Once a niche part of the employment sector, working to implement Salesforce products has grown into a sought-after career. Whether it’s the paycheck, the easy-to-implement approach, or the unique community, more people than ever are choosing to go to work with Salesforce.
However, this also means that there is more competition for roles in the ecosystem. Having recently looked into my own career, I’ve spent some time pondering what I could do to differentiate myself and improve my prospects of landing my next dream job. Based on over twelve years’ experience in the Salesforce ecosystem, recent visits to conferences, and many hours looking at online job prospects, here are three areas that you could look at to diversify and differentiate yourself…
Salesforce and…
When I joined Salesforce in 2010, public cloud was in its infancy and was treated with great skepticism. Today, public cloud providers are ubiquitous. From smaller businesses, to the largest enterprises, to the public sector – it’s hard to find an IT shop where the public cloud doesn’t play a role in some form. The ‘big three’, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), make up nearly two thirds of the market.
On a recent visit to AWS Summit in London, I was surprised at how often Salesforce was brought up. This is not just Salesforce in its role as an AWS partner, I found Salesforce was often mentioned as a data source for AWS partners to integrate with. It became clear to me that being the Salesforce expert who also had some fundamental AWS skills (or vice-versa) could be a clear opportunity to differentiate.
After this realization, I even decided to attend the AWS Certified Cloud Practitioner prep session (this is their ‘fundamental’ level certification). It didn’t feel like it would be a big stretch to get that knowledge, and weirdly, I even bumped into someone else in the Salesforce ecosystem who attended thinking the same thing as me.
Add to this that there are various Salesforce products and features that integrate with or use public cloud services, expanding your knowledge could make you a better partner to the public cloud teams in the business.
Each of the ‘big three’ public cloud providers has their own foundational certification. In each case, no previous experience is required:
- AWS: AWS Certified Cloud Practitioner certification
- Azure: Microsoft Azure Fundamentals certification
- GCP: Cloud Digital Leader certification
As with all knowledge-only certifications, these are more about demonstrating interest and motivation rather than practical experience. But to get a foot in the door, and to explore a new interest, the cost and the bar is pretty low.
As of today, AWS and Azure hold 33% and 22% respectively of public cloud market share. So, barring other factors, as a straight up career play the safe money would be on those. But if you work for a company that is already invested in GCP, you won’t do yourself any harm in exploring that platform either.
Every public cloud provider has extensive online learning resources. And especially with AWS and Microsoft being so big, free or cheap third-party learning is easy to find – including an AWS Cloud Practitioner Trail on Trailhead.
The Multilingual Developer
When looking at the actual code that a developer in the Salesforce ecosystem might write, it used to be pretty straightforward: learn Apex. While this still remains important and requires proficiency of the language syntax and idioms, an experienced Apex developer must also have intimate knowledge of the Salesforce platform’s peculiarities. Governor limits, SObjects, and all the configured goodness of your org greatly influence good code design and patterns when using Apex.
But two major changes have impacted which languages a Salesforce Developer might look to master. The first major change is the expansion of the Salesforce Platform itself. Every Salesforce Developer that wants to move beyond server-side code needs to gain some competence with JavaScript., and I’ve been an advocate for and teacher of JavaScript for years.
But platform developers need not stop at Apex and JavaScript. With the Summer ‘23 release, Lightning Data Service has surfaced the GraphQL API wire adapter to Lightning Web Components.
This popular web query language promises to greatly change how we access Salesforce data when building custom UIs. DataWeave in Apex will unlock massive data operations using a functional approach to data manipulation that’s been brought over from MuleSoft. Both features are in beta as of the writing of this article.
Then there is mobile development. For native iOS apps, Swift is a fun and expressive language which has grown in popularity in the past five years. And Kotlin, a functional JVM language, has become the standard for native Android applications.
The second major change is the accretion of new technologies through Salesforce’s acquisitions. MuleSoft comes to mind immediately. I’ve already mentioned MuleSoft’s DataWeave. More importantly, Java plays a key role in MuleSoft integrations.
