to the event host or register for the next available session on the Salesforce Events page to receive a fresh, active environment and the correct code.

Builder Central (Beta) shows "Failed to fetch" on the welcome screen in my Agentforce Developer Edition org. 

Console: CORS preflight to

https://api.salesforce.com/platform/dx-workspaces-proxy/v1/api/workspaces-proxy/<workspaceId>/project-service/v1/projects

 

is blocked. The OPTIONS response is HTTP 204 with no Access-Control-Allow-Origin header. 

Reproducible with curl from outside the browser for any Origin, so it is not a client-side issue. 

"Connect an org" logs in successfully but never returns to the app. 

Org: nexustrade-portal-dev-ed, Home Org ID 00DgK00000WFVD2. Workspace ID: b6f6c7b9-dd87-4ca5-99e9-0d74efb79d36. 

 

Builder Central (Beta) shows

 

 

image.png

 

 

 

I have followed the steps - 

  1. enable data cloud - https://help.salesforce.com/s/articleView?id=data.c360_a_setup_provision.htm&type=5
  2. enable einstein AI from einstein setup - https://help.salesforce.com/s/articleView?id=ai.generative_ai_enable.htm&type=5
  3. enable agentforce - 
  4. enable builder central
  5. assign permission set - Access Builder Central
  6. launch the builder central(beta) from setup

 

 

 

#Agentforce  #Salesforce Developer  #Data Cloud  #AI

5 answers

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14 comments
4 comments
  1. Oct 10, 7:18 AM

    Hi Chromer, This error usually happens when Salesforce doesn't allow changes to the current agent version. 

     

    Try these steps:

    1. Check if the agent is active. Deactivate it before making changes.
    2. Refresh Agent Builder and try publishing again.
    3. Check if any deployment or publishing process is still running.
    4. If possible, try creating the agent again in a fresh Trailhead org.
    5. If the issue continues, raise a Trailhead support case with the error and request ID.

    It could also be a temporary Salesforce platform issue.

    Hope this helps!

Hi Trailblazers,

I’m working on a Data 360 implementation where customer data is coming from multiple source systems.

The records are being ingested correctly, but some profiles that should represent the same customer are not getting unified as expected.

In this situation, what do you normally check first — match rules, reconciliation rules, source data quality, normalization, or identity resolution configuration?

Also, what are the common mistakes you’ve seen in real projects that prevent profiles from being unified correctly?

Would appreciate insights from anyone who has handled Identity Resolution issues in production.

#Data360 #Agentforce #Salesforce #AI

2 answers
  1. Oct 8, 9:04 AM

    Hi @Santhosh Gorantala

    This is a common challenge when customer data comes from multiple systems.

    I would normally start by checking the match rules and source data quality.

    A few things I would suggest:

    1. Match Rules: Check whether the rules are too strict. Sometimes small differences in names, emails, or phone numbers prevent matching.
    2. Data Quality: Look for missing values, duplicate records, extra spaces, and inconsistent formats.
    3. Normalization: Try normalized email and phone matching where applicable.
    4. Data Mapping: Make sure Individual, Contact Point Email, and Contact Point Phone are mapped correctly, including their relationships.
    5. Ruleset Execution: Check whether the Identity Resolution ruleset completed successfully and review the processing results.
    6. Reconciliation Rules: If records are unified but the expected field values aren't showing, check which source is given priority.

    Simple Example:

    One system has "Santhosh Kumar" and another has "Santosh Kumar". An exact name match may fail, but fuzzy matching could help identify them as the same person. 

     

    My suggestion is to take 2–3 customer records that should match, compare their source values, and test the matching rules step by step. 

     

    One important point: Match rules decide which records get unified, while reconciliation rules decide which field values appear in the unified profile.

    Hope this helps! 

     

    Thank you, 

    Venkat Yadav.

Hi Trailblazers,

I’m exploring Data Graphs in Data 360 for real-time Agentforce use cases.

Since a Data Graph can bring related customer information together for faster access, I’m interested in understanding how teams decide what data should be included.

Do you mainly consider relationship depth, response time, business relevance, data volume, or how frequently the data is accessed by Agentforce?

Also, have you seen performance issues when too many related objects or attributes are included in a Data Graph?

Would love to hear some real implementation experiences.

#Data360 #Agentforce #Salesforce #AI 

3 answers
  1. Oct 8, 9:00 AM

    Hi @Santhosh Gorantala

     

    Good question! I think the main thing is to include only the data that Agentforce actually needs, rather than bringing everything into one Data Graph. 

     

    A few things I would consider:

    1. Business Use Case: First, understand what questions the agent needs to answer and what data is required.
    2. Relevant Data: Include only necessary objects and fields. Avoid adding unnecessary information.
    3. Relationships: Keep relationships simple. Too many related objects can make things complex.
    4. Data Volume: Be careful with large datasets and historical records.
    5. Performance: Test how quickly Agentforce can retrieve the required information.

    For example, if we're building a customer support agent, I would start with Account, Contact, recent Cases, and Orders instead of bringing in the entire customer history.

     

    And yes, adding too many related objects or attributes can increase graph size and potentially impact performance. 

     

    My suggestion would be to start small, test with real-world scenarios, and add more data only when it's actually needed. 

     

    At the end of the day, Agentforce needs the right information at the right time, not every piece of data available. 

     

    Hope this helps! 

     

    Thank you, 

    Venkat Yadav.

#Trailhead Challenges #Trailhead #AI

 

Trailhead gives good hands-on practice, but how can a student create experience that is closer to working on a real Salesforce project? 

3 answers
  1. Oct 8, 9:59 AM

    Hi @Chandra Shekar

     

    Good question! Trailhead is a great place to learn Salesforce, but working on complete projects will help you understand how things work in real companies. 

     

    Here are a few things I would suggest:

    1. Build Real-Time Projects: Start with projects like Student Management, Recruitment Management, or Customer Support Management.
    2. Understand Requirements: Don't just create objects and fields. Think about the actual business problem you're trying to solve.
    3. Practice Admin & Development: Work with security, Flows, validation rules, Apex, SOQL, and LWC based on project requirements.
    4. Work on Real Scenarios: Practice bulk data uploads, error handling, record sharing, and approval processes.
    5. Use GitHub: Upload your project code, requirements, screenshots, and documentation.
    6. Join the Community: Participate in Salesforce community discussions, developer groups, and hackathons.
    7. Practice Team Work: Learn how Jira, Agile, Scrum, Git, and deployment processes work.

    My suggestion:

     Pick one project and complete it from requirement gathering to development, testing, and deployment. 

     

    For example, build a Recruitment Management application where recruiters can manage candidates, schedule interviews, and track hiring status. 

     

    Most importantly, during interviews, you should be able to explain what you built, why you built it, and how you solved the challenges. 

     

    A complete hands-on project can give you much better practical understanding than completing multiple Trailhead modules alone.

    Hope this helps!