At Being Guided we are bringing to market a new AI innovations that extend or replace an earlier generation of Software-as-a-Service (SaaS) apps: Vibe Coding¹. So, firstly, what is Vibe Coding, secondly, who's it for, and thirdly, why should you care? Here are the answers:

1. Vibe Coding is a terms first used by industry analyst Andrej Karparthy¹ to describe how you can generate software code by using AI to describe apps using natural language, where the term 'vibe' comes from "fully giving into the vibes, and forget that the code even exists".
2. Vibe Coding is for everyone. Even our largest customer, the UK National Health Service (NHS) is embracing next generation Software-as-a-Service (SaaS) apps built with AI-powered Vibe Coding. Elimating a £604million deficit¹¹ at the NHS has some influence here!
3. You can now avoid or replace expensive SaaS licences by engaging with AI-powered technology. We become your Vibe Coding Partner, empowering you to move beyond expensive first generation SaaS apps, using best-in-class AI technology.

At Being Guided we have a four stage Build process, which starts with Design Thinking⁸ and Value Engineering⁹ to generate a solid foundation for Vibe Coding. As explained below, Vibe Coding depends on having 'humans-in-the-loop' to provide Software Engineering.

Of course, AI is fast-moving and whether you just use SaaS apps or are a software publisher, you will want to know how to 'ride the AI wave' in a meaningful, effective way. As you will see in this Journal post, Vibe Coding is rapidly changing - new entrants appear, some acquired. No doubt, in the future, the Vibe Coding landscape and the capabilities of AI Agents will continuously evolve.

With our four stage Build process, just a few hours engaged with us at Being Guided can identify a starting point for Vibe Coding, where Design Thinking is all about getting the right breadth and depth of stakeholder engagement and where Value Engineering ensures a clear business case for engaging in a timely manner.

Design Thinking, applied.

Design Thinking maximises stakeholder engagement by fostering empathy and collaboration across the buying and selling cycle, whilst Value Engineering builds robust business cases using ROI models to defend value and quantify costs.

In the real world this means that the Chief Executive Officer will have one perspective, and the Chief Technology Officer or Chief Information Officer a very different, yet equally important view of Vibe Coding. Increasingly, this will include some experience of using AI tools.

There has to be an element of Experimentation driving the early stages of Vibe Coding.

Inspired by the Stanford d.school our Design Thinking is delivered as six iterative stages: Empathize; Define; Ideate; Prototype; Test; and, Implement. This offers a structured yet flexible framework to better understand and challenge assumptions and redefine problems.

01. Empathize
The first and most important stage in Design Thinking is Empathize. This where you are creating receptivity and rapport among a broad set of decision-makers and influencers as stakeholders in innovation, leads to trust. In turn, this generates the truth required to move to the Define stage.

02. Define
Clearly articulating the problem to be solved. After gathering insights, define the core problem in a human-centered manner. This stage is about synthesising observations and articulating the problem in a way that guides the creation of a compelling argument for a solution.

03. Ideate
Generating a range of creative ideas to solve the defined problem. This phase involves brainstorming and exploring potential solutions, encouraging out-of-the-box thinking. It's essential for innovation, as it embraces creativity in the discovery of effective outcomes.

04. Prototype
Turning ideas into tangible products. Prototyping means a hands-on approach to the rapid transformation of Current State, generating a simpler, more effective Future State with the right solution. Prototyping is crucial for visualising how the solution will work.

05. Test
Gathering feedback and refining the Prototype. Testing includes feedback collection on reactions to the solution offered. This helps in understanding the prospect's experience, identifying issues, and validating the effectiveness of what has been proposed.

06. Implement
Finalising the solution and closing the deal. The final stage involves finalising the solution design based on feedback, completing the development, and launching the product or service in question. This ensures that the solution is fully understood and ready for everyday use.

Value Engineering, calculated.

Design Thinking is strengthened by Value Engineering: mapping out a solid use case, financial justification and technology preferees for high-value products and services.

Value Engineering was originally conceived by Lawrence D. Miles⁹, a General Electric engineer. Miles' techniques have saved design engineers, manufacturing engineers, purchasing agents and service providers millions of dollars.

