u/TrailblazeTaco

So Salesforce has been pushing Agentforce and AI stuff pretty hard lately, feels like every update has something new about it. And honestly with Dreamforce coming up I have a feeling this is gonna be a big chunk of what they talk about this year too.

Wanted to ask people who are actually using this stuff instead of just seeing it in demos. Is it actually helping day to day or is it more like something which looks cool in the demo but kinda mess when you're actually using it?

Also how's it working when the AI agent hands something off to an actual person, is that smooth or do you end up fighting with it half the time lol. Has it changed how your team works at all or is it still too early for that.

If anyone's been using it long enough to know what actually works vs what just sounded good on paper, would love to hear it.
Just trying to get a real answer instead of the keynote version of all this because that is something that works for me.

Was reading that ServiceNow crossed a billion dollars in AWS marketplace transactions and the part that stuck with me was an AWS exec basically saying that companies aren't experimenting with AI anymore, they're actually running it in production

Which is kind of wild because a year ago pretty much everything I saw in this space was pilots. "let's test an agent in a sandbox," POC after POC, nothing really shipped. Now it sounds like enterprises are putting AI agents into actual governance, security, IT ops workflows, not just demoing them.

But I keep wondering if the reliability side is actually keeping pace with the pricing part. A billion in marketplace transactions tells you that the budget is real. It doesn't really tell you if these agents can be trusted with real workflows without someone babysitting them.

So genuinely curious, does anyone here work somewhere that's past the pilot stage and running this in production. Is it actually holding up or is it still more hype than people admit?

So apparently Salesforce launched a "prebuilt" version of Agentforce just for customer service called "Agentforce Help Agent."

Like instead of building your own agent from scratch (connecting kb, setting up actions, doing each channel separately which honestly takes forever), this one just comes ready and it gets deployed in minutes.

But the interesting part of this help agent thing is the pricing, it's pay per resolution now. So you only pay if the agent actually resolves the issue from start to end, there's no charge if the agent passes the issue to a human or if the customer is not satisfied with the resolution.

Feels like a low key admission that a lot of these agents have been kinda mid at, actually resolving stuff and they're trying to fix that trust problem.

They're claiming 4.3M tickets handled on their own help site with 70% resolved before launching this publicly, which is a decent number I guess but also it's their own data so take it with a grain of salt.

Anyone actually tested the setup flow yet? curious if it's genuinely fast or if "deploys in minutes" is doing a lot of heavy lifting like usual

So with Dreamforce 2026 around the corner, I keep hearing about this whole Agentic Enterprise idea and Agentforce being the big thing.
The part that actually makes me think is not the tech itself, but the way people keep talking about humans and agents working side by side.

TBH, I don’t think anyone really knows what that balance looks like yet. In theory, it’s great, like, agents handle the repetitive clicks, the data pulls, the boilerplate stuff, and humans get to focus on decision making, creativity, and building relationships. Makes sense to me.
But in practice, I actually wonder how much trust you can put in an agent before you feel the need to double‑check everything. If you’re constantly reviewing what it does, is it really saving time? I don't know, I'm confused!!

At the same time, I can see how this could reshape roles.
A sales rep who used to spend hours analyzing reports might now spend that time thinking strategically about accounts. A support agent might spend less time typing repetitive responses and more time handling the tricky conversations that actually require empathy.
That sounds good but it also means people have to let go of tasks they used to own and that’s not always easy.

Another thing I keep thinking about is accountability. If an agent makes a mistake, who’s responsible? the human who approved it? the system that generated it? that grey area feels like it could get messy fast.

Personally, I’m curious whether this humans + agents model is going to stick and actually change workflows, or if it’s just another shiny theme we’ll hear about at Dreamforce 2026 and then quietly move on from.

What’s everyone else’s take? do you see this as a genuine shift in how teams work, or just another buzzword cycle?

Seeing a lot of people in my network starting to talk about Dreamforce 2026 and every time I ask if it's worth going the answer is basically "yes obviously you have to go" with no real explanation of why.

Like I get that it's the biggest salesforce event of the year. 1600 sessions, big keynotes, Marc Benioff doing Marc Benioff things.

But $1500 for the pass plus flights plus san francisco hotel prices in september is a serious commitment and "it's an experience" isn't really convincing anyone's finance team.

So genuinely curious from people who've actually been. What's the thing that made it worth it for you. was it a specific session, a conversation you had, something you learned that you couldn't have gotten from salesforce+ at home.

