u/mr-sforce

Hey folks, my company's doing a booth at Dreamforce this year for the first time (well, we've attended before, but this is our first time actually having a booth). trying to make it not suck lol.

If you've been to Dreamforce (any year, doesn't matter), what actually made you stop at a booth vs just walk past? like was it the swag, the setup, someone actually talking to you instead of just scanning your badge, a game/activity, free coffee, something else entirely?

Also curious if there's any swag you got that wasn't another tote bag or stress ball, something you actually kept and used, instead of the stuff that just went into trash the same day.

And were there booths that felt too salesy where you just avoided them altogether?

Also, let me know if games or activities at booths still work or if that feels kind of old and gimmicky now, and honestly how much swag even matters compared to just having real conversations with people there who actually have clarity on what they want?

I really don't want our booth to be one of those booths people just walk past, so any honest advice helps, even if it's about something that we shouldn't do.

So this has come up at like three different companies I've talked to recently. sales pulls up Salesforce and says the account paid X. finance pulls up the bank or the gateway dashboard and the number's different.

sometimes a transaction looked successful in the CRM but didn't actually settle. sometimes there's a refund that happened at the gateway and nobody ever updated Salesforce. sometimes it's just timing and if you check at the wrong moment the two just don't match for a day.

every time I've seen it happen someone ends up exporting two reports from each side and matching them line by line. feels like such a waste of an afternoon for something that should just be a number you can trust.

we ended up just assigning it to someone on finance to check weekly, still feels like a workaround and not an actual fix. If you've fixed it, was it a process thing or something automated?

So my friend runs a cleaning business. been doing it 4 years. fully booked mostly through word of mouth and her reviews are genuinely great.

last month she googled her own service just to see.

page 3.

Some random company with fewer reviews and honestly a worse rating was sitting right at the top. she was so confused and honestly kind of annoyed.

And it made me think because she is not alone in this. so many small business owners are out here doing everything right and still invisible to anyone who doesnt already know them.

like your reputation and people actually finding you on Google are just two completely different things and nobody really talks about that gap.

Now my question is has anyone dealt with this similarity. did you figure it out or just give up on Google altogether?

Hi, so day 3 was honestly alot. three major sessions back to back and i was running on coffee and vibes by the end of it but genuinely some of the best stuff came today

gonna keep this casual like the last two posts, just the real announcements and what actually matters, no fluff

Australia Release

So the whole thing opened with a stat that kinda hit hard. Enterprises are running 367+ apps, and AI maturity is actually going DOWN 20% every year. more AI, less confidence. i think anyone working in tech right now felt that in their chest a little

the four things the whole release is built around are Sense, Decide, Act and Secure. Sounds markety, but the demos actually backed it up

Big announcements:

AI Agent Advisor - finds automation opportunities in your existing processes automatically, no guesswork, feeds straight into AI Agent Studio. the demo showed a department transfer workflow that drags on for days, agent just found it and mapped everything

AI Agent Evaluator - tests agents before they go live, completion rates, accuracy, decision quality. honestly this is the thing people skip and then wonder why stuff breaks in prod

Knowledge Center - finds duplicate docs, merges them, even generates new content from incidents and cases automatically. if you have years of messy documentation sitting around this one is for you

Dynamic Guidance - voice AI assistant inside the platform, explains dashboards, surfaces your own docs in real time where you actually need them

Intelligent Approvals - okay this one genuinely got me. you upload a policy doc, platform reads it and builds the approval logic itself. showed a vegas trip getting auto approved and a berlin client dinner getting rejected because international entertainment wasnt covered. policy changes, logic changes with it. no manual workflow building at all

AI Control Tower - single view across your entire AI environment, not just servicenow. risk, lifecycle, business value, real time alerts on cost spikes, suggests prompt improvements. actual governance not just a pretty dashboard

Process Mining (cool thing) - surfaces workflow patterns, delays, inefficiencies, feeds back into Agent Advisor

Data Analytics

whole session basically came down to one thing, agents are useless if they cant reach the data they need

key stuff:

Zero Copy Connectors - going from 250 to 100 more additions, agents work with data wherever it lives, no massive integration project needed

Full MCP Support - same idea, meet data where it is

Data Fabric AI Native - describe what you need in plain english, AI builds the schema and integration. weeks of work supposedly down to nothing

Context Engine - this one was interesting, not just a knowledge graph, it adds action graphs and decision traces so agents actually understand WHY data matters and what to do with it. most platforms are nowhere near this yet, honestly.

