Shiran Brodie, Head of Growth and Marketing at Softr – Interview Series

Shiran Brodie, Head of Growth and Marketing at Softr, is a growth marketing executive with extensive experience scaling SaaS companies through product-led growth, go-to-market strategy, and brand development. At Softr, she leads the company’s growth and marketing efforts as it expands its AI-powered no-code platform. Previously, she held leadership roles at Plasmic and Make (formerly Integromat), where she helped drive rapid growth, build high-performing marketing teams, and lead major product and brand initiatives. Her background spans growth marketing, product marketing, content, partnerships, and customer acquisition, with a strong focus on helping technology companies scale efficiently.

Softr is an AI-native, no-code platform that enables businesses to build custom internal tools, client portals, CRMs, dashboards, knowledge bases, and other business applications without writing code. The platform combines an AI-powered application builder with built-in databases, workflow automation, user authentication, permissions, and integrations, allowing organizations to create production-ready software from natural language prompts. Trusted by more than one million users worldwide, including teams at major enterprises, Softr’s mission is to make business software creation accessible to non-technical users by replacing complex development with intuitive visual building tools that help companies automate operations and streamline workflows. In 2026, the company expanded its vision with an AI Co-Builder capable of generating complete business systems—including databases, applications, and business logic—from a single prompt, positioning Softr as a leader in the emerging AI-powered business software market.

You were the first marketing hire at Integromat and helped lead its transformation into Make, one of the most recognizable brands in no-code automation. Looking back, what were the most important marketing decisions that turned a powerful technical product into a category-defining platform, and how are those lessons influencing your work at Softr today?

When I joined Integromat, the platform was still positioning itself around integrations and there was an internal belief that we were for developers, despite calling ourselves a no-code platform. After hundreds of customer interviews with operators, it was very clear the positioning angle was around end-to-end workflow automation for operators. The rebrand to Make wasn’t just a name change, it was a deliberate signal that we were building for a new kind of user: someone who wanted to build, not just connect apps. We leaned hard into that builder identity, and it gave us a positioning anchor that held even as the market got crowded. Today, in Softr, we’re now in a newly crowded market with AI, so leaning into what makes us truly differentiated- building secure business software with AI your entire team can use.

Softr recently launched its AI-powered app builder, which can generate fully functional business applications from a single prompt. What separates production-ready AI app builders from tools that primarily generate prototypes or demos?

The honest answer is: what happens when you actually need it to work with real users and real data.

Most AI app builders today are extraordinarily good at generating something that looks like an application. The gap shows up when you ask harder questions: can real users log in with different permission levels? Can business users integrate it with their existing stack without fear of exposing API keys? Does it handle edge cases, or does it assume a perfect happy path?

With Softr, our definition of production-ready means the moment you hit publish, you have a real application connected to real data, shareable with real users immediately, no additional setup, no code to maintain. The hardest parts of software building: auth, user management, permissions, security, hosting are handled out of the box, not bolted on after.

We’re seeing an explosion of AI-powered app creation platforms. From your perspective, which parts of software development are truly being transformed by AI, and which parts still require significant human judgment and expertise?

AI is genuinely transforming the parts of development that are high-repetition and low-context: generating boilerplate, scaffolding data models, writing automation logic for well-defined workflows, suggesting UI patterns. Things that used to be inaccessible to non-technical people. I’ve also noticed personally that people tend to solve problems using AI moreso now than diving into forums or communities or contacting support. So it’s helping people learn and upskill faster as well.

What still requires human judgment is everything that depends on knowing the business. AI doesn’t know which workflows matter most, which edge cases will actually happen, or how the person using this tool actually thinks. It doesn’t know that your invoicing process has a weird exception for certain clients, or that your team checks Slack for notifications but ignores email. There are many ways to solve a problem, the right solution is the one that best fits your business.

The most effective builders I’ve seen use AI to move fast on the parts where speed matters, and slow down to apply their own judgment on what actually needs to be built, the logic, and what the experience should feel like. AI is also a useful thinking partner even in that judgment phase.

Having led the rebrand from Integromat to Make during a period of rapid growth, what are the biggest lessons you learned about positioning, messaging, and brand building in highly competitive software markets?

Positioning, messaging, and brand go hand in hand, but you don’t always need to work on all three at once. Brand is an investment, and the need should really exist before you make it. Timing matters too. Too early and you’re polishing something that hasn’t found its footing. Too late and the perception has already set.

What I do think is that in today’s market, brand has become more important, not less. Everyone is using the same value props, the same feature stacking, the same AI buzzwords. When the messaging all starts sounding the same, how you make people feel is one of the few ways left to actually stand out.

The rebrand changed that almost immediately. A new name and a visual identity refresh completely shifted how the platform was perceived. Suddenly it felt modern and accessible. The team felt genuinely proud to say where they worked. There’s something about a brand that people feel cool being associated with that changes everything: how they talk about it, how they show up in the workplace. That energy is contagious and it compounds.

Product-led growth has become the default strategy for many SaaS startups. What have you learned about the limitations of pure PLG models, and when does a hybrid approach with sales support become necessary?

We’re in a very different market in the AI era, and I think it’s changed what PLG actually looks like in practice. There are more tools competing for attention than ever before, which makes the word-of-mouth and community flywheel that pure PLG depends on much harder to sustain. People aren’t discovering tools through forums and communities the way they used to: they’re asking AI, attending events, and relying on peer recommendations in much smaller, more private circles.

