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How Coding Systems Drive Better Trades

Ran Aroussi · March 6, 2026

Author · Entrepreneur · Artificial Intelligence · Leadership · Finance · Technology · Public Speakerin

Interview with Ran Aroussi

How Coding Systems Drive Better Trades — Ran Aroussi

Podcast: Invest in You

March 6, 2026 · 1 hr 7 min

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Key topicsBeyond the Chatbot: How AI Can Turn a Business Into a Self-Driving OrganisationMoves the conversation beyond ChatGPT and individual productivity toward AI operating at the organisational level. Ran can explain his vision of businesses where work naturally moves forward: proposals are aggregated, tasks progress, people are nudged when action is needed and drafts are created without someone having to constantly tell an AI what to do.Load Bearing — Why Production AI Agents Need a Layer That Takes the WeightRan Aroussi has built the layers other people's software runs on for 30 years, from ad engines serving 3 billion ads a day to yfinance, now installed more than 30 million times a month. Most teams treat agents as a model problem and reach for another framework, when the thing that breaks in production is everything underneath: memory, orchestration, audit trails, failure handling. He walks through what an agent-native layer has to do before autonomy is safe to ship, and why he wrote Production-Ready Agentic AI and built MUXI around declarative, inspectable configs. Listeners leave able to tell which parts of their agent stack survive real traffic, and which fail quietly.Plumbing — Why AI Money Ends Up With Whoever Owns the PipesRan Aroussi has spent 30 years building the parts of software nobody sees, from ad engines serving 3 billion ads a day to yfinance, downloaded more than 30 million times a month. Most of the attention in AI goes to the models and the apps sitting on top of them, and he argues the durable returns land a level below, the way operating systems, cloud, and DevOps each pulled the value down to themselves. He walks through what that means for agents in practice: who controls memory, orchestration, observability, and the audit trail when a run goes wrong, and why he wrote Production-Ready Agentic AI and built MUXI on open, declarative configs rather than closed tooling. Listeners leave able to work out which part of their own agent stack they actually own, and which part someone else will end up charging them for.View all topics →

About Ran Aroussi

Founder of VarOps • Building software and Resident AI into companies that can't afford to guess.

35+ years Production coding experience30M+ Open-source downloads per month50K+ GitHub stars3B+ Ads delivered daily by systems he built

Ran Aroussi has spent 35 years building software infrastructure. Now he thinks we’re building AI for businesses backwards.

Most companies are adding copilots, chatbots, and agents, then asking employees to learn how to use them. Ran’s argument is almost the opposite: people shouldn’t have to adapt to AI. AI should adapt to the company.

He’s the founder of VarOps, where he’s building what he calls "Resident AI": AI that lives inside an organization, learns how it actually operates, and works through the tools and workflows people already use. No new destination. No constant prompting. Ideally, employees barely notice it’s there.

The idea grew out of a problem Ran believes the AI industry has underestimated: AI doesn’t understand organizations.

A chatbot might have access to every document, meeting, and message in a company and still not understand why a decision was made, which unwritten rule matters, who actually knows how something works, or that the official process hasn’t been followed in three years.

Retrieval gives AI information. It doesn’t necessarily give it understanding.

Ran’s work focuses on building that missing layer: a living model of the organization itself – its knowledge, decisions, relationships, processes, and unwritten operating context. He describes it as an "Organizational Language Model" (OLM) rather than another LLM with access to company data.

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About this episode

The world of trading can feel like a high-stakes psychological battlefield, but forRan Aroussi, it’s a game of systems and logic. In this episode, Ran joins hosts Ivan and the team to discuss his transition from a 35-year coding and engineering background into the world of quantitative trading. Ran explains his ‘psychological reactionary’ style, which avoids deep fundamental analysis in favour of measuring price action and standard deviation. The group explores the burgeoning role of AI in market prediction, the necessity of emotional discipline, and why a simplified set of rules often beats a complex one.

KEY TAKEAWAYS

A background in engineering and coding provides a significant edge in trading by forcing an investor to view market data through a structured, systematic lens.

Successful trading doesn't always require complex math; sometimes, rules as simple as ‘buying after two down days’ can outperform broader indices like the S&P 500.

AI won't necessarily replace traders but will shift their role from manual execution to ‘orchestrating’ agents that can recognise patterns and predict support/resistance levels in real-time.

In the trading world, the ability to stick to a predefined system (discipline) is often more valuable than raw intelligence or the ability to predict the future.

A common mistake in backtesting is using the same data set repeatedly to find a ‘sweet spot’, which leads to strategies that work on past data but fail in live markets.

BEST MOMENTS

"I don't think we're great value investors. Coming from programming, you tend to type a few things and see a result."

"The markets are not efficient; otherwise, nobody would make money outside of investing in the S&P."

"My job is no longer typing; my job is to orchestrate and give the strategy and a set of rules and direction to the AI."

"If there's something that the market gives you, it's constant feedback. You need to know what's not working in order to know what to improve."

"I'd rather not lose 50% on a stock than gain 2,000% on a stock because I can't predict it. I'd rather make the easier bets."

Ran Aroussi

X @aroussi

Free book productionaibook.com

LI https://www.linkedin.com/in/aroussi/

Books by Fredrik Sandvall

Options Strategy: Build to Keep. Ready to Sell Tomorrow.

For founders and CEOs who want businesses that compound in value, stay under control, and are always sale-ready.

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The Abyss of Finance: Trust, Leverage and the Cycles of Collapse

For investors and leaders who want to understand why financial systems break before they do.

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About the Podcast

Invest in You is a global podcast where entrepreneur and investor Fredrik Sandvall shares practical ideas and conversations with founders, investors, and operators. Episodes focus on investing, entrepreneurship, and building long-term control and freedom.

Occasionally joined by his sons Ivan and Charlie, the show offers both experience-based insight and a next-generation perspective.

Listeners in 155+ countries tune in to think clearer, act smarter, and build with intent.

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Guest: Ran Aroussi