Business AI Explained

Nico Simko (Clair): $100M ARR with 70 people, and the plan for $1B with under 200

### Description
Nico Simko runs Clair, which lets US workers get paid early. In the last year they went from ~$30M to close to a $150M run rate, with a team of about 70.

His own math: without AI, Clair would need 400 people to be where it is today. The plan is $1B in revenue with fewer than 200.

We talked about:
- scaling past $100M without a sales team
- the agent that shipped a whole feature on its own, and still missed the context
- why the bottleneck moved to their bank and payroll partners
- open-source vs frontier models, and when the cheaper one wins
- what hiring looks like for AI-native engineers and PMs

Chapters
(00:00) Intro
(01:02) What Clair got right
(04:30) $100M+ without a sales team
(06:46) What stays human
(08:35) AI across every team
(11:49) The new bottleneck
(14:30) New AI use cases vs. the mission
(18:37) Moats in the AI era
(20:57) Hallucinations and model costs
(23:10) Hiring AI-native engineers and PMs
(25:23) Strategy and go-to-market in 2026
(27:49) $1B with fewer than 200 people
(29:15) Wrap-up

Watch on YouTube: https://www.youtube.com/watch?v=v0eruAaxqaQ
Book an AI operations audit call: https://cal.com/vladimir-de-ziegler-uyu7qb/ai-operations-audit-discovery-call
Elements: https://www.elementsagents.com/
Vlad on LinkedIn: https://www.linkedin.com/in/vladeziegler/
Clair: https://getclair.com/
Nico on LinkedIn: https://www.linkedin.com/in/nsimko/

Business AI Explained: how entrepreneurs actually use AI to grow their businesses.

Igor Pogany just hosted the largest AI event in history — 600,000+ people — and grew a 400K+ channel teaching mid-career professionals how to actually use AI.

So I asked him the obvious question: what did running it all teach you about using AI? His answer isn't about prompts or the newest tool. It's about context: stop treating AI like a vending machine, start feeding it your context, and use it to amplify the expertise you already have instead of trying to reinvent yourself.

Igor Pogany — founder of The AI Advantage and now partnered with Tony Robbins and Dean Graziosi — teaches mid-career professionals (average age 50+) how to master AI instead of fearing it. We get into the practical playbook: why you should amplify your existing expertise instead of reinventing yourself, how to give AI enough context that it stops people-pleasing and hands you opinions you can trust, the two-rule test for avoiding AI slop, how to grow an audience by matching your viewer's worldview, and the "company brain" he uses to run a 50-person media company on AI.

In this episode:

• Why you should amplify your existing expertise with AI instead of reinventing yourself

• How to give AI enough context that it stops people-pleasing and tells you the truth

• The two rules for avoiding AI slop (never go 0 to 1, always seed it)

• How to grow an audience by matching your viewer's worldview — and what a thumbnail really is

• Why social media is networking at scale — and how Igor ended up working with Tony Robbins & Dean Graziosi

• The "company brain" and Alfredo Hub setup Igor uses to run a 50-person company on AI

Chapters:

0:00 The world's largest AI event (intro)

2:50 Who Igor helps: mid-career pros vs AI anxiety

4:10 Amplify what you do — don't reinvent yourself

6:18 The fastest first win: photograph your fridge

7:41 Using AI for decisions you can trust

8:36 Context: how to stop AI people-pleasing

13:25 Creating content with AI — without the slop

15:17 The real skill: turning chaos into content

17:30 Match your audience's worldview

19:07 Grow an audience: networking at scale

23:26 Compacted knowledge = time travel

25:47 The Alfredo Hub: one place for every AI tool

29:23 Company brain: a shared source of truth

Guest: Igor Pogany, Founder @ The AI Advantage. Igor Pogany is the founder of The AI Advantage, one of the most-watched practical-AI channels on YouTube (400K+ subscribers), and Head of AI Education for the AI Advantage program he runs with Tony Robbins and Dean Graziosi. He teaches professionals how to use AI to save time and amplify the expertise they already have.

