Developing senior managers to lead high-performing agencies | Leadership coach | Scaled from start-up to 8-figure agency

I help companies grow by developing their most valuable asset: their leaders.

For over a decade, I've worked at the intersection of leadership development and data-driven results, showing organizations that investing in people isn't just good culture but good business.

My approach is straightforward. I design performance management systems that actually motivate people while building cultures where psychological safety and accountability coexist. I strip away leadership fluff to focus on what works: targeted people development that connects directly to business outcomes.

As a consultant, I partner with companies looking to transform their leadership teams through practical skill-building and honest feedback systems. I help organizations create environments where diverse perspectives are valued and teams feel empowered to innovate. My clients appreciate that I don't sugarcoat challenges, but I'm always in their corner.

My background in digital marketing gives me a unique perspective on measuring what matters, whether that's campaign performance or leadership effectiveness.

I'm passionate about sharing what I've learned from studying influential thinkers like Daniel Goleman, Robert Greene, Dale Carnegie, and Kim Scott. More importantly, I share what I've learned from being in the trenches myself as an executive balancing business demands with family life.

The best companies know that leadership excellence drives business success. If you're ready to make that connection explicit in your organization, reach out and let's discuss how I can help.

Kim Fitkin

At MetaCTO, we build custom mobile apps that help businesses grow new revenue streams, create online communities, increasing customer LTV with digital products, and make client communication more personal.

Christopher Fitkin

What is tech debt?

Can you avoid it? Are you already doomed?

Imagine you bought a new car.

At first it runs great! Then the tires wear down. The oil needs changing. Maybe the battery starts acting up. This doesn’t mean the car is “broken”… it’s just normal wear & tire. But requires maintenance.

Tech debt is the same thing.

As products move faster, change direction, accumulate features… the system naturally degrades. Every shortcut, workaround, or rushed decision adds wear & tear (especially when speed is involved).

I’ve worked with with massive corporations and early-stage start-ups… and they ALL struggle with tech debt.

The mistake is treating it like a giant rewrite or a special cleanup project.

The real solution is boring & continuous.

Every feature should leave the codebase slightly better than you found it. Small refactors. Clear abstractions. Feature flags. Cleanup along the way, done as part of normal work, not during a crisis.

So no, you’re not doomed. 

You just need to make sure your team is doing the boring things right.

I’m genuinely worried about junior engineers.

Okay, let’s get this out of the way (I’m annoyed that I even feel the need to say this): Yes… AI is useful. (We use it every day. It makes our teams faster. That’s not the debate.)

The problem is what it’s removing from the learning process - especially for devs coming up after c. 2023.

For most of my career, junior engineers (myself included) learned by doing the hardest, most boring part of the job. The only question you were ever asked on an interview: “Can you write code.”

The grind of banging out massive amounts of code everyday is where my instincts developed. I learned what a bad abstraction felt like because I had to live with it. I learned why certain shortcuts were dangerous because I broke things.
 Then, I had to know how to fix them.

But that critical implementation stage is disappearing fast.

Today, AI can generate decent code in minutes. Which is great… unless you never learned how to reason about that code without help.

That’s the part I’m worried about.

So here’s my advice to anyone early in their career (and yes, I know this sounds old-man-y… I don’t care):

Build something on your own time WITHOUT AI. Pick a project: auth, database, API, frontend, deployment. Whatever.

You will struggle. You will make bad decisions. You’ll stay up all-night scanning thousands of lines of code until your eyes almost pop out of your head.

And that’s the point.

Because later, when you do use AI (and you should), you’ll know when it’s wrong. You’ll know when something feels off. You’ll be able to diagnose a problem & understand why a solution works.

My prediction: the juniors who put in reps (without the AI crutch) will move up the ladder faster & be the seniors all the vibe-coders rely on.

I really hope more people talk about this!

Senior dev: “Yeah, we f*cked that one up - fix it by Wed.”
New dev: “Okay so just to give some context here, this issue is actually the result of a few interconnected factors, one of which dates back to a decision that was made before I joined the team. There were also some edge cases that weren’t documented, and the requirements changed slightly after implementation. I want to be clear that the code technically works as designed, but the design itself may not have accounted for all downstream effects. I’m still investigating root cause and will circle back with findings. Open to thoughts.”

After 20+ years working in companies big and small… the fastest way up the ladder is knowing how to communicate.

They ask a question - you give an answer.
They need something done - you give a date.

No one likes/reads 7 paragraph Slack messages. 🙂

Yes: AI can do 50% of the work

No: Businesses don’t have to give you 50% off

I had someone reach out recently and say: “You quoted this last year… but with AI writing code now, can you do it for half the price?”

Sorry, no!

Writing code has never been the rate-limiting factor. That’s maybe 20% of the work.

