Helping startup operators move faster with automation

I train business professionals on AI and automation: workshops, online courses, live sessions, all the way down to custom company training programs

Alexandre Kantjas

Attio MCP is out. Translation: fully programmable CRM gets its command-line interface. Why this is huge:

You can now orchestrate your entire CRM from Claude or any MCP-compatible AI tool. Configure fields, access data, trigger workflows, etc. all from a single interface.

This isn't just "another" integration - it's a big shift in how users will interact with Attio. Think about it:
→ No more filtering records on lists for minutes to get leads
→ No more clicking through UIs to update records
→ No more context-switching between tools 
etc.

Instead, you describe what you want in natural language, and your AI assistant executes it directly in your CRM.

And with tools like Claude Skills, you'll gain the ability to orchestrate complex multi-step operations in Attio with a single command.

This is so, so powerful.

Now, truth be told: a lot of this was already possible with Attio's API. 

But MCP will facilitate things further, especially for less technical users: now they can query Attio data and execute operations using natural language, in an environment less intimidating like Cowork.

It's still early and will require setup and iterations:
→ You'll need to understand your CRM data model
→ You'll need to think through permissions carefully
→ And you'll still need to test and validate

I already have a few use cases in mind that I'll be testing.

If you're using Attio, this is worth exploring.

What's your take? Who else is super pumped about MCP?

Nick Roco

Hi, I'm Nick, from Morningside AI.

We're a completely done-for-you AI workflow automation agency.

Where we help you:

→ Transform your business into an operational machine
→ Turn AI into a tool, not just a toy
→ Ultimately save time, headaches, and money

We do this by working with you 1-on-1 to find the biggest bottlenecks in your business today, and help you solve them with AI and automation.

Here’s how we do it:

1. Audit your current workflows.
2. Identify bottlenecks, inefficiencies, and repetitive tasks.
3. Verify if they can be outsourced to AI or automation.
4. Break down the task into steps.
5. Build custom AI automation tools to streamline.
6. Launch.

Simple as that.

What you get when you work with us:

→ Built-for-you AI and automation solutions
→ A full top-to-bottom AI Automation Business Review
→ Expert guidance on integrating AI into your business for maximum impact

Past clients have received:

→ An efficient AI System for customer support + lead generation.
→ Completely automated client onboarding system.
→ Infinite AI-enabled content creation.
→ Strategies focused on tangible outcomes (time savings, reduced overhead, and increased revenue).
→ Much more sleep.

Here's what 2 of our clients have had to say:

"Nick has taken out a lot of those pain points and a lot of those tedious day-to-day tasks that would feel very overwhelming... I can always count on him when it comes to anything AI and really automating anything" - Ryan, Marketing Manager @ Aragon

"We've been working together with Nick trying to figure out how we can integrate automation in making our workflow much more efficient... Not only did he help us figure out what to do with our workflow to make it more efficient, he also helped us develop what we have to make it better" - Syra, Marketing Project Manager @ Adcrate

----------

If any of this resonates, let's have a genuine conversation about your most annoying challenges.

Reach out to me directly, and let's explore how AI and automation can be a part of your success story.

I respond promptly and am here to help.

Or go here for a Free 16-page E-Guide on Ways to Use AI in your Business: https://tally.so/r/wMElKg

See ya soon.

Member

This is the exact ROI calculator we use to calculate ROI for AI automation projects.

We've used it to identify millions of dollars ($$$) in value across 53+ engagements in 11 industries.

And now, we're giving it away.

It includes:

✅ The exact A + B + C formula - including the 2 parts most people never calculate

✅ 3 real world ROI examples (RFP generation, speed-to-lead, meeting prep) with actual numbers filled in

✅ 3 blank tabs ready to go - plug in your own numbers and get a dollar figure in minutes

✅ Step-by-step instructions so you can do it yourself

Most ROI calculations stop at time saved. This one goes 3 dimensions deeper.

To get it:

1. Connect with me
2. Comment "ROI" below
3. If you repost, I’ll send it to you first

Happy calculating.