That’s part of why layering a sales motion on top becomes necessary at a certain point, not to replace PLG, but to cover the gaps it leaves. And there’s an interesting irony here: even though sales requires more relationship-building, hand-holding, and trust, the deals it closes tend to be far more durable. When adoption becomes organization-wide rather than individual, you get lower churn, deeper integration, and accounts that are genuinely weather-resistant.

The PLG motion finds the champions. The sales motion converts them into customers the company actually runs on. 

At Softr, the goal is to help non-technical users build business applications without writing code. How do you see the relationship between no-code platforms and AI evolving over the next five years?

The distinction between “no-code” and “AI” is already collapsing, and I think in five years it won’t exist as a meaningful category separation.

Mariam, our CEO, puts it well: in the next five years, 80% of software will be built by non-developers. That’s not a prediction, it’s already happening. The question is what infrastructure makes that possible safely and at scale.

AI handles the scaffolding: generating the initial app, suggesting workflows, accelerating the parts that used to require technical knowledge. No-code ensures it’s built right, not just fast. It’s the layer that gives you a real database, real permissions, real auth, real automations-  the production infrastructure that AI generation alone can’t give you.

Developers focus on the genuinely hard 20%, more complex integrations, security architecture, performance at scale, rather than spending time on the routine work that AI and no-code can now handle.

The platforms that win this era won’t be pure AI code generators or pure drag-and-drop builders. They’ll be the ones that combine both: the speed and freedom of AI with the reliability and security of no-code.

You intentionally moved from larger, hyper-growth organizations back to earlier-stage startups. What advantages do small, lean teams have when building and marketing AI products in today’s environment?

At earlier-stage startups, there’s no multi-step approval chain. There’s no time for additional bottlenecks, they become expenses you simply can’t shoulder, especially in a market moving as fast as AI.

Small teams also make more opinionated decisions without design-by-committee. The best AI products right now have a strong point of view: about who they’re for, what they will and won’t do, what the experience feels like. That’s much easier to maintain at 10 people than at 100.

But honestly, the thing I value most about earlier-stage companies is the product proximity. When I joined Make, I was in love with the product. Same with Softr. I build most of my own tools and systems on it, and I encourage my team to do the same. That kind of genuine investment in what you’re building is harder to sustain as organizations grow and people get further from the product itself. Hiring people who are genuinely invested in the vision, not just the role, is something we’re very deliberate about at Softr.

Many companies struggle when product innovation moves faster than their ability to communicate value to customers. How can founders ensure that their messaging keeps pace with increasingly sophisticated AI products?

The discipline I’d recommend: find a positioning frame that’s true, differentiated, and has a very clear audience. Not “generic AI” , something specific enough that the right person reads it and immediately thinks “that’s for me.”

It should say exactly what you do, rather than reaching for a buzzword at the expense of clarity. In AI especially, everyone is tempted to sound sophisticated. The ones who cut through are the ones who sound clear. If I can’t take one look at your product description and understand what you do, I won’t take a second look.  I’ll just assume it’s not for me.

Founders tend to think that stamping “AI” on something is enough, because everyone wants AI. It’s actually the opposite. There’s no shortage of AI products in the market, positioning primarily around AI is the worst way to differentiate your platform. Is it true that companies are actively looking to purchase AI software? Yes. But with the level of competition, you have to prove why they should buy yours specifically. 

AI is dramatically lowering the barriers to building software. Do you believe this will create a new generation of entrepreneurs and business builders, and what opportunities does that unlock for non-technical founders?

Yes, and I’m living proof of it, which makes this one personal for me.

I’m not a developer. I never have been. But I’ve built the influencer platform we use to manage 125+ creators, our brand mentions tracker, our content writer portal, all without writing a single line of code. Five years ago, the biggest problem was getting non-technical people to invest time into learning no code, despite how much it abstracted code, because it still had a learning curve.

Today, AI has become the missing puzzle piece that has unlocked innovation as even a possibility for non-technical builders. That’s enormous. But I’d push back slightly on the idea that barriers have disappeared entirely. The new barrier isn’t code: it’s judgment. Knowing what to build, for whom, and what success actually looks like. 

There are hundreds of ways to solve any problem, and the ability to think in systems- to see how the pieces connect before you start building, is still a critical and deeply human skill. 

As someone who has spent years helping define emerging software categories, what characteristics will separate the AI platforms that become enduring businesses from the hundreds of AI tools currently competing for attention today?

Ultimately, it’s a kind of focused adaptability that’s genuinely hard to develop. Work as we know it is evolving faster than most people’s ability to process it. 

Founders will need to stay focused on what matters while remaining open-minded enough to understand which trends are creating real shifts and which are noise. Making that judgment call of fad versus permanent change, and adapting without getting completely derailed is one of the hardest parts of building a software company right now. 

Focusing on a single market, ICP, or niche feels uncomfortable to many founders. My whole background has been leading GTM for horizontal platforms, which are notoriously hard to position and sell. But if you have a really well-defined persona and genuine demand from them, going deep on how to win that specific group can make or break the long-term resilience of your platform. And this goes beyond product to relationship building as well, because that’s one thing no amount of AI automation can replicate.

Thank you for the great interview, readers who wish to learn more should visit Softr.