Ian Johnson

Multiple Companies

Selected client work:

Paramount Pictures: (Fractional Product Lead) Designing the software for greenlighting movies.
ChatLabs: (Fractional CPO) 
Tonic Labs: (Fractional Product Lead) Working with leadership at high-growth startups in Fintech, Genomic Breeding, and Recruitment on product strategy and execution. 
Ultra VC: (Validating demand, pricing, and UXR Strategies) Advised 2023 batch of companies on strategies for validating demand, pricing, and execution of user research. 
Titans Legal: (AI Product Strategy) Consulting on Gen AI implementation strategy for major law firms.
Helios: (Product Strategy) Enabling anyone, anywhere, to profit from saving our planet through Solar investment.

Product Management Consultant

On Deck

Founder Fellow

Lasso (Acquired)

A pioneering AI-powered platform designed to redefine the creator marketing space for SaaS marketers. By facilitating the efficient discovery, management, and performance analysis of millions of creator profiles, Lasso enhances marketing strategies with data-driven insights and automates key processes to measure ROI effectively.

Co-Founder and CEO

Flow Commerce (acquired by Global-e)

The leading platform for cross-border ecommerce, enabling SMB brands to go global and technology that powers Shopify's native cross-border ecommerce platform (Shopify Markets Pro). Selected by Shopify through competitive RFP as sole technology provider for native cross-border ecommerce API/capabilities.

Responsible for product strategy that helped scale and grow some of the fastest-growing DTC brands in the world.

Flow is a SaaS platform that enables retailers to sell and expand internationally, providing end-to-end functionality, including localized pricing, marketing and payments, tax and duty calculation, and global logistics. Supported by venture partners, including Bain Capital Ventures, Forerunner Ventures, and Fung Capital.

Principal Product Manager

Senior Product Manager

Showtime Analytics

Responsible for the product portfolio of business intelligence, customer, and marketing analytics products for Showtime Analytics and Showtime's joint venture with Alibaba Pictures in China.

Showtime Analytics is a SaaS platform aimed at providing the movie industry with an intelligent software solution that is built to understand, communicate, and optimize relationships with moviegoers. Showtime Analytics is supported by partners including Alibaba Pictures and comscore.

VP of Product Management

Accenture

Consultant at Accenture experienced working with large organizations in the technology & financial services industries. 

Client work included;
- Product Marketing Production lead for EMEA at Google 
- Product lead at global financial institutions 
- Analytics and reporting across ad tech sectors

Consultant @Google

Management Consulting Analyst 

eir Ireland

Programme manager of eir's Customer Experience (CX) programme for eir Technology.

Program Manager

Business Operations Specialist

Product leader specializing in helping B2B SaaS and Consumer companies explore new segments, tap into emerging markets, and scale up existing ones.

Key Clients include;
ChatLabs by Writingmate.ai: (Product Strategy and GTM) Bringing private, secure, and customizable AI models in one place.

Paramount Pictures: (Fractional Product Lead) Designed the software used to greenlight movies.

Tonic Labs: (Fractional Product Lead) Working with leadership at high-growth startups in Fintech, Genomic Breeding, and Recruitment on product strategy and execution. 

Ultra VC: (Validating demand, pricing, and UXR Strategies) Advised 2023 batch of companies on strategies for validating demand, pricing, and execution of user research. 

Helios: (Product Strategy) Enabling anyone, anywhere, to profit from saving our planet through Solar investment. 

Track record of enabling B2B SaaS companies to accelerate their path to product-market fit through hands-on product strategy development, rapid experimentation, and execution. 

Designing processes and systems that enable high-growth teams to leverage market and user research to quickly ship the right solutions to end users.

Leveraging experience spanning pre-seed startups to Fortune 500s, including other collaborations with Andreessen Horowitz and ReFace.

For fractional or speaking engagements, please email contact @ ianjohnson.io

If sending a connection request, please include a note.

Founder

Whispermate - ai voice to text, open source

Building AI products for creators and businesses.

Writingmate.ai — Write, generate images, create videos. All frontier AI models in one place. No subscription hell.

Mentioned.to — Get visible on Reddit, Google, and AI search.

AIDictation.com — Voice to text, fast.

Previously Meta. Engineer → founder.

Let's connect.

