The next generation of no-code is AI-native.

By Dan Preiss

As a former Product Manager and lifelong tinkerer, my journey through the landscape of no-code tools has been marked by constant evolution. Companies like Bubble, Airtable, and Zapier have made significant advancements in this space, democratizing application development and empowering users across the board. Now, we stand on the brink of a new era fueled by the unparalleled potential of generative AI; the definition of ‘no-code’ is being rewritten.

Consider the traditional no-code approach, where various applications are pieced together to create a complete system — Airtable acting as the back-end, Softr.io as the front-end, and Zapier for integration. While each component is effective on its own, this setup is clunky, disjointed, and difficult to maintain.

The next generation of no-code is AI-native.

In this new phase, AI-first solutions are not merely enhancements to their predecessors; they are complete overhauls of the software development lifecycle — edging us closer to 100% AI-generated software development. AI-native no-code tools, in stark contrast to traditional ones, will understand your workflow needs and autonomously craft an application — from front-end to back-end, without the need for multiple third-party tools.

The paradigm shift is profound, and the next generation of no-code solutions will be markedly different:

• AI-Driven Software Planning: Imagine AI agents that don’t just follow instructions but engage with users, deriving intricate requirements and translating them into comprehensive user stories and technical architectures.
• From Drag-and-Drop to Conversational Interfaces: The emergence of natural language as code is not just a feature — it’s a revolution in user interaction, enabling complex application building through intuitive dialogue.
• Opinionated Guidance: AI agents equipped with the capability to suggest and refine requirements based on user-provided inputs like drawings or screenshots.
• Seamless Full-Stack Development: We’re talking about AI-generated user interfaces seamlessly integrated with back-ends, all within a unified platform, bug-free.
• Intelligent Workflows for Complex Scenarios: Beyond just automating tasks, AI-native tools are poised to handle complex decision-making, reshaping traditional workflows.
• Effortless Integration: The future is about integration without barriers — dropping API docs into a system and watching as the AI flawlessly binds disparate applications.

Redefining software development

Across the spectrum, startups are emerging, each tackling a distinct phase of the development lifecycle. From AI co-pilots enhancing human efficiency to platforms focused on fully automating UI generation and back-end workflows — the landscape is rich with new entrants.

Yet, the journey towards an end-to-end, full-stack, no-code solution capable of building a full application from the ground up using natural language is not without challenges. The current iterations of Large Language Models like GPT-4, while impressive, still face limitations. Presently, AI code generation methods are prone to errors and lack the accuracy needed for end-to-end application development. This is precisely why code generation co-pilots exist rather than full-blown code generators. However, as these models evolve, they are expected to enhance their contextual understanding, improve their ability to interpret requirements more accurately, and better understand existing codebases. We foresee a future where the integration of these technologies will yield full-stack, robust, error-free applications fully generated by AI in certain constrained environments.

“Product teams of one”

We envision a future transformed by AI-native no-code tools, where the concept of a ‘product team of one’ becomes a tangible reality. This means an individual “AI PM”, can single-handedly manage the full spectrum of a digital product’s lifecycle. With AI’s prowess, non-technical domain experts can now lead and execute complex tech projects, liberating them from the constraints of traditional team dependencies. This evolution fosters a new era where creativity isn’t hindered by technical capacity constraints.

The potential operational efficiencies are staggering — leaner teams, reduced opex, and accelerated time-to-market. This paradigm shift in team structure will redefine what it means to be a modern organization.

A new dawn for SaaS

The AI-native no-code revolution will have a profound impact on the SaaS industry. We’re not just talking about incremental improvements; we’re envisaging a scenario where traditional applications are supplanted by bespoke, 100% AI-generated solutions. Vertical applications, in particular, could face significant headwinds given that 90% of the functionality, regardless of industry, remains the same, and 10% are really just customized features specific to the sector’s unique business processes. We plan to unpack this opportunity in our next blog.

Looking forward

I’m personally really excited about the next era of no-code tools and would love to grok with anyone interested in this area. If you’re building or investing in this space or think I’m missing companies in the market map above, please reach out!