And on the flip side, what's the stuff that's genuinely overhyped. sessions you can skip, things that sound good on the agenda but don't land in person.

Trying to give people an honest answer when they ask me whether to go this year. 

Keep seeing the case studies, "cut resolution time by 40%" type stuff, but every time i ask someone who actually works with this day to day, the answer is way more boring. Usually "yeah we turned it on for one use case and it's fine I guess.

Trying to figure out if that's just early days, most orgs haven't gotten past proof of concept yet, or if there's a real split between teams that went all in with budget behind it vs everyone else still kind of poking at it.

Specifically curious about the difference between "we built an agent" and "this does something every day that used to be on me and now it's not." Feels like most of what's online is the first one dressed up as the second.

Also wondering if it tracks by team size, like is a 5 person admin team seeing the same results as an enterprise org with a dedicated ai budget.

If you're running this in production, even just one workflow, genuinely want to hear what it actually looks like. What broke, what surprised you, what you'd tell someone before they sink months into something that ends up being a demo nobody uses

Saw salesforce's new blog post from their ai research chief about "ambient intelligence."
The pitch is ai that's always listening, always reading context, and acts before you even ask it to. Four pillars: always-on, aware, adaptive, anticipatory.

Cool in theory but this is basically copilot's whole pitch from a year and a half ago, which itself followed einstein gpt. Now it's folded into "ai foundry" alongside agentforce, which is already in market promising agents that run full workflows on their own.

The part that actually made me pause was the "always listening" angle for sales and service calls. They're calling it PISA(Proactive In-Meeting Support Agent), apparently it scans your screen and listens in real time during calls to surface info.

Genuinely curious how that's supposed to play with shield or data residency requirements if you're in a regulated industry. anyone seen this live anywhere or is it gonna be another eVerse situation (all vision, no actual rollout).

Not saying ambient/proactive ai is a bad direction, it's probably where everything eventually lands. Just feels like salesforce keeps publishing the manifesto before the product ships. I've had to walk leadership back more than once on what agentforce can't actually do yet vs what the keynote demo showed.

Okay so this happened last week and I'm still a bit annoyed about it!!

Our payment gateway started failing right in the middle of a billing cycle. No notification, no alert, nothing. Transactions were just quietly failing in the background and nobody knew until someone on the team randomly checked. By the time we caught it half the scheduled payments had already missed their window.

The actual gateway issue wasn't even that big a deal, got fixed pretty fast. but then came the cleanup. Figuring out which transactions failed, manually chasing them down, resending payment requests, fixing records. Took way longer than it should have.

What got me was there was zero visibility while it was happening. Everything looked completely normal on the Salesforce side. no errors surfaced, no flags, nothing.

Is there a way to set up some kind of fallback or retry logic natively, or do most people just find out when someone notices something's off?
genuinely curious if others have figured this out or if this is just the kind of thing you accept and deal with reactively

So i came across this recently and i've had a weird reaction to it that i can't quite shake.

Build Agent now works inside cursor, windsurf, github copilot, claude code. on paper it sounds great, stay in your existing environment, build on the now platform without switching tools full context maintained throughout.

But i don't know. part of me wonders how much of this is solving a real problem versus servicenow just making sure they're in the same sentence as all the tools everyone's talking about right now. Cursor especially feels like it's in every announcement from every platform these days.

The governance angle is the part i actually find more interesting than the integrations themselves. App engine management center being free and sitting between your build and your deployment, that feels like it could matter more in practice than which IDE you're using. Ungoverned deployments have quietly caused a lot of damage for a lot of teams.

maybe i'm overthinking it but i feel like the "works inside your favorite tool" messaging is doing a lot of heavy lifting here and the actual substance is buried underneath it.

Has anyone used this in a real environment yet? I'm curious whether the experience feels as seamless as it sounds or if there's more friction than the announcement lets on.

Mandatory MFA for all users. Phishing-resistant MFA for admins. step-up auth on reports. Auto-containment of "high-risk" connections. Email domain verification, all compressed into roughly 12 weeks, April to July 2026.

Fine. Security matters, no argument there.

But here's the part that actually stings: the requirements keep changing mid-rollout. IP range enforcement was on the list, then quietly dropped, after consultants had already briefed their clients on it. one MVP with a 20-year-old developer org got locked out, and Salesforce apparently couldn't clearly explain why.

The community reaction has been pretty blunt. And honestly, fair.

When goalposts keep moving this fast, it's not just a technical problem, it erodes trust in a way that takes a long time to rebuild.