🔮 Artem Vysotsky

weekend project: spin up your own OpenClaw instance from Telegram....

for context: openclaw has 157k github stars and karpathy called it the most incredible sci-fi thing hes seen. but almost nobody is actually running it because the setup is painful. docker permissions, api keys from three providers, oauth callbacks to localhost that break

so i made a telegram bot where you send /create and get your own openclaw instance in 60 seconds. container on fly.io, unique api key through openrouter with a hard spending cap, persistent storage. everything managed through telegram commands

the whole thing is about 15 typescript files. grammy for the bot, fly machines api to provision containers, openrouter management api for per-user keys with dollar limits, supabase for state.

heres the part that almost killed the project

telegram requires stars for digital goods. no stripe option. i figured fine, stars are stars. then i looked at the withdrawal math

users pay roughly $0.02 per star. when i withdraw as a developer i get $0.013. thats a 35% cut. plus a 21 day hold. and the payout is in toncoin not dollars

so my $45 subscription actually nets me about $29. had to redo all my pricing once i figured this out

the interesting learning: the hard part wasnt the code. it was the integration details. openrouter lets you create api keys with dollar spending limits per user which eliminated the need for a custom proxy.  fly machines api lets you create containers programmatically. telegram handles the checkout flow. once those three clicked together the rest was just wiring

each subscriber gets a container with 2 vcpu and 2gb ram, $15/mo in ai credits that work with any model including opus 4.6, and topups from $10 to $1000. every instance is isolated. separate container, separate volume, separate api key

mentioned.to - get true ai visibility via reddit

What's new in Mentioned[.to] this week

The biggest update this week: we used human-in-the-loop feedback to retrain our comment and post generation. Every reply and post now follows best-in-class practices — more natural, more relevant, and significantly better at driving real engagement.

We also redesigned the Competitors page with a tabbed layout, stacked area charts, and date range filters - making it much easier to track how you stack up over time.

Reddit search got a major upgrade. You can now search across all of Reddit globally, not just your tracked subreddits. It's faster and more reliable.

Across the board, we unified action buttons, polished interactions, and tightened up the overall UI.

Claude Code has been deployed globally at Meta for several months now. Meta also has an internal product built on top of the Claude Agent SDK, which has fundamentally 80% feature overlap. Most recently, Meta also moved into Google Chats instead of its internal chat system.

This is interesting to say the least... Meta uses now third party software from competitors since it want able to do it internally.

AI can build anything now. Can you manage it?

Claude Code is building Clawmaker...

I left it running just to write this post.

The more I work with these AI coding tools, the more I realize where the next frontier is — and the bottleneck.

It's our mental capacity.

Once I figured out how good Claude Code was back in October, I immediately started building four projects in parallel.

In reality? This isn't working well for me.

My brain is running at 3x speed trying to keep up with every project and maintain context across all of them. It's exhausting.

Why? Because there are no good frameworks yet. No established understanding of how to actually operate these tools at scale.

Some people in my community are trying to scale themselves by building teams of agents — each one working on different projects simultaneously.

But it's not working yet.

It's still slop. We still need human oversight. 

And yet... I wonder if we'll be able to scale further.

It reminds me of levels of seniority within large organizations.

At Staff Level, you own one very large project. Think: an army of 5-10 agents. This is doable today. We can kind of manage multiple agents working on different features of the same codebase.

At Director/VP Level, you start thinking in bets, risks, and portfolios.

"We have 100 billion tokens to spend. How do we allocate them efficiently? How do we not fail completely?"

One high-risk, high-reward project. One that extends an existing product. One focused purely on maintenance.

Then come horizons, strategy, resource allocation.

Here's the thing that might sound crazy:

Just as we scaled ourselves from ICs to managers to VPs to executives... we will eventually scale ourselves to VPs of agents.

I think this is hiding in plain sight.

We're going to work with AI more. We're going to gather more data on how we operate with these tools. That data will train the next models.

It's a perfect environment for AI to develop itself.

The human becomes the executive function. The strategic layer. The one who sets direction and manages risk across a portfolio of AI-driven projects.

Not managing people anymore. Managing intelligence.

But here's the uncomfortable truth:

Can every person scale themselves to that level? No. Absolutely not.

Some people have far greater mental capacity than others. The ability to hold multiple complex systems in your head, context-switch fluidly, think in portfolios and probabilities — this isn't evenly distributed.

Very few people will command armies of agents.

The leverage gap is about to become a chasm.

One person with the right cognitive capacity + the right frameworks + unlimited AI compute = what used to require entire companies.

And most people won't be that person.

We're not there yet. But the path is becoming visible.

The question isn't "can AI code?" anymore.

It's "can humans scale their cognition to manage what AI can now build?"

And the harder question: "who gets to?"

taplio

The Battle

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🔮 Artem Vysotsky

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🔮 Artem Vysotsky

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Engagements

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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);}🔮 Artem Vysotsky's LinkedIn Performance

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