Building Consumer Software in the AI Era
Consumer software is one of the hardest categories to build a business, but the most rewarding to get right. Here's how the best founders are approaching it right now.
Introduction
Consumer software has produced some of the most valuable companies in history – Google, Meta, Netflix, Spotify, Airbnb – and it has also been a graveyard for more promising startups than almost any other sector. The same characteristic that makes it so attractive — building for billions of individuals, not procurement committees — is what also makes it so unforgiving. Consumers have unlimited alternatives of where to spend their time, money and attention, so introducing another app onto their phone makes for an unbelievably high bar.
At True, we believe AI has the potential to disrupt entire categories of the consumer software landscape. We’ve been talking about this since 2024 – here are a couple of blog posts exploring our thinking on the market: New Consumer Markets With AI and AI Agents: Ready For Take-Off.
ChatGPT’s launch changed the way people engage with software forever – being able to speak to and message products in a natural language way opens up a whole new world of true one-to-one personalisation. A virtuous cycle opens up: more engagement = more data = more and shorter feedback loops = better and stickier products.
As part of our Consumer Tech content series with EUVC, we recently spent time with Neil Tanna and Graham Paterson discussing what it’s like building consumer software in the AI era. Here are some of the key takeaways.
Speed
Software has never been a durable moat by itself — features and entire products have always been copyable: Snapchat's stories/lenses being copied by Facebook is the classic example. AI hasn't changed this dynamic. In fact, it's made the copying faster.
Agentic coding companions like Cursor and Claude Code have collapsed the barrier to building software, enabling quicker speed to market and iteration of products. The lower technical barrier to entry means more innovation and choice for consumers, but also higher levels of competition and a higher bar for what counts as outlier traction.
Despite new tools, the same fundamental challenges exist: ideas fail, products change, competitors evolve, and consumer feedback is brutal. Speed of execution and iteration have become more important facets of teams to stay relevant and ahead of the rest of the market. That pace and intensity relies on a culture of urgency embodied by the founders. It’s one of the key traits we look for when backing Founders – as we discussed in this blog post).
Customer & product obsession
Being able to build cheaper and faster is a key unlock, but it doesn’t solve the more important upstream question: what should be built in order to cut through the noise and earn the right to a place in consumers’ daily lives? In fact, it makes it even harder – AI slop is a real risk.
Unlike enterprise founders, a consumer software founder needs to think deeply about psychology, human behaviour, aesthetics and design, habit formation and virality. Understanding customers and the problem at hand in an obsessive way is crucial. The best Founders we work with understand their audience and problem space so well that they continually deliver the best experiences and delight their users, in turn driving genuine love and advocacy for the product.
Feedback & learning loops
The ability for teams to continuously iterate by developing feedback loops and learning systems into their product development cycle has always been important.
However, in a world of increased speed-to-market from potential competitors, the best Consumer founders leverage their existing customer base for feedback data to help improve the user experience and get to product-market-fit faster. Competition might be able to copy features, but not experimentation cycles or what is already known from users.
The best Founders embed continuous experimentation into their culture, and combine (i) disciplined hypothesis-testing (tied to specifical goals or KPIs that are easy to track and test) and (ii) bets, which might be low confidence “swings” but with huge upside that can lead to big breakthroughs in the product.
Leveraging AI can also help bring automation to these processes, as well as enable experimentation at greater scale.
AI can’t simply create new products that will guarantee customer love, but it can help accelerate speed of learning and iteration, which is crucial in today’s market.
Distribution
In a world where building software is cheaper and faster than ever before, go-to-market strategy and accessing customers cost effectively is even more essential for an early-stage company.
The ability to swerve paid competition across Meta/Google et al, and instead, ride network effects and organic virality (word of mouth, owned communities, founder-led audiences etc.) is a real advantage, which teams should be heavily focused on.
Equally, acquisition channels themselves are volatile – what works on TikTok today, won’t tomorrow – so it requires an ongoing, adaptive trading mindset within a team.
As has always been the case (pre-AI), distribution is necessary but insufficient — it must be owned, it compounds only when paired with genuine retention and product love, and is a requirement from day one rather than bolt on after product-market fit. Today, the speed at which anyone can leverage AI and code new features simply makes distribution an even more important asset and prospective moat – a customer base of daily engaged users is much more difficult to replicate than new features.
If you're building in Consumer, get in touch!
Notwithstanding the challenges, Consumer software remains one of the most exciting areas to build in – and we’re excited to back the next generation of founders in the space. If you're a founder working on something, we'd love to hear from you.
We invest early (Pre-seed & Seed) and bring a genuine, decade-long obsession with consumer and retail to every conversation. Get in touch at vc@true.global.
Author: Mike Martin