Connect with Igor: https://www.linkedin.com/in/igorpogany/

Connect with Vlad:

• LinkedIn: https://www.linkedin.com/in/vladeziegler/

• YouTube: https://www.youtube.com/@aiwithvlad

• Work with Vlad (Elements Agents): https://www.elementsagents.com/

• Come on the show: https://cal.com/vladimirelements/podcast-intro-call

—

Business AI Explained is a podcast for founders and GTM teams on how AI creates real business impact — real examples, real constraints, lessons from AI in production. Hosted by Vlad de Ziegler, founder of Elements Agents.

Most companies are buying AI, then quietly failing at the last mile. Michael LaVista has spent 25 years shipping the hard final stretch — here's how he gets AI into production.

Michael LaVista, founder of Caxy (a Chicago software firm that's spent 25+ years staying a few steps ahead of the market), breaks down "last-mile AI" — why most AI projects run out of steam right at the end, and how to actually get them into production. We cover finding use cases worth building, the AI stack you can realistically hire for, driving adoption against real resistance, value-stream mapping to find the work that matters, guardrails for autonomous agents, and the rule that saves the most pain: solve the problem first, pick AI second. Real AI in production, not theory.

In this episode:

• What "last-mile AI" is — and why most AI projects run out of steam right at the end

• How to find AI use cases worth building (let 100 ideas compete, keep the home runs)

• Why automating tasks you already do is a weak AI strategy — and what to do instead

• How to pick an AI stack you can actually staff and maintain

• Driving adoption when part of your team is quietly resisting AI

• Value-stream mapping, guardrails for autonomous agents, and when NOT to build it yourself

Chapters:

0:00 Cold open: pick the problem, not the hype

1:20 Last-mile AI: where AI projects quietly die

2:56 Why automating tasks is a losing bet

3:53 "The board said use AI" — $100K/mo, zero accountability

5:45 Finding use cases: let 100 ideas compete

6:54 Idea to working software in 6 minutes

8:07 The AI stack: pick tech you can actually hire for

9:52 Adoption & the people who resist AI

11:25 Value creation beats automation (proposals, IKEA)

15:43 Right tool for the job: when NOT to use AI

18:47 Value stream mapping: find the red-pen process

21:28 Coding vampires & the autonomous-agent holy grail

23:25 Guardrails: prompt injection & Bedrock

24:58 Three steps ahead: a world where everyone builds

27:46 Final advice: problem first, then go get help

Guest: Michael LaVista, Founder & CEO @ Caxy. Michael LaVista is the founder and CEO of Caxy, a Chicago-based software and AI transformation firm. For 25+ years he's helped mid-sized companies turn AI from a board mandate into something that actually ships — what he calls last-mile AI.

Connect with Michael: https://www.linkedin.com/in/michaellavista/

Connect with Vlad:

• LinkedIn: https://www.linkedin.com/in/vladeziegler/

• YouTube: https://www.youtube.com/@aiwithvlad

• Work with Vlad (Elements Agents): https://www.elementsagents.com/

• Come on the show: https://cal.com/vladimirelements/podcast-intro-call

—

Business AI Explained is a podcast for founders and GTM teams on how AI creates real business impact — real examples, real constraints, lessons from AI in production. Hosted by Vlad de Ziegler, founder of Elements Agents.

━━━━━━━━━━━━━━━━━━━━━

#BusinessAI #AIForBusiness #AIimplementation #AIstrategy #AIadoption

Lanch went from zero to $200M in under three years selling chicken. Leander Gruss, Head of Growth at Lanch, will explain us how.

