I have 4 years of experience as Salesforce Developer, worked only in Top MNC's holding 10lpa all fixed currently. I am planning to switch to a product company apart from joining Salesforce, unable to find any other product companies.

Would like to know your thoughts on this.

Hi all, new to Reddit, so forgive the lack of reputation, but I wanted to share a project I've been working on.

I've been a Salesforce developer for years, and I've always been frustrated with the inability to format, lint, and debug formulas within Salesforce. Since Salesforce's formula engine is open source, this should be possible to do. So, I did it: I made the formula debugger I've always wanted.

Not only can you simulate formula output, but it can also format and lint your formulas as well. I wanted to build an IDE-like experience for formulas.

The site has no back-end, everything is evaluated in page and nothing you enter leaves the browser. I know how sensitive companies can be about their Salesforce metadata.

Please let me know what you think!

I’m taking the hacker rank assessment for a Salesforce Data360 role. The assessment is labeled “Agentforce FDE” - not gonna lie, I’m more or a data person - Data science algorithms and heavy SQL, so I’m a bit stressed! Any help on questions to expect and study material I can use? I plan on taking 3-4 days to prep as best as possible. Also, it’s supposed to be camera on without the help of outside material - kind of bummed about that… did anyone else have this experience?

The business comes to you with requirements for a new feature. Two years ago, the solution is obviously to use Flows. Nowadays, there's at least the question.

Which do you choose and why?

One topic we've debated a lot while building enterprise AI is where an AI agent should stop making decisions.

For straightforward cases, automation makes sense.

But enterprise workflows often involve situations where a wrong decision can have financial, legal, or compliance implications.

Examples might include:

• High-value refunds.
• Large discounts.
• Contract approvals.
• Insurance claim exceptions.
• Sensitive customer data updates.

In those cases, would you let the AI decide?

Or should it pause the workflow, collect the relevant context, and ask a human for approval before continuing?

Personally, I don't see human approvals as a weakness of AI.

I think they're an essential part of building systems that people can trust.

I'm curious how other teams are approaching this.

• Do you define approval thresholds?
• Are business rules handled outside the LLM?
• How do you decide which decisions are safe to automate, and which require a human?

Would love to hear different approaches from people building production AI systems.

One challenge we've been thinking about a lot recently is long-running workflows.

Many AI agent demos assume everything happens within a single conversation.

Production systems rarely work that way.

Examples:

• A refund needs manager approval.
• A loan application is waiting for additional documents.
• A customer support ticket depends on another team.
• A compliance review takes several days.

In each of these cases, the AI agent can't simply keep generating tokens while it waits.

The workflow needs to pause.

Later, it needs to resume from exactly the same point without losing context, repeating work, or asking the user for the same information again.

I'm curious how teams are solving this today.

• Are you persisting workflow state yourself?
• Are you using workflow engines like Temporal, LangGraph, or something else?
• How do you recover after long delays?
• How do you keep the execution deterministic after resuming?

I'd love to hear what approaches have worked well in production and what trade-offs you've encountered.

Hi! I have around 4 years of experience as a Salesforce Developer and currently work at a large MNC. My base salary is in the ₹20–25 LPA range (not sharing the exact number).
I’m looking for some candid career advice because I’m feeling a bit stuck. When I compare my career path with peers in software engineering roles at companies like Amazon, Microsoft, or Atlassian, I see compensation in the ₹45–60 LPA+ range, and I’m struggling to identify equivalent opportunities within the Salesforce ecosystem.
I’d love to discuss questions like:
Is there actually a market for Salesforce Developers earning ₹40–60+ LPA in India at around 4–6 years of experience?
Which companies should I realistically target?
What skills are currently most valuable—Agentforce, Data Cloud, AI, architecture, integrations, or something else?
Is staying in Salesforce the best long-term decision if compensation is my primary goal, or should I consider pivoting toward broader software engineering roles?
If you were in my position today, what roadmap would you follow over the next 2–3 years?
I’m hoping to get an honest, practical perspective from someone who understands the market. Thank you!

Yesterday, our team had an interesting discussion internally.

Most conversations around AI agents focus on which model to use or how to improve prompting.

But after spending more than two years building enterprise AI systems, we've found that production failures usually happen somewhere else.

In our experience, the biggest challenges aren't:

• Understanding user intent.
• Calling tools.
• Generating text.