To quote Miles, it was necessary to show "why so much unnecessary costs exist in everything we do and how to identify, clarify, and separate costs which bear no relationship to customers' needs or desires."

Value Engineering eliminates waste and determines value over price. This is calculating the cost of purchasing (or crucially, not purchasing) any high-value product or service in a timely manner. It is quantifying time-based value versus the cost of delay or doing nothing.

As Value Engineers, we set the scene mapping your ideal customer's needs with your offering. This is where we apply Design Thinking to enable you to build receptivity, rapport, trust and truth with buyers - early and often.

From a financial perspective, we start with a simple question for the buyer:

What is the cost of NOT buying the product or service?

Firstly, let's look at the Return On Investment (ROI) Model - a general formula:

ROI = (Cost of Investment / Net Profit​)×100%

To adapt this formula for an As-Is vs. To-Be comparison, consider:

Net Profit: This will be the difference in profits between the Future State (To-Be) and the Current State (As-Is).

Cost of Investment: This is the cost incurred to move from the Current State (As-Is) to the Future State (To-Be).

Given the above considerations, the formula becomes:

ROI = (ProfitTo−Be​ − ProfitAs−Is​​ / Cost of Transition) × 100%

Where:

Profit To-Be = Profit or (benefit) in Future StateProfit As-Is = Profit (or benefit) in Current StateCost of Transition = Cost to move from As-Is to To-Be

Note: If you're measuring benefits other than strict monetary profits, such as time saved or other intangible benefits, ensure you can convert these benefits into a monetary value for this to be valid.

To calculate the Return On Investment (ROI) with the specified inputs, we can formulate several equations. Let's define the variables first:

BVAs-Is = Current State (As-Is) Business Value generated per annum without Solution.BVTo-Be = Future State (To-Be) Business Value generated per annum after investing in Solution.

COS = Cost of Solution.ROI = Return on Investment as a ratio relative to the Cost of Solution.

CoD = Cost of Delay per day when not investing in Solution.CoDN = Cost of Doing Nothing per day when not investing in Solution.

CoDday = Cost of Delay per day when not investing in Solution.

CoDNday = Cost of Doing Nothing per day when not investing in Solution.

Calculating ROI from Solution: Net_Gain - BVTo-Be - BVAs-Is

Calculating ROI: ROI - Net_Gain - CDI / CDIThe ROI is expressed as a ratio. Multiply by 100 to get a percentage.

Cost of Delay (CoD): This represents the loss per day by delaying the Solution purchase. Assume the delay starts from the beginning of the year and goes on for d days:CoD = BVTo-Be - BV As-Is (d x CoDday) - CDI / CDI

Cost of Doing Nothing (CoDN): This is the loss per day for not implementing the Solution. Similarly, for d days:CoDN = BVAs-Is - (d x CoDNday) - CDI / CDI

Vibe Coding. Experimentation works.

Consistent with the Design Thinking inspired by Stanford d.school⁸ I believe that it is vital that business and technical stakeholders fully embrace Experimentation as a state of mind that governs the Vibe Coding journey.

Simply put, the best place to start is with five steps that govern the Vibe Coding, which also flesh-out the Design Thinking and Value Engineering that drives a positive engagement:

01. Framing the Testable Idea.
02. Defining Evidence.
03. Selecting The Test.
04. Building the Prototype.
05. Executing, Analysing, Testing.

With this approach to Experimentation, underpinned by Design Thinking and Value Engineering, a Vibe Coding process can be incorporated in an Experimentation app: reinforcing best practices by creating a solution that embraces the following Entities (Objects):

Models
From generating high levels of engagement among all key stakeholders throufh Design Thinking, the Value Engineering process creates Return On Investment Models (ROI) Models for the seller's offer, where a solid business case for the buyer,. This defends value over price.

Projects
With a clear ROI Model in place, a Compelling Value Proposition is translated into a Project Plan. This includes setting out a hierarchy of Milestones, Tasks, Deliverables and Costs, mapped against the ROI Model created to generate a strong business case for the buyer.

Tasks
Project Tasks are assigned to Users where many Tasks can make up the Milestones and Complete Projects related to the Project Plan. Project Tasks utilise Activities for Tasks, Emails and Calls in Salesforce or Google AppSheet.