In this episode:

• Why you should never "vibe-code" your source of truth — and how to decide build vs buy

• How a non-technical growth lead actually ships internal tools (the exact stack)

• The 2-day prototype rule that stops AI builds from sprawling

• Running shared AI agents for SQL, customer support and procurement across the org

• Why clean, structured data — not bigger prompts — makes agents accurate

• The buy-vs-build math that's wiping out their monthly software bills

Chapters:

0:00 Cold open: own the transaction

1:08 Meet Leander & Lanch (0 to $200M)

3:41 The data warehouse that runs the business

6:09 Writing SQL in minutes, not weeks

7:22 Build vs buy: what NOT to vibe-code

8:22 Building the route-optimization tool

10:26 The build stack: Replit, Lovable, Claude Code, Vercel, Supabase

11:55 Driving AI adoption + PRDs + cost limits

15:39 Langdock & sharing agents across the org

18:38 Context engineering & RAG for retrieval

24:25 Benchmarking & evals

26:33 Buy to build economics & maintenance

32:45 Lovable + git + skills = 3-4x dev cycle

37:40 Where to find Leander

Guest: Leander Gruss, Head of Growth @ Lanch. Leander Gruss leads growth at Lanch, the creator-backed food-tech company behind Loco Chicken and Happy Slice. He joined as one of the first employees and helped scale it from zero to $200M.

Connect with Leander: https://www.linkedin.com/in/leander-gruss-aa1280147/

Connect with Max: https://constructlabs.com/

Connect with Vlad:

• LinkedIn: https://www.linkedin.com/in/vladeziegler/

• YouTube: https://www.youtube.com/@aiwithvlad

• Work with Vlad (Elements Agents): https://www.elementsagents.com/

• Come on the show: https://cal.com/vladimirelements/podcast-intro-call

—

Business AI Explained is a podcast for founders and GTM teams on how AI creates real business impact — real examples, real constraints, lessons from AI in production. Hosted by Vlad de Ziegler, founder of Elements Agents.

Most AI agent projects stall at the last mile: the legacy browser workflows no API can reach.

Idan Raman, founder of Anchor Browser, joins Vlad to explain why browser agents are the missing piece in enterprise AI, how the Cloudflare partnership is changing the economics of automation, and why the OpenClaude security fallout was a wake-up call for anyone running computer-use agents in production. If you're evaluating AI agents for your business, this is the layer of the stack nobody's explaining clearly.

In this episode:
- Why 90% automated still isn't automated — the KYC last-mile problem
- Computer use vs browser use, and when each one makes sense
- The real security story behind the OpenClaude virality (leaked credit cards, stolen passwords)
- How enterprises are pricing AI: the voice AI framework ($3/call → $0.30) applied to back-office work
- Why open source LLMs are exploding inside large enterprises
- The Cloudflare "web bot protocol" and why it's a win for everyone
- Building a moat in AI infrastructure: "if it's hard, it's good"

Chapters:
00:00 Intro
00:52 Computer use vs browser use
03:34 KYC as the poster child
06:08 The Cloudflare partnership
09:01 When to use browser agents vs Playwright
10:56 Security and the OpenClaude fallout
14:05 Open source LLMs in the enterprise
17:08 Pricing AI tools for enterprise
21:19 Building a real moat in AI
25:24 Dogfooding Anchor to grow Anchor
29:45 What's next

Guest: Idan Raman, Founder @ Anchor Browser. Idan built Anchor Browser to solve the last-mile automation problem for enterprise AI agents.
Connect with Idan: https://www.linkedin.com/in/idan-raman/
Anchor Browser: https://anchorbrowser.io/

Connect with Vlad:
- LinkedIn: https://www.linkedin.com/in/vladeziegler/
- YouTube: https://www.youtube.com/@aiwithvlad
- Work with Vlad (Elements Agents): https://www.elementsagents.com/
- Come on the show: https://cal.com/vladimirelements/podcast-intro-call

—
Business AI Explained is a podcast for founders and GTM teams who want to understand how AI creates real business impact. Hosted by Vlad de Ziegler.

AI training usually fails for a simple reason: it is too generic.

In this episode of Business AI Explained, I sit down with Elise Masurel de Laval, co-founder of Catalyst.ai Academy, to break down what makes AI training actually work inside companies. Elise and her team focus on practical AI training for non-technical roles, with a strong emphasis on role-based use cases and learning by doing rather than abstract demos. 