The real cost is planning, scoping, design, picking the right features, architecture, testing, validation, launching, and supporting the thing once it’s live. AI doesn’t magically solve decision-making.

I also see a lot of “it’s 90% done” projects built in Replit or with vibe-coding tools.

But in reality, 4 days of AI coding can easily create 4 months of technical debt. Security issues, bad abstractions, brittle logic - all the stuff that only shows up later, when it’s expensive.

We use AI across our entire stack at MetaCTO. It’s a huge multiplier.

But it multiplies experience, it does not not replace it.

7 mistakes to avoid if you’re building an app in 2026:

1. Starting with features instead of a real problem
2. Overbuilding/overthinking v1
3. Assuming users will “figure it out” without onboarding
4. Ignoring performance until users complain
5. Not prioritizing/optimizing your monetization strategy
6. Shipping without a rollback plan
7. Treating security as an afterthought

What you should be focusing on (from someone who's built hundreds of successful apps):

A. Clarity

Be painfully clear about who the app is for, what problem it solves, and what success actually looks like. 100% of failed apps aren’t 100% sure what their users actually want/need.

B. Reversibility

Real speed comes from being able to undo mistakes quickly. Feature flags, small rollouts, boring architecture, and clear rollback paths let you move faster, safely.

C. Retention & revenue - early

If users don’t come back or won’t pay, nothing else matters. Not your tech stack. Not your cool AI features. Not how “clean” the codebase is. Value > vibes.

If you want your app to be successful in 2026… make fewer bad decisions, earlier.

For anyone hiring a software dev team:

You can have 2 of these 3: good, fast, cheap

If you want good & fast, it ain't gonna be cheap.
If you want cheap & fast, it ain't gonna be good.
If you want cheap & good, it ain't gonna be fast (probably not good either).

I’m curious: Does anyone know companies zigging (no-AI) while everyone else is zagging (AI)?

Genuine question.

Everywhere I look right now, teams are going all-in on AI… AI in the product, AI in the workflow, AI writing the code, AI reviewing the code, AI deciding what to build next.

But I keep wondering if there are companies intentionally doing the opposite.

I mean teams that are making a deliberate, principled bet on no AI (or extremely constrained AI) in engineering or product.

An interesting thought I’ve been having…

If everyone is outsourcing thinking, judgment, and implementation at the same time, is there upside to being the team that doesn’t? The one that forces a deeper understanding, hard-earned intuition, and human originality/creativity > prompt mastery?

Are there companies doing this on purpose? 

Or is “AI everywhere” already so baked in that opting out is impossible?

Would love real examples (or strong discussion/arguments 😉 ) in the comments!

At the risk of sounding like a grumpy old timer…

I miss when software engineers openly cared about the craft.

Not just shipping tickets or hitting sprint goals… but genuinely caring about how things were built. Debating tradeoffs. Obsessing over edge cases. Wanting to make something cleaner or faster even if no user would ever notice.

But I don’t think that mindset disappeared because engineers got worse or lazier. I think the incentives changed.

As a founder now, I see it from the other side.

The industry trained people to optimize for survival: pass interviews, don’t stand out too much, don’t set a pace you’ll be expected to maintain, protect your energy because layoffs are always lurking. 

Add AI and the pressure to “just ship” gets even stronger.

The tension I wrestle with as a boss is “How do I build a team that ships fast AND still cares about quality, learning, and long-term thinking?”

I’m actively trying to solve this inside my own company:

- Rewarding engineers for good decisions (not just output)
- Making time & space for refactors, cleanup, and tech debt
- Being explicit that “working smarter” and “working more” are not the same thing

(I think my team appreciates the last one most)

I genuinely don’t want a team that’s so optimized for productivity and safety that curiosity disappears.

My thinking is if engineers only ever optimize for short-term output, they don’t grow. And if leaders only ever reward output, they shouldn’t be surprised when actually creativity & craftsmanship suffers & fades away.

I don’t have a perfect answer yet. I’m experimenting in real time.

Bad subscription infrastructure is an app killer.

That’s why we partnered with RevenueCat!

Garrett Fritz and I have helped companies build A LOT of mobile apps at MetaCTO. And one pattern shows up over and over again: the product is solid, users like it…

But subscriptions = the bottleneck

Failed receipts, broken trials, App Store rejections, analytics you don’t trust, teams duct-taping billing logic together. I could go on…

What some companies forget is that subscription infrastructure is part of a growth strategy (just like marketing or sales). If it’s shaky, everything else suffers.

That’s why we're so excited to partner with RevenueCat.

They solve the unsexy (but critical) stuff: billing edge cases, renewals, trials, receipts, integrations, and clean data. It means our clients launch faster, pass reviews faster, and don’t have to rebuild their paywall 6 months in. 

Wins all around!