Resources
Human and Digital Resources are assigned to Project Tasks, defining named Users, fully supported by AI Augmentation or AI Automation options. Resources include customisable Record layout options for Skills plus Custom Objects (Entities or Tables) for eLearning and Certifications.

Storyboards
Alongside Snapshots, Storyboards are continuously updated via a Web Form and CRM app record, defining and iterating Problems and Challenges expressed in terms of both urgency, importance - and also, how they are mapped to Models.

Decisions
In moving from the what-if Projections of a ROI Model for a Compelling Value Proposition, the buyer and seler agree and continuously refine Value Engineering calculations for Purchasing against Economic Basis of Decision and Emotional Basis of Decision scoring.

Solutions
Over time, the Compelling Value Proposition emerges from a Mutual Value Discovery between buyer and seller. This is where progressively clearer Solutions are developed and documented, underpinned by a convincing Value Engineering and ROI Model outcome.

Checklists
The Checklist Module allows for customised Checklists to be used at each stage of a buying and selling cycle. One or more Checklists can be included in Tracking, where this can measure the change of status for each Checklist Item over time.

Objections
Combining in-depth human experience with an AI Assistant to work through predicted abd actual objerction handling situations. Example: "The customer says our price is too high compared to the competition. How should I respond?"

Calculations
Using Models to generate what-if Return On Investment (ROI) Calculations that results in a Clear comparison between Current State and Future State. This feeds into a progressive Mutual Value Discovery to result in a solid Value Engineering outcome for buyside and sellside.

Guidance
Again, combining human experience with AI Assistant to ask questions informing the right actions at key stages of say, a buying and selling cycle. Example: "We're in the negotiation stage of the deal. What are the most important things to focus on to close the deal successfully?"

Does history repeats itself?

Having worked with Salesforce technology for the past 20 years I remember the early stages of this Software-as-a-Service (SaaS) pioneer: it was simply faster, simpler and cheaper than what went before: namely, Siebel on-premise Customer Relationship Management (CRM) systems.

Fast-forward 20 years and just as Siebel was displaced by Salesforce as the global leader in CRM systems, today, we see AI-powered VIbe Coding as the disrupter of Salesforce (and other first generation CRM apps) for the same reasons: it is simply faster, simpler and cheaper.

Further back, over one hundred years ago, Mary Parker Follett (1868–1933) was a true pioneering management theorist whose work emphasised collaboration, integration, and the empowerment of individuals within organizations.

Follett advocated for “power with” rather than “power over,” promoting participatory decision-making, cross-functional teamwork, and the idea that authority should be rooted in expertise and situational needs rather than rigid hierarchies (Follett, 1924¹⁸; Graham, 1995¹⁹).

Follett’s insights into participatory management, integration, and empowerment are highly relevant to the Vibe Coding paradigm. Both approaches seek to flatten hierarchies, foster collaboration, and enable those with the most relevant expertise to drive innovation.

The difference is that, in 2025, AI-powered platforms have made this vision technically feasible at scale, transforming not just management but the very process of software creation.

No-Code. No problem.

Salesforce and first generation CRM SaaS apps are only one example of where Vibe Coding (with an AI-powered 'CRM Pro' Framework) and can lead to creating and replacing many SaaS apps. To quote leading industry analyst at Forrester, John Bratincevic¹⁰:

“Nobody wants to admit that their own death is coming soon. Low-code has been swinging the pendulum away from off-the-shelf applications and toward custom development for years. There are good reasons for this. When practical, fit-to-purpose software is best. And the lower cost, risk, and lead time of low-code development - coupled with an expanded developer pool, easier integration, management of apps on a common platform, leveraged licensing, etc. - makes it much harder to justify off-the-shelf software licenses and vendor sprawl. AI-powered enterprises will 'build' software instead of 'buy' it — and many applications in enterprise portfolios will consolidate onto low-code AppGen platforms."

Emerging role. Vibe Coder.

For AppGen now read Vibe Coding. For low-code now read the strapline for Vibe Coding: 'No code. just words'. As illustrated above, I see AI-powered CRM apps as replacing Salesforce and other first generation Software-as-a-Service (SaaS) apps.