They discuss why AI adoption needs to be tied to real business workflows, why peer-led learning often beats formal training, and how companies should think about shadow AI, governance, and long-term capability building. They also explore why AI agents create excitement early on but often become difficult to maintain unless internal teams can truly own them.

They cover:

•  Why most AI training programs fail 
•  The case for role-specific AI enablement 
•  Why peer practitioners are often the best teachers 
•  How to build relevance through real company use cases 
•  Why AI communities can outperform static courses 
•  How to think about shadow AI without overreacting 
•  Balancing experimentation with governance 
•  The hidden maintenance cost of AI agents 
•  Why practical adoption matters more than tool knowledge 
•  How non-technical teams can build AI confidence quickly 

This episode is for founders, operators, enablement leaders, consultants, and anyone trying to move from AI awareness to real adoption across teams.

About the guest
Elise Masurel de Laval is co-founder of Catalyst.ai Academy. Catalyst describes its approach as practical AI training for non-tech roles, and the company’s about page highlights Elise’s background in marketing, digital, sales, innovation, and executive leadership in education. 

Where to find Elise:
→ LinkedIn: https://www.linkedin.com/in/elise-masurel-de-laval-2579b999/?skipRedirect=true
→ Company: https://catalystacademy.ai/

Work with Vlad:
If you’re implementing AI in your operations and want hands-on help building real workflows:
→ https://www.elementsagents.com/

Subscribe / follow Vlad:
→ LinkedIn: https://www.linkedin.com/in/vladeziegler/
→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Max Emma started in landscaping and construction, then got hit hard during the 2008 recession, a period that eventually led to bankruptcy and some hard-earned lessons about risk, financial management, and resilience.

He later co-founded Booxkeeping, a bookkeeping business built around fixed pricing, operational efficiency, and standardized financial reporting. That business went on to scale through franchising, becoming a standout model in the bookkeeping industry.

In this episode of Business AI Explained, Vlad sits down with Max to unpack that journey and explore how AI is being used inside real business operations today. They discuss where AI genuinely saves time, why custom AI builds often disappoint, and how off-the-shelf tools like ChatGPT and QuickBooks can create real leverage when applied to the right workflows.

They cover:

•  Lessons from the construction industry and the 2008 recession 
•  The path from bankruptcy to building a new business 
•  Why bookkeeping was the opportunity Max chose to pursue 
•  How Booxkeeping scaled through franchising 
•  Where AI works well in finance and ops 
•  Why custom AI tools can be costly and impractical 
•  How AI helps evaluate franchise territories faster 
•  Using AI to automate notes, emails, and internal workflows 
•  Why efficiency gains matter more than hype 
•  How lower operating costs can become a competitive advantage 

This episode is for founders, operators, franchise builders, finance leaders, and anyone trying to understand what practical AI adoption looks like inside a real business.

Where to find Max Emma:

 → LinkedIn: https://www.linkedin.com/in/maxemma/

→ Company: https://www.linkedin.com/company/booxkeeping/

Work with Vlad:

 If you’re implementing AI in your operations and want hands-on help building real workflows:
 → https://www.elementsagents.com/

Subscribe / follow Vlad:
→ LinkedIn: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

AI adoption usually breaks when companies try to force it top-down or keep it stuck in experimentation.

Charlotte Lucas is Head of Strategy at ScorePlay, where she’s driving AI adoption across the business to help teams in sales, customer success, marketing, and operations move faster and work smarter. As ScorePlay competes in sports broadcasting with a lean team, Charlotte is building practical AI workflows that save time, improve execution, and help teams scale without losing the human touch. 

In this episode of Business AI Explained, we break down what AI adoption actually looks like when it works: how to get buy-in, where to start, which workflows to prioritize, and how to combine executive sponsorship with team-level ownership. We also cover how AI can support relationship-driven work, why shared learning matters, and how to build trust in AI outputs across the company. 