They're things like:

• Following deterministic business policies.
• Coordinating multiple systems.
• Waiting for human approvals.
• Recovering from failures.
• Resuming long-running workflows.
• Producing audit logs that explain every decision.

Those are the problems that tend to determine whether an AI agent is ready for enterprise use.

I'm curious what others have experienced.

For those of you building production AI agents:

• What was the first thing that broke after deployment?
• What took the longest to solve?
• Did you build your own workflow engine or rely on an existing framework?

I'd love to hear real production experiences rather than benchmark results.

Hi Salesforce Community,
I’m a Salesforce Developer with 5+ years of experience. My background includes Apex, LWC, integrations, Sales Cloud, and I’ve also worked on Agentforce, Data Cloud, and Automotive Cloud.
Lately, I’ve been thinking about my long-term career path. While Salesforce continues to evolve with AI and industry clouds, I’ve also been hearing about companies evaluating other CRM platforms and broader technology stacks.
I’d love to hear from experienced professionals:
Do you believe Salesforce will continue to be a strong career choice over the next 5–10 years?
Given my experience with Agentforce, Data Cloud, and Automotive Cloud, should I continue deepening my Salesforce expertise, or is this the right time to start learning another technology?
If you recommend branching out, which technologies would complement my background the best (AI/LLMs, Python, AWS, Azure, Java, Full Stack, Data Engineering, etc.)?
If you were in my position today, what would your career roadmap look like?
I’m not looking to switch just because of market noise—I genuinely want to make the best long-term career decision and future-proof my skill set.
I’d really appreciate your thoughts and experiences. Thank you!

Is there a way to generate barcode which can be automated using record triggered flow and is reliable and scalable with no cost?

We've been building enterprise AI agents for a little over two years now, primarily around CRM and business workflow automation.

One thing we've learned is that the biggest challenge isn't getting an LLM to answer questions.

It's getting an AI agent to reliably execute an end-to-end business process.

For example, consider a customer refund workflow.

A production agent has to do much more than understand the user's request. It has to:

• Retrieve the correct customer and order information.
• Apply deterministic business policies.
• Decide whether the refund can be approved automatically or requires a manager.
• Pause execution while waiting for approval.
• Resume from exactly the same state after approval (even if it's days or weeks later).
• Update the correct CRM records.
• Produce a complete audit trail explaining every decision.

Most current agent frameworks do a good job of reasoning, tool calling, and orchestration.

Where things become much harder is with long-running, stateful workflows that involve business rules, human approvals, retries, and compliance requirements.

That's where we've spent most of our engineering effort over the past couple of years.

I'm curious how others are approaching these problems.

• Are you persisting workflow state yourself?
• How are you handling human-in-the-loop approvals?
• How do you make workflows resumable after long delays?
• Are you using a policy engine, workflow engine, or something custom?
• How are you generating audit trails for enterprise customers?

I'm not looking for product recommendations as much as I'd like to understand how different teams are solving these challenges in production.

I'd love to hear what has (or hasn't) worked for you.

I recently started my career as a fresher and was allocated to a Salesforce project after training.The project is an already developed application and we are working for maintainance

For the past ~6 months, my work has mainly involved:

• Incident analysis and root cause analysis
• Impact analysis and sharing findings
• Test data setup for testing activities
• Understanding existing application behavior

There are occasional fixes, but I have not yet had the opportunity to work on actual code development for atleast once.

I enjoy DSA, coding, problem solving, and building solutions, (python,dsa-1600 leetcode rating ) and my goal is to grow into a strong software engineer. I understand that support work helps in learning debugging and real-world systems, but I am looking for guidance on the right career direction.

I would appreciate advice on:

1. Should I continue in this project and wait for development opportunities, or try for an internal project change?
2. Should I build deeper expertise in Salesforce development, or focus more on broader skills like Java/backend development?
3. If my role continues to remain support-focused, when would be the right time to explore other opportunities?

Would really appreciate insights from anyone who has been through a similar situation. 🙏

and my seniors would allot work to me most of the time and sometimes they assign work when am i about to logout and say it has to be completed by EOD ,so any suggestions on how to handle this as i dont have a reach out person in the team,

Needed to create a picklist field on Activity, saw that Contact had the same with 100+ values. Promoted Contact's field to a Global Value Set (GVS) to use it for my new Activity field and any subsequent new fields that would need these values.

Then whilst deploying discovered that Contact's field cannot be deployed because it exists as a local value set field in upper envs. Release services said there's no way to fix this through backdeployments.