---

P.S. Works whether you're a business owner building the internal case OR a service provider selling AI to clients.

Head of AI Consulting @ Morningside AI | Sharing real AI transformation strategies from the front lines | Launched 53 AI projects for clients (and counting)

I'm looking for 5 companies that want to get serious about AI in 2026.

Not "add a chatbot" serious. Actually redesign how work gets done.

In 2025, we ran AI Strategy Assessments for NBA teams, NRL clubs, Fortune 500s. We mapped where AI actually fits (not just where it sounds impressive), and then built those solutions side-by-side with our clients.

Almost all of that work came through referrals. Leaders who got results told other leaders.

Now we're opening the doors to others.

We’ve got 5 spots left in Q1. If you're interested, book a call below to see if there's a real fit.

I run the Consulting team here at Morningside. When you book in, you’ll chat with me directly. There are no sales people that work here.

No fancy deck. No song and dance. Just an honest conversation about what you're trying to solve.

Link below ↓

P.S. My DMs are flooded - booking is the fastest way to actually connect.

AI multiplied my output 3–5x.

It multiplied my decisions 10x.

I constantly have between 2-3 Claude Code agents running at a time - one building a lead magnet, one doing competitor research, one doing transcript analysis.

Cool. Great. Fantastic.

BUT the skill I don't see anybody really talking about is:

Context switching.

Each agent has its own goals, its own state, its own trajectory. Lose track of one for 20 minutes and you're debugging a deliverable that wandered off course.

Your brain becomes the orchestration layer - holding three threads, deciding which needs a nudge, remembering where each one left off.

The bottleneck isn't capability anymore (which is INSANE btw).

It's your ability to hold multiple contexts without losing the plot.

The teams that win here won't just use AI. They'll learn to harness AI faster.

Just wrapped our first Morningside AI webinar. Man that was fun.

Topic was: our 3-phase process that we use to identify, prioritize, and prototype opportunities.

AND we gave away our AI ROI calculator template - the one we use to help identify millions of dollars in value from AI for our clients.

If you missed it, no biggie - you can sign up below, and we'll send you the recording.

https://lnkd.in/gVMKxXbp

And if you don't want to miss the next one, shoot me a DM and I'll automatically add you to the list.

It’s wild that after personally running 25+ AI strategy assessments, it’s always the “boring” AI use cases that get approved first.

We recently ran a 10-day AI strategy assessment for an NBA team's basketball operations. 21 interviews across 12 departments in 10 days. As you can imagine, we weren’t short on ways AI could help (we surfaced 29 unique opportunities).

Each one sounded like a breakthrough. We could've spent months chasing all of them.

Instead, we asked one question: "Where is leadership time disappearing into manual work?"

That question forced alignment and clarity.

We found that 4,000+ hours per year was lost to copy-paste reporting, manual scheduling, and repetitive data entry. Not glamorous. Not exciting. But undeniably expensive.

And lo and behold, this is exactly what we ended up pursuing with the team.

The starting point is the boring work quietly costing you thousands of hours. Fix that. Build trust. Then the moonshots stop being speculative and start being inevitable.

---

P.S. If your team has more AI ideas than they know what to do with, that's a strategy problem - not a tech one.

Shoot me a DM if you’d like to chat.

I have a working theory: The bigger the AI strategy deck, the less likely anything ships.

Most of the time, execs point to these massive strategy decks two years later: "We had a plan." The deck cost $250k… aaaand now it lives in a filing cabinet somewhere.

Story time:

3 months ago, my team and I showed up to pitch an NBA team for an AI opportunity audit. We quickly learned that we were competing against a 600,000-employee consulting firm (whose name is not important, but you definitely know.)

We heard their plan through the grapevine: a lengthy strategic view that will culminate in a flashy slide deck presentation for the client's key stakeholders. Classic consulting playbook.

So before we kicked off our project, we decided to do something completely different this time.

