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Hi. Ex developer evangelist at Salesforce. Also known as @codefriar. Salesforce likes to take a bunch of related technologies and brand them under an aegis ter
by noeticpenguin 2y ago
Hi. Ex developer evangelist at Salesforce. Also known as @codefriar.
Salesforce likes to take a bunch of related technologies and brand them under an aegis term. Currently Salesforce’s Ai offerings under the aegis of “Agentforce” are capable, but no more so than other agent frameworks. IMHO.
Under that aegis is their copilot like code writing helper for their proprietary language Apex, and their proprietary Js frontend technology Lightning web components. Its performance is ok, so long as you don’t expect it to reuse any of your existing code. Its performance can write tests, but don’t expect tests with mock data, for instance.
They also have “agent” like chat interfaces for customer service to end use chats. Again, performance depends on who implements it, but while functional, it’s not better than other tools.
What Salesforce is doing with ai, however is interesting. They’re implementing client facing Ai tools with a “trust layer” that ensures Salesforce’s customer’s data - including data on the customers customers is protected from leaking into a training g pool, and on the return side hedging against hallucinations. There’s more of course - using your own models, a whole host of prompt engineering and then some nice to haves like Ai calculated data fields. (Prompt response stored on records, recalculated when prompt inputs are changed…)
Their big bet, is twofold.
1: that the key differentiation in any agent system is not just the prompts and agent workflows, but the data available to ground the results. (Duh). They’re further betting that their enterprise customers that have terabytes of data on spending habits of b2b and increasingly b2c customers, will yield results that move the “deal” meter.
2: by giving away Ai certifications to anyone with a pulse in their Ai tools, their hoping the groundswell of “certified” people will give cXo’s an inflated sense of Salesforce’s market and mindshare leadership.
But Ai is only part of the picture at Salesforce. You should also be paying attention to their “DataCloud”.
Data cloud is all the tech and tooling to enable a customer to become their own data broker. Take that ability to de-anonymize and coalesce disparate data streams into identities - and then feed that into your “Ai” agents and you might really have something. (Albeit probably a creepy something).
This might, for instance give you the ability to note that “bob” made capital expenditures in the fall as cmo of foo Inc, and that according to your linked in scraper he’s now at “bar Inc” so maybe you should reassign your sales exec from foo to bar, before q4…
You know, if you’ve thought to develop that agent.
I now work in the public sector, so I don’t know anyone developing “no seat in the rain” agents, but … I can envision how to do it with … well any of the agent frameworks I’ve used. The only difference is whether or not the customer is willing to pay Salesforce for easy access to their Salesforce data. Course, they got robust APIs so, pulling that data could just be step 1a in your agent workflow…
Happy to answer any questions
- vmarchaud 2y agoJumping the opportunity:; we make a product that do hyper-personalisation for marketing emails, we do have few customers using SFMC and we tried to think about some use cases with Agentforce but i don't see a lot of useful things. Some customers want to see data about who saw personalisation in tableau/datacloud but again this isn't direct integration with Agentforce but more sending data to any salesforce product. Did you see any pratical use case for Agentforce in SFMC ? Thanks
- noeticpenguin 2y agoI think the holy grail of marketing cloud is tied to two key things: 1. Cohort identification (segmentation) 2. Personalization. I think Agentforce could be a powerful tool for processing the vast audiences, and identifying - with data cloud's help - cohorts for segmentation. I'm envisioning more than cohorts of 'women in their 20's and 30's who ski' but more 'past customers of women's ski boots who also predominantly buy red products' That's a little fuzzier than just data. In fact it's a combination of data(who bought what, when) but also fuzzier info 'who mostly buy's products that are predominantly red, regardless of the shade' and I think if you can surface that data to an agent, it could synthesize an interesting cohort for you to market your brand new red ski jacket to... On the personalization side, I think Agents have a lot of potential. Imagine an agent workflow that went something like this: 1. for each known Data cloud profile develop a marketing profile 2. identify the profiles that show recent activity and / or a history of activity in the next two weeks. 3. Our marketing partners for the next month are: A, B and C. 4. Sort our selected profiles into one of those marketing partners by expressed interest, past history, or relevant markers from their extended data cloud profile. (ie, Kumar seems to always go skiing in early feb..., sort him into Partner A's marketing group) 5. Write email copy to Kumar with a sense of longing and nostalgia for past winter sports vacations. use marketing images from partner A (Vail) and talk about the upcoming ski weather, what the resort's new offerings are in the restaurant and talk up our new 'Ice planet Hoth' approved ski jackets to keep him, and his family warm... I envision that email is going to be a hell of a lot more persuasive to casual buyers than 'hey, check out this jacket bro!'.
- suzzer99 2y agoWould it be crazy for a decision-maker to think the commercial is pitching a turnkey solution to keep Matthew McCaughnehey out of the rain, as opposed to a platform where a Salesforce developer could potentially create such a system? Or do they have a better handle on the big picture than I did before reading your excellent post?