If you’re building a subscription app and want infrastructure that scales instead of fighting you, happy to chat.

I hate seeing #ad. 99% of the time, I won’t use that app / product / service / whatever.

My brain literally goes: “nope, skip.” I know I’m not alone.

Creators hate it too.

They know that if they’re pluggin something and it feels forced… pitchy… salesy, their trust with their audience (built from years of hard work!) is gone.

So what does work? No #ads. But advocates.

I’ve seen high-performing apps avoid traditional #ad entirely by doing rev-share partnerships with creators. The trick is to actually make creators LOVE the product.

The worst way to do this is approaching a creator and saying… “Here’s a script. Post 3 times this month say these bullet points word-for-word.”

Instead, I advise companies to:

- Give creators real access to the app (full premium, not a demo)
- Let them decide how & when it shows up in content
- Pay them when it works (rev-share)

This works 100x better because people don’t necessarily hate marketing. They hate being sold BS from people who obviously don’t care.

2022: Runna rejected by App Store. 2026: 
Runna growing ~30× YoY & raised £8M+.

(The difference was 1 week with RevenueCat)

@Runna was started by @Ben Parker and Dom Einhorn Maskell, two runners who wanted to make personalized coaching accessible. They brought in Walter Holohan (now their CTO) to build their MVP .

Early on, things were going great from their website… so naturally, their next step was a mobile app.

But then Runna ran into a wall.

The 1st version of the app linked out to web payments (so Apple rejected it immediately). And anyone who’s shipped a subscription app knows how deflating that moment can be… weeks/months of hard work blocked by a simple compliance detail.

Instead of trying to hack together their own in-app purchase system, Walter signed up with RevenueCat.

1 week later (after adding in-app purchases), they were approved on the App Store!

With subscriptions handled… the team focused on training plans, personalization, performance, integrations.

30× YoY subscription growth
£8M+ raised
Scaled from 2 to 16 engineers

Runna is one of the best examples I’ve seen of how important it is to get the infrastructure right early.

This is why we’re so excited to partner with RevenueCat:

a) You launch (& get approved) faster… without weeks of trial-and-error

b) Your team focuses on product, not billing edge cases - no DIY paywalls, receipt validation, or renewal headaches

c) Your monetization scales with you

If you’re building a subscription app and want to get the foundation right the first time, shoot me a DM!

Happy to talk through your idea.

I see a lot of companies try to build apps in crowded spaces (fitness, fintech, you name it). Most don’t survive Year 1.

One advantage we have at MetaCTO is visibility.

From 20+ years of experience & partnering with companies like RevenueCat… I’ve had a front-row seat to how apps survive Year 1: what they change, what they rip out, and what they rebuild when things aren’t working.

Take Ladder.

On the surface, they’re “just another fitness app” (one of the most crowded categories on the App Store). But what made them work wasn’t their initial idea. It was how they were willing to reinvent themselves.

- Pricing plateaued early:

They tore up their monetization strategy and rebuilt it based on how users valued the product.

- Growth stalled:

They stopped listening to investors and ONLY listened to members instead. Their users didn’t want more workout videos… they wanted a motivation app. Ladder complied. (I believe this is why they became the highest earning fitness app in 2025)

- Engagement lagged:

They doubled down on brand, community, and meeting users where they already were (TikTok, Youtube, in-person community meet-ups).

20+ years has shown me that every successful app has been unafraid to reinvent themselves.

Please don’t be the company thats clings to the original idea and call it “vision.” 99 times out of 100, the first version is NOT the finished product!

I was told I was CRAZY for investing in SEO in 2025. But Jan 28th… we had 277 organic visits. So… maybe CRAZY smart?!

Jan. 2025: ~1 organic visit per day (on a good day)
Jan. 2026: averaged 100+ organic visits/day (277 peak)

Best part… these thousands of monthly visitors are people actively searching for mobile apps, software dev, and MVP development.

Here’s what’s working for us in the Age of AI:

- We treat SEO as a long-term investment

We started in December 2024 fully expecting nothing to happen for months. SEO only works if you’re patient enough to let compounding do its thing.

- We align SEO with how people use AI now

People don’t just “Google keywords” anymore. They ask questions. They research deeply. They bounce between search engines and AI tools. So we optimized for intent (not keyword stuffing).

- We use a simple formula

a. AI-driven programmatic SEO for volume
b. A small, consistent stream of human-written content for trust
c. A strong, performant website (server-side rendered, fast, accessible, mobile-optimized, clean structure)

That’s it.

This is also exactly how we build sites for clients now. When MetaCTO builds a website, we partner with strong SEO + content teams to bake SEO in from Day 1.

SEO didn’t die. Low-effort SEO did.

Happy to share what we’ve learned if you’re thinking about this for your own product!

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