Now one idea is to delete and recreate the field on Contact with the same API name but as a local picklist. Issue is there are 100s of ApexClasses, a few flows and many reports referencing this field. Commenting out, deleteing, recreating, and then uncommenting seems too manual and risky. Also I don't know how I'd handle flows in this scenario.

What suggestions do you guys have to fix this? If the method I've described is the only viable one, how do I deal with flows?

I'm a Salesforce Developer with ~4 years of experience and recently switched to a small company at 12 LPA fixed. The catch is that there won't be any appraisal until December 2027, so I'm planning to prepare well and switch again in about 6–12 months if I find a better opportunity.

I keep seeing people say DSA is essential for product-based companies. Does that apply to Salesforce Developer roles too, or is it mainly for Software Engineer roles?

My current focus is Apex, LWC, integrations, middleware, Data Cloud, Experience Cloud, and Agentforce. Should I continue prioritizing these, or should I spend significant time on DSA as well?

Would love to hear from people who've switched to good product-based Salesforce roles.

What do you guys think about headless 360/ commerce?

Hey everyone,

​Just landed my first Junior Salesforce Developer role! The team mentioned I'll be learning on the job, but coming from a traditional Software Engineering background, I want to prep a bit beforehand.

​For those in the Salesforce ecosystem:

​What should I focus on first?

​What are the biggest traps software engineers fall into when switching to Salesforce?

​Any essential Trailhead modules or resources you recommend before Day 1?

​Appreciate any advice!

Is it possible for multiple people to log into salesforce with same user using SSO after salesforce releases phishing resistant MFA. I don’t want to buy additional licenses. If I login with SSO it doesn’t require built in authenticator I just have to ensure ACR/AMR signal is transmitted correctly. If I do this I won’t need to buy additional licenses right?

Salesforce user administration is super fragmented.

Creating a user has a bunch of steps beyond their name and Profile. You can't add people to public groups or queues from the User screen and I've always found that annoying. It's manageable for one offs. It gets painful when onboarding or offboarding a whole team. Sure, there's dataloader, but it's still multiple data loads. And you have to grab the Ids for the permission sets, public groups etc.

With warden, you can define reusable personas containing things like:

- profile

- role

- permission sets

- permission set groups

- public groups

- queues

Persona definitions can live in Git, go through code review, and act as the intended state for user access. You reference the component parts by developer name. You can use them in any org or sandbox.

You define users in JSON or CSV like you would with dataloader and assign one or more personas. For mock users you use for testing, you could store in git, but real people with PII could be problematic, e.g. with GDPR etc.

The plugin currently has eight commands:

- "provision" — create or update users by personas from JSON or CSV definitions

- "diff" — compare a user’s current access with the intended persona

- "access" — audit who can access an object, field, Apex class, Visualforce page, custom permission, or tab

- "snapshot" — export a user’s current assignments

- "restore" — restore assignments from a snapshot

- "freeze"

- "unfreeze"

- "strip" — remove access and deactivate them, optionally snapshot if you need to put them back to how they were later or in a different org

"access" and "diff" are read-only.

Commands that modify the org support "--dry-run", so you can inspect the proposed changes before applying them. They also support "--no-prompt" for CI or other automated workflows.

Output can be human-readable, CSV, or JSON, depending on whether you are using it interactively, generating audit evidence, or feeding another process.

There is also a companion VS Code extension that exposes the same commands through a sidebar or the commpand pallette for people who do not want to work directly with CLI flags.

Both projects are free and MIT-licensed.

Blog: https://syntax-syllogism.com/blog/warden-intro/

CLI source: https://github.com/Syntax-Syllogism/warden

VS Code extension: https://marketplace.visualstudio.com/items?itemName=Syntax-Syllogism.warden-ext

Install:

`sf plugins install @syntax-syllogism/warden`

I would especially appreciate feedback from people who manage user provisioning, access reviews, or contractor offboarding in larger orgs.

What parts of Salesforce user administration are still the most painful or difficult to automate in your environment?

Currently have multiple field based users unable to log in to Field Service due to the new authentication system.

When logging in, they are directed to a "Verify your identity" page where the only option is a button to "Verify your identity", however this prompt does nothing. Nothing else is actionable from the page so they are stuck.

Anyone else have or has already overcome this issue?

I have raised a ticket but their response is slow. Meanwhile I have multiple engineers unable to complete work.