In just 7 days, we:

- Conducted 21 interviews
- Across 12 departments
- Surveyed 70 people
- Identified 16 AI use cases
- Built working prototypes for the Top 3

Our final presentation was 7 slides - not 70.

But the slides weren't the point. They were there to tee up software the client could actually touch. Solutions that would actually solve their problems that they told us about.

This is the future of AI service providers.

A deck can explain. It rarely de-risks. A working prototype immediately answers “would this really help?”.

If you're evaluating getting AI help right now, ask yourself three questions:

1. What will we have in our hands in 30 days?
2. What will we be able to use- not just understand?
3. Does this plan end in a shipped artifact, or just recommendations?

The orgs that move fast are not buying decks right now, they’re buying momentum.

Every company is buying AI agents. Almost nobody is teaching their people how to work with them.

I honestly think we're watching the same gap that appeared with spreadsheets in the '90s. The tool showed up. Training didn't. And for years, most workers used Excel like a glorified calculator.

The same thing is happening with AI agents right now.

I'm calling this skill “Agentic Fluency” - the ability to delegate to, manage, and multithread across AI agents as part of your daily work.

This is NOT just prompt engineering. It's not honestly not even necessarily technical. It's operational.

Let me explain:

Consider the CSM.

Think about what a strong CSM does during renewal season. They're pulling account history, drafting outreach, prepping risk assessments, updating the CRM - all in parallel. Agentic Fluency means knowing how to hand 50-80% of that to agents, while the CSM focuses on the judgment calls that actually save the account.

Same for an AE doing account research. The agent handles the data pull, the competitive landscape, the first-pass account plan. The (human) AE shapes strategy and owns the relationship.

The MAJOR SHIFT HERE is ensuring that your CSMs and AEs all have the wherewithal and the skillset to pull this off.

And for the AI maxi’s: Yes, the tooling will keep getting easier. Interfaces will abstract away much of the complexity - you won't need to know what folder you're in or which tools are connected. The software will eventually handle all that.

(Exhibit A: Clawdbot)

But the core skill? Managing multiple agents, knowing what to delegate, when to intervene, how to quality-check output across parallel workstreams?

That doesn't get abstracted. It compounds.

The companies building this fluency now will operate at a fundamentally different speed in 18 months. The ones waiting for the tools to "get easy enough" will be playing catch-up - again lol.

Agentic Fluency is the spreadsheet literacy of the AI era. The question isn't whether your team needs it… it's whether they are building the skills fast enough.

We've run 25+ AI diagnostics for companies over the last 9 months. Here's what I'd tell any leader scoping AI projects for their team:

1. Nominate a strong internal champion: Someone who owns the outcome - not someone who "oversees" it. They clear blockers, wrangle calendars, and keep momentum when attention drifts. Ideally this is someone with strong influence and a longer tenure.

2. Top-down leadership buy-in: When execs ask "why haven't we done this yet?"- things move. Meetings get scheduled. Decisions get made. Participation becomes real.

3. Being on-site: Remote discovery works, but it’s slower, and less effective. On-site compresses feedback loops, builds trust faster, and lets you pivot in real time. You cannot underestimate the power of IRL connection. This is of course especially true for consultants, but also holds for in-house AI leaders too.

4. Heavy prework + a tight master discovery plan: Interview guides built before day one. A day-by-day blueprint. A single place to analyze transcripts. A scheduled synthesis block. When you hit the ground, all you do is execute.

Dozens of projects and (probably) hundreds of mistakes later… this is what I wish someone had taught me earlier.

Every bad AI strategy engagement I've run started with a bad kickoff meeting.

Not exaggerating.

The interviews were unfocused. People didn't know why I was there. I spent the whole project clawing back alignment I never actually had.

The kickoff sets the frame & pace for everything that follows.

Get it wrong, and you're swimming upstream for weeks.

Get it right, and people show up to interviews prepared. They know what you're digging into. They've thought about it ahead of time.

When next steps are this clear, we hit 95%+ survey completion, and teams are excited about what’s coming. When they're not, we chase people for weeks.