Anyone else following this closely? How bad has it been on the ground?

I've been going back and forth on whether to post this because it's long. But here we go.

Went to K26 with a few colleagues. all three days. keynotes, breakouts, the side conversations that happen when you're waiting in line for coffee, and someone just starts venting about their CMDB situation.

And I've been processing it for two weeks now.

The announcements were genuinely impressive. ServiceNow basically said, "The platform you know is about to look completely different," and the energy in that room was unreal.

But here's the thing that kept hitting me the whole time and hasn't stopped since:

None of this works if your foundation is broken.

And most enterprise foundations are broken. not catastrophically. just quietly. messy CMDB. Data that's been "we'll clean it up" for two years. AI governance that exists as a policy doc nobody reads. workflows that five different people touched and nobody fully owns.

K26 announced the ceiling. Most orgs are still fixing the floor.

So what does Otto actually mean for an enterprise that can't trust its own data? What does Data Fabric do when your integrations are pushing dirty records? How do you govern AI at scale when you don't have a clear owner for it internally? How do you even begin to measure ROI when your baseline metrics are all over the place?

These are the questions I haven't seen answered properly anywhere. Not in the keynotes, not in the recap articles, not in the LinkedIn posts.

Anyway, I've been thinking about putting something together on this. Either a detailed written breakdown or, honestly, maybe a live session with some of the ServiceNow people in our company who were there too. Like a proper sit-down conversation where they just go through what each announcement actually means practically, not theoretically.

Not sure if that's worth doing or if everyone's already moved on from K26 at this point.

If that's something you'd actually find useful, drop an"interested" below. would help me figure out whether to actually go ahead with it.

Not a complaint exactly. Just something I've noticed.

The announcements were genuinely big. AI Agents handling multi-step tasks on their own. AI Control Tower for governance. Otto. Action Fabric. Bill McDermott is basically saying the platform will be unrecognizable in two years.

And now it's been almost two weeks and the vibe in every ServiceNow conversation I'm in has shifted from hype to something closer to quiet panic.

Because agentic AI sounds great until you look at your actual environment. messy CMDB. workflows that five different consultants touched over six years. No internal clarity on who owns AI governance or what that even means day to day.

The gap between what got announced and what most orgs can actually do with it right now feels massive. And I don't see that talked about enough.

Is anyone else sitting on a long list of K26 notes with zero idea where to actually begin?

The job market for fresh grads right now is actually cooked and nobody's being honest about how bad it is.

People in my feed sending 300+ applications and hearing nothing. entry-level hiring down 6%.
Anthropic's own CEO out here saying AI could replace 50% of entry-level jobs. And the advice everyone gets is just "learn AI" with zero context on what that even means or who's actually hiring for it.

It's exhausting to watch.
so it genuinely felt different when I saw Salesforce announce the Builder program.
They're recruiting 1,000 graduates and interns through their Futureforce initiative across engineering, product, sales, all of it. The whole idea is that today's grads aren't behind on AI, they grew up with it, they already know how to work with it, and that's exactly why they want them.

Their CPO said "businesses can't afford to wait for their workforce to catch up to AI. that's why we're betting on Builders now."

Don't know how it plays out in reality but at least it's a different conversation. curious if anyone else is seeing companies actually hiring with this mindset or if this is still pretty rare

got back from K26 few days ago and look, the conference was genuinely amazing. the AI announcements were impressive, the energy was unreal, Now Assist stuff looked slick as hell.

but something kept nagging at me the whole time and i can't shake it.

like we're out here celebrating agentic AI and deeper automation and everyone's hyped. rightfully so. but nobody in those sessions stopped to ask what this AI is actually going to run on.

because most companies have a CMDB that nobody fully trusts. integrations pushing dirty data that's been "we'll clean it up soon" for literally three years. workflows built by someone who left the org. data governance policies from 2019 that haven't been looked at since.

and now we're pointing AI at all of that.

the features aren't the problem. the roadmap looks great on paper. the problem is enterprises are skipping the boring foundational stuff because it doesn't make for a good keynote slide and nobody wants to be the person saying "actually we need to fix our data first" when everyone else is rushing to ship AI.

the companies that are actually going to see ROI from any of this are the ones quietly doing CMDB hygiene, data quality audits, governance cleanup right now. it's unglamorous. nobody's writing blog posts about it. but it's literally the difference between AI that works and AI that just exists.

anyway. is anyone actually doing this at their org before going all in on AI or is everyone just pushing forward and hoping for the best?