RaptorDB Pro Live Connect - real time third-party data, no ETL no copies, governance stays intact. boring sounding but genuinely a big deal practically

Autonomous Data Governance - quality, lineage and policy management handled automatically

McKinsey came on stage to show real world application, which was a good reality check after all the platform level stuff

CreatorCon

this session opened with a story i genuinely cannot stop thinking about. a founder had an AI agent delete his entire production database in nine seconds. agent found an API it wasnt supposed to have access to, made one call, three months of customer data just gone. no rules. no human approval. nothing stopping it

and thats literally why everything shown after that matters

Build Agent - the main event. fixes bugs, traces integrations, proposes better architecture, builds features from plain english or an Excel sheet, documents every single decision in real time. they showed it fixing a broken prod script nobody understood anymore, traced every integration, found the issue from a system migration, and rebuilt it properly. then gave it a finance requirements spreadsheet and it made five user stories with acceptance criteria, ran tests, caught failures, explained why, fixed it. all inside the platform, nothing external needed

Build Agent in External Tools - ServiceNow skill plugin for Cursor and Claude Code. governance travels with you no matter what tool you use. ACLs audit trails deployment controls all enforced by the platform regardless

WarpSpeed (cool thing) - governed hosting where non-developers can build real apps on real production data without a servicenow license. Permissions are inherited automatically, platform team controls when things graduate to full prod. Alpha later this year, this one is worth keeping an eye on

EmployeeWorks - connects everything built on the platform to employees across the whole org, closes the gap between what gets built and who actually uses it

three days down and honestly my notes doc is embarrassingly long at this point lol. few of you have asked about a newsletter after day 1 and 2 and im actually gonna do it**, drop a comment** if you want the complete newsletter or field notes when they're ready.

Heath opened with a number that actually surprised me

367 plus apps running across employee experience in the average enterprise. and AI maturity is going DOWN 20% year over year despite all the AI activity. so more AI, less confidence. that's the whole problem they're trying to solve with the Australia release

they're calling it 4 superpowers. Sense, Decide, Act, Secure. gonna share what actually stood out

AI Agent Advisor was the first demo and honestly the most practical thing they showed. instead of guessing what to automate it just scans your existing data and processes and surfaces the opportunities for you. they showed a department transfer workflow that was dragging on for days across HR and IT. clicked on it. platform mapped the tools, pre filled everything in AI Agent Studio and basically handed the team a ready to go agent. that bottleneck between spotting a problem and actually building something for it is kind of just gone now

AI Agent Evaluator was the part that got no reaction but probably matters the most. tests agents before they go live. completion rates, tool accuracy, decision quality all visible before production. Heath straight up said he hasnt seen a single large scale AI deployment succeed without this. i believe him

Knowledge Center is for the documentation mess. and every org has one. finds duplicates, gaps, merges overlapping articles into one clean draft automatically. but the bit that got me was it generates new articles directly from incidents and cases as they happen. knowledge base just improves on its own as work gets done

Dynamic Guidance was the one i wasnt expecting. voice assistant built inside the actual live platform. Heath talked to a dashboard he had never opened before. it walked him through what he was looking at, reorganised the table by priority, helped him personalise the view. all by voice. inside the real environment not some separate chat window

Intelligent Approvals got the biggest reaction in the room. you literally just upload your policy doc. travel policy, SOPs, whatever you have sitting in a folder somewhere. platform reads it and turns it into automated approval logic. Las Vegas trip for a company event, auto approved. Berlin client dinner, auto rejected because international client entertainment isnt covered in policy. and when the policy changes you just update the doc. logic updates with it. no human interpreting things differently every single time

AI Control Tower closed it all out. single place to see every agent, every model, every workflow running across the entire org. but its not just a visibility dashboard. it flags cost spikes, unexpected outputs and actively suggests fixes to prompts and steps. the agent you built in the first demo feeds straight back into this view. the whole loop closes

Heath kept the ending simple. everything shown is live today

been DMing the full newsletter breakdown to people who asked after the day 1 and day 2 posts. if you want the detailed version with full product context drop a comment or DM me. day 3 keynote recap coming in the next post

which one of these does your org actually need right now?