Broke this down in a quick vid 👇

P.S. We run AI strategy assessments for 50-500 person companies at Morningside AI. DM me if you want to talk through yours.

I don't subscribe to the whole "AI is replacing SaaS" narrative right now.

There are a ton of reasons why (and honestly, smarter people than me have written about this at length already).

However… Claude Code (and vibe coding generally) can get you INCREDIBLY far for a very large amount of software applications.

Let me explain.

Last night, with Claude Code, I vibe coded an entire feature prioritization survey using MaxDiff methodology.

Quick context: MaxDiff is a specific survey approach designed to force trade-offs from respondents. Instead of "rate these 1-5" (where everyone gives everything a 4 and you learn nothing), it makes people choose between subsets - revealing what they ACTUALLY value.

It's one of the best ways to build a software roadmap based on real user signal.

Issue is - this isn't something you can just whip up with a Google Form or Tally. The survey needs to randomize option sets, present balanced combinations, and the analysis on the back end is fairly complex.

I remember in my past life paying Qualtrics or other niche survey companies $10-15K to access this kind of functionality.

Last night I built the whole thing in about 4 hours.

1. Requirements doc written in the first hour
2. Code written by hour two
3. Tested completely by hour three
4. Deployed via Railway by hour four

It looks exactly how I want it. Custom UI, custom flow, custom everything. It’s… beautiful.

So here's my actual take on "AI eating software" -

It's not coming for your systems of record. Not your CRM, not your ERP, not the core platforms that run your business.

Where it IS eating software is these niche, tangential applications that you need spun up. The tools that sit adjacent to your core work. The ones where you used to have two options: pay a premium vendor or just go without.

THAT is the version of "AI replacing SaaS" I'm here for.

Being able to go from idea → requirements → code → deployed in a single evening is wild.

And honestly, it's these kinds of use cases that make me most excited about where this is all heading.

---

P.S. I'm Nick. I post about what we're learning on the front lines of AI transformation - including when AI isn't the answer.

If you're interested, follow along.

vibe coded maxdiff survey

I’m obsessed with designing and running the perfect discovery interview. 

In our AI assessments, we spend anywhere between 10-20 hours interviewing rank-and-file employees before writing one line of strategy.

No lie - in 2025, I spent 120+ hours of my life interviewing employees across client orgs to create their AI strategies. 

These 5 interview tactics consistently separate successful AI rollouts from failed ones:

1. Interview teams separately
2. Keep hierarchy levels apart 
3. Block out 1-hour sessions
4. Start with leadership first
5. Request org charts beforehand

Each of these 5 tactics were hard-won through hours of wasted discovery and banging our heads against the wall.

I hope this saves some of you worthwhile time and frustration.

The 5 Tactics For Better AI Discovery

Morningside is hosting our first webinar to pull the curtain back on what we’ve been up to over the last 14 months, working directly with mid-market companies to implement AI the right way.

This is the first of a series of chats that we’ll have. 

Lots of raw numbers and screen sharing.

Should be a good one! See you guys there ✌️

Founder of Morningside AI, AAA Accelerator & Agentive | AI Educator & Creator of the AI Automation Agency Model

Real numbers. Real case study. No fluff.
On 18 February at 3pm EST, the Morningside AI team is running a live online session breaking down exactly how we helped a mid-market company save $2.3M using AI.

No theory. No buzzwords.
Just the work, the decisions, and the numbers behind it.

If you’re a business owner or AI service provider and want to understand:
• Where AI actually creates ROI
• How to identify initiatives worth building
• How to quantify impact before you deploy
then this session will be useful.

Everyone who attends will also receive access to our internal ROI modelling framework.

The event is completely free.
Register and secure your spot below 👇
https://bit.ly/4kqv9dC

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The Battle

Alexandre Kantjas

Nick Roco

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Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Alexandre Kantjas's LinkedIn Performance

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Performance ScoreAlexandre Kantjas's LinkedIn Performance