Vibe coding will drive the next wave of innovation. Just don't look under the covers

From idea to impact, why tangibility matters

Ever pitched an idea only to receive pushback because people struggle to visualise your vision? Theory is one thing, but ideas can often fail to gain traction until your stakeholders see them in action.

For years, getting an idea off the page meant engaging with an external development partner who would translate your thoughts into working software - a highly skilled, time-consuming and costly activity.

AI has changed that.

Innovation, in the right hands

Today, LLMs and AI low-code platforms are giving innovators a new kind of power: the ability to translate raw ideas into tangible prototypes and proofs-of-concept, fast.

Want to test out an AI chatbot idea for your internal customer support team? With a few prompts and some tweaking, you can build a working prototype in hours instead of weeks. Want to visualise a new sales enablement tool or automate some manual processes? AI tools can help spin up early versions, complete with sample data and interface suggestions.

This is revolutionary not because it replaces the traditional product development lifecycle, but because it accelerates and empowers the earliest stages. It allows people closest to the problem to take the first step toward solving it.

The illusion of productivity

As these tools evolve, we can expect to see an unprecedented wave of experimentation. Innovators who were once stifled because they didn’t have access to specialist technical expertise can now explore, test and prove ideas on their own terms. 

Indeed, work that previously took a team of highly skilled people weeks or months can now be done in a matter of minutes or hours by a non-technical person. It would seem that software development has been reduced to nothing more than a few prompts - something that anyone can now do without the need for the middleman. 

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However, peek under the covers and you will find that your software is a long way from being production ready - there is no architecture, no automation, no security, no monitoring, no maintainability and no tests. That initial wow moment and sense of productivity is largely a performative illusion.

With vibe coding, a half-working prototype might make you feel you're 80% done, but you are only at the beginning of your product journey. The effort to close the gap - to create secure, robust, production-grade software - is still considerable.

Getting to production will mean, in all likelihood, throwing away your beautiful prototype. No engineer will ever want to own the generated code. It is simply too messy and unmaintainable. It has served its purpose, it's just not fit for purpose.

But that's okay. In trading quality for speed, you are intentionally swapping long-term success with something ephemeral - a throwaway artefact that has allowed you to validate an idea faster than ever. The whole purpose of vibe coding is not to produce production software. It is purely to innovate, experiment and validate.

Discovery, as vital as ever

Prototypes serve a hugely valuable purpose in software development. They build momentum. They galvanise support. They help decision-makers rally behind a vision faster than a slide deck ever could.

But whilst AI tools might have significantly reduced the cost of early stage validation, it is important to stress, they are not a replacement for the rigorous processes and disciplines required to bring a product to life.

Complex software still needs to be scoped, refined, architected, secured, tested, costed, resourced etc. And to do that you need to a thorough discovery process.

The fact that you can build a compelling prototype in a few hours might make you think that all software development has been similarly condensed, but in this regard, nothing has changed. You still need to:

• Understand the needs of real users and personas

• Identify technical risks, blockers and unknowns

• Define overarching governance and delivery approach

• Shape a delivery roadmap, prioritised backlog and system architecture

• Evaluate feasibility at scale

• Undertake a detailed competitor analysis

• Estimate and cost analysis

• And much more

The takeaway

The new wave AI no-code platforms will undoubtedly reshape how we approach early stage innovation. Every enterprise should be embracing this power today.

But, we are a long way from eliminating the need for software delivery experts altogether. Yes, we will see a generation of innovators but the move from prototype to production still requires the full rigours of modern software engineering, and will do so for years to come.