Day 2 actually went deeper on platform architecture and had some genuinely big announcements. Here's what stood out:

gonna try to break down what they showed without making it sound like a press release

whole thing was built around one idea. AI fails in enterprises not becuase the models are bad but because the data underneath is a mess. so they introduced a 4 layer platform to fix that from the ground up

sense, decide, act, secure. sense is making your data AI ready. decide is where AI reasons on top of it. act is where it executes workflows. and secure isnt a layer on top, it runs underneath all three the whole time. cleaner framing than anything theyve shown before

1. Workflow data fabric

250+ connectors now, 100 new ones announced. AI reads your data live directly from the source, with no ETL and no copying it somewhere. whatever is in your system of record is what the AI actually sees. for large orgs with data spread everywhere, this matters a lot

2. Autonomous data governance

new product announcement. once your data is connected it still needs to be trustworthy before you put agents on top of it. handles data quality, pipeline monitoring, anomaly detection and policy enforcement automatically. platform watches your data health so you dont have to

3. Autonomous data analytics

takes that connected governed data and turns it into something agents can act on. doesnt wait for someone to pull a report. monitors your operational data, detects something worth acting on and triggers automatically. they demoed it catching a contract at risk and drafting a brief and scheduling a meeting with nobody asking it to

4. RaptorDB Pro

database sitting underneath all three. runs transactional and analytical queries on the same live dataset at the same time. no lag between somthing happening in your system and the AI knowing about it. not glamorous but genuinely important if you care about agents making decisions on fresh data. Free is also available.

5. Partnerships & integrations

Google Cloud was the deepest integration shown that includes full stack gapabilities like gemini enterprises, live reasoning (audio + video). Gemini plugged directly into ServiceNow's governance layer, not just a logo on a slide. also OpenAI, Anthropic, NVIDIA, Mistral all supported. any model you bring in inherits the platform's security and governance automatically.

6. AI control tower

single dashboard to see every agent, every model, every workflow running in your org. full audit trail. free for 12 months which is clearly a move to become the default governance layer before anyone else does. if shadow AI is already a concern at your company, pay attention to this one

7. Context engine

understand part of the whole thing. its a live model of your org, people, roles, assets, policies, history. every agent decision gets grounded in this in real time, so its not guessing, its working from whats actually true right now. and it gets smarter the more it runs

8. Enhanced security foundation

Assets + Access + Knowledge this was the most important part imo. three areas: assets meaning IoT, OT, cloud and AI agents all visible in one place. Access means every agent runs under the same permission rules as human workers and cant escalate its own access. and knowledge meaning the platform understands active vulnerabilities and attack paths so it knows if an agents action is actually risky

9. Build Agent + Claude Code demo

they brought Claude Code on stage built a full enterprise feature live, 20 files, and scored 90% app readiness. the point was it came out enterprise ready because governance is baked in by default not added later

10. CMDB

also talked about this, and its more important than people realize. It's the live map of every asset in your org and what business service it supports. agents query this in real time when making decisions. the more accurate your CMDB, the smarter your agents. simple as that

the whole point is the more autonomous your agents get the more dangerous it is if guardrails are added afterward. theyre saying the guardrails are the platform itself not something you bolt on later

btw been getting a lot of questions on this stuff so we are building a proper newsletter going deep on ServiceNow AI. no fluff just the things that actually matter. DM me if you want to be on it.

happy to answer anything if you were there too

just got back. few things worth sharing

Otto is not just another copilot. every action runs through your enterprise policies before anything executes. "ottomatically governed" sounds cheesy but the concept is real. the shift they are making is from AI that thinks to AI that acts. that is the whole bet.

the AI Control Tower hit different. they asked the room if anyone has full visibility into what AI is running across their org right now. silence. that is the product. one place to control everything, pause agents, track cost, manage permissions. free for a year which is clearly a land and expand play but the problem it solves is real.

the ROI angle was surprisingly grounded. stop measuring AI by usage, measure actual outcomes. productivity, cost savings, down to token level per workflow. finally a story finance will not laugh at.

the part nobody clapped for but probably matters most. none of this works without clean data and structured workflows. agents do not fix broken processes, they just run them faster.

my honest take, the governance story is stronger than most enterprise AI pitches i have heard. but i am skeptical how much of this holds outside a demo environment.

are you actually measuring ROI from AI in your org or still in the we are exploring phase?

Think about that for a second.

The thing you open 40 times a day. The tab that's always there. The thing your whole team complains about but still lives inside.

Salesforce just said agents will do that part now. You describe what you want, the agent handles the navigation, the clicking, the updating. You never actually go there.

And I'm sitting here like... okay but my muscle memory has opinions.

Jokes aside, the scary interesting part is not the technology. It's that every workflow your team built assuming a human would click through it, those were the wrong workflows and nobody knew yet.

We built for the browser because that was the only option. Now it's not and everything has to be rethought.

Not ready to say if that's exciting or terrifying. Probably both.