When creating Slack apps, Java, Python, and JavaScript have libraries for interacting with the original Slack Bolt API, with TypeScript forming the foundation of its next generation platform. And Tableau Server Client Library for Python is a great recent addition to help Tableau appeal to the most popular language of the data science community.
While Trailhead’s coverage of programming languages outside of Apex and JavaScript is spotty, fortunately, with the explosion of software development online trainings and bootcamps, there is no shortage of resources to go to in order to learn a new programming language. So go forth! There is no downside to learning a new programming language.
The Emerging AI Opportunity
While AI is not new, with generative artificial intelligence (GenAI) there’s no denying we’re in a new wave of AI transformation. First the AI scientists were surprised by the unlikely acceleration of the performance of GenAI technology. Then with the launch of Dall-E, Midjourney, ChatGPT, and Bard, everyone else in the world was surprised by the sudden emergence of GenAI in the public consciousness.
If you were a technology company and weren’t already building something with GenAI, the pivot was irresistible. In short order, every cloud provider either launched a GenAI initiative, took their existing initiative public, or both.
Salesforce have been no different. On the home-grown side, Salesforce’s Codegen project looks very promising for developers and admins to get Apex and Flow assistance. With other features, it appears they’re taking a partnership approach.
Based on the two “AI Days” in New York and London, it looks like they’ll wrap OpenAI services and models to surface those in Salesforce as features. In other cases they’ll use some best-in-class AI providers, like AWS, Anthropic, and Cohere, to build and host models owned by Salesforce. And for customers with in-house AI expertise, they plan to support a bring-your-own-model arrangement with AWS SageMaker and Google Vertex AI.
Most of the features so far seem to leverage large language models (LLMs), which have to do with text generation. Although the keynote demo at London World Tour did whet our appetites for Marketing Cloud-based multi-modal generative feature with Typeface.
While predictions of the future, both long and short term, range from unbridled optimism, to full on catastrophizing, the one consensus appears to be that there are new skills needed out there.
No doubt, GenAI is super cool. But (sticking with LLMs for the moment) beyond the parlor tricks of making up a Shakespearean sonnet on the need for my kids to brush their teeth or a recipe for porridge oats written by Dr. Seuss, getting something useful out is not so straightforward at the moment.
GenAI models require a certain craft at making the correct incantation to produce the magic. These incantations are called prompts, and for any decent result, there’s work to be done.
As an LLM user, you need to understand what produces success in a prompt. The context for the request you’re making is key, including providing background, what persona the model should assume, examples of successful responses, and even how to structure the response (say, in JSON). There are even techniques to help the model slow down and even proof its own work. This new set of skills has a name: prompt engineering.
Helping GenAI users be successful with prompts looks like it may be a key skill. But how long actual prompt engineering will last is definitely up in the air. Even now, Salesforce is showing us how they want to democratize prompt creation for the end user with Prompt Studio. And even outside of the Salesforce ecosystem, companies like Cohere and Inflection.ai are doing the work of making GenAI more accessible.
In every technology, it seems as though there is an opportunity for the “super user”. I think this will look like someone with an understanding of how to communicate with GenAI models, combined with deep domain knowledge.
If ever there was an opportunity for workers to get in at the ground floor of a technological ground swell, the Generative AI Super User is it. In London, EVP of Product and Industries Marketing, Patrick Stokes even showed us that some Salesforce Administrators may soon be adding GenAI to their long list of possible specializations.
If you’re inclined to explore this emerging GenAI space, a good place to start is the new Get Started with Artificial Intelligence Trailhead Trail. But if you want to go deeper, why not try the SF Ben ChatGPT Mastery for Salesforce Professionals course?
Summary
For years now, Salesforce has provided an ever-growing, ever-expanding marketplace for job seekers. Now more than ever, it is overlapping with general purpose technology skill sets. If you’re looking to expand, specialize, or broaden your employability, the time has never been better.