We cover:

•  Why AI adoption works best when leadership sponsors it, but teams own the use cases 
•  How to start with small, practical workflows that build trust quickly 
•  How ScorePlay is using AI across lead generation, deal desk ops, customer success, and marketing 
•  Why peer learning, internal sessions, and shared channels accelerate adoption 
•  How to match the right AI tools to the right teams 
•  What strong governance looks like: access, review loops, and exception handling 
•  How AI can strengthen relationship-driven work instead of replacing it 
•  Why automating high-impact, low-complexity workflows creates leverage across the business 
•  How unstructured data can become a strategic advantage with the right AI workflows 
•  What it takes to build an AI culture that works both top-down and bottom-up 

This conversation is for founders, operators, GTM leaders, strategy teams, and department heads trying to move from AI experimentation to real adoption across the company.

Episode length: ~45 minutes

👤 ABOUT THE GUEST

Charlotte Lucas
Head of Strategy, ScorePlay

Charlotte Lucas leads strategy at ScorePlay and is driving AI adoption across the company to help teams save time, improve execution, and support sales, customer success, and marketing at scale.

→ LinkedIn: https://www.linkedin.com/in/charlotte-lucas-ba479125/

→ Company: https://www.scoreplay.io/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

AI is no longer just a buzzword in sales, it’s becoming the backbone of how companies engage customers, qualify leads, and scale go-to-market.

In this episode, I’m joined by Adis Ceman, Regional Enterprise Sales Director at Cequens, a company building AI-powered communication systems across channels like WhatsApp, SMS, and voice.

We go deep into how enterprises are actually using AI today, beyond the hype.

We cover:

•  How AI chatbots are replacing missed opportunities in customer support 
•  Why most companies fail at AI
•  How to structure your data and prompts to get real results 
•  How AI is used in enterprise sales (lead generation, qualification, demos) 
•  The role of human touch in high-value deals (and why it still matters) 
•  How to use AI internally to train teams, build proposals, and move faster 
•  What signals actually matter when selling to enterprise clients 
•  Why speed + personalization are the real competitive advantages in 2026 

One of the most valuable insights:
AI doesn’t replace sales teams, it makes them faster, sharper, and more responsive.

If you're building a product, running sales, or thinking about implementing AI in your company, this episode will give you a clear, practical view of what works.

Episode length: ~24 minutes

👤 ABOUT THE GUEST

Adis Ceman

Regional Sales Director at Cequens - UAE

→ LinkedIn: https://www.linkedin.com/in/adisceman/

→ Company: https://www.cequens.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

Many companies are experimenting with AI.

But very few are restructuring their operations around it.

In this episode of Business AI Explained, Vladimir de Ziegler sits down with Sean Griffith, founder of Truffle, to discuss how AI is reshaping hiring, software workflows, and internal operations.

Sean explains how his team is able to produce the same level of output with fewer than 10 people compared to what he previously experienced inside a publicly listed company doing over $300M in ARR.

The conversation explores how startups and modern teams are beginning to replace traditional software tools with AI-driven workflows and how leaders can rethink operations to become fully AI-native.

Sean also explains how Truffle is redesigning the hiring process using AI-assisted candidate screening, transcription, and evaluation to help HR teams move from hundreds of applicants to a shortlist much faster.

The conversation covers:

• How startups can control costs when rolling out AI features
• Quick SEO opportunities to appear in LLM search results
• How developers are replacing traditional software with Claude Code
• How to structure operations for AI-native teams
• Which tools and workflows companies should automate first
• How AI is transforming hiring and recruitment processes

If you're building products, leading a startup, or exploring how AI can reshape your internal operations, this episode provides practical insights into the next generation of AI-native companies.

Episode length: ~30 minutes

👤 ABOUT THE GUEST

Sean Griffith

Founder of Truffle

→ LinkedIn: https://www.linkedin.com/in/griffithsean/

→ Company: https://www.hiretruffle.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.