Vibe Coding for creating CRM and other SaaS apps is an AI-driven, No-Code First approach to software development. This is where users can describe their desired CRM or other SaaS app in plain, natural language prompts or instructions.

In defining Vibe Coding Andrej Karparthy¹ also described this as Software 3.0 as the third era of software as prompts, vibes and conversations. Software 1.o is the first era of hand-written code and Software 2.0 is the second era of data plus machine learning.

From natural language inputs, AI automatically instantly generates a fully functioning SaaS app, complete with frontend, backend and supporting infrastructure, without requiring manual coding or technical expertise.

This process leverages advanced Large Language Models (LLMs) with integrated development tools to translate high-level ideas into executable code. This is shifting the Vibe Coder’s role from traditional programming to guiding and refining AI-generated outputs.

AI-powered Vibe Coding should serve as an augmentation tool for Software Developers rather than as their replacement, but fewer required, nevertheless. The emergence of the Vibe Coder is going to creating a new environment for co-designing apps.

The Software Developer role shifts from pure coder to 'orchestrator, curator and tester', moving beyond writing every function by hand. Part of this new role includes security and quality of what has been generated via Vibe Coding.

Think of digital innovation and software publishing now as more business analysis, less software development. A Vibe Coder is more like a business analyst or subject matter expert, than a tech architect or programmer.

Extend or replace.

With Vibe Coding the extent to which the Vibe Coder can create a fully working app with less input by expert Software Developers (see Pair Programming below) depends on the context and complexity of the app build. Although the long term future of Vibe Coding is mostly a focus on replacing first generation SaaS apps, in the short term, it is about extending existing IT.

For example, an existing Salesforce CRM environment may be where extending this technology to reach more customers, partners, suppliers or employees may be a low risk starting point for Vibe Coding and integration new apps.

A real world example.

Let's explore extend or replace further. In this example we are Vibe Coding a CRM app. This can extend to other apps on a common business logic: Project Management; Talent Management; Professional Services Automation, and so forth. 'CRM Pro' then becomes 'CRM Plus'.

The first step here is engaging in a Mutual Value Discovery to determine where Vibe Coding can generate a next generation SaaS app at a fraction of the cost of existing technologies, yet must be result in a solid user experience and secure, scalable IT. It could be extend or replace.

At Being Guided we are now helping enterprises adopt Vibe Coding for next generation CRM apps, where non-programmers, or Vibe Coders, collaborate with Software Developers under the guidance of an AI Agent. It's a new kind of 'Pair Programming'.

The AI technology includes:

• Database Setup
• AI Large Language Models
• AI Integration
• Design System
• Email System
• Authentication
• Analytics
• Storage

AI-powered Vibe Coding is capable of generating code across the entire software development stack. This starts with prototyping with an inherent ability to quickly translate natural language prompts into fully functional code (Chen et al., 2021³).

Vibe Coded apps generated by AI must meet key questions around potential issues: security vulnerabilities, or performance bottlenecks - all critical in production-class applications (Dahlin, 2021⁴). So our Discovery Engagements at Being Guided are truly minful of these realities.

At Being Guided we are creating this App Framework called 'CRM Pro'. Here we started with a simple Data Model of typical Entities (Objects) you would find in a CRM app: Leads; Contacts; Accounts; and, Opportunities.

Software Engineering. Humans-in-the-loop.

In The AI Con, Emily M. Bender and Alex Hanna offer a sharp critique of the current state of AI, particularly focusing on the hype, misrepresentation, and ethical pitfalls that pervade the field (Bender & Hanna, 2024¹⁶).

One of The AI Con's central arguments is that much of what is marketed as AI is a collection of statistical tricks and pattern-matching systems, often oversold as possessing alleged human-like intelligence. The authors went further to describe the Large Language Models (LLMs) that underly Vibe Coding technologies as 'stochastic parrots'.

The criticisms of AI are a healthy part of understanding what's real and what's hype in all things AI. In our Being Guided four stages of Build illustrated above, you will see that we placed Software Engineering as the fourth stage, after Vibe Coding. In reality, this is more of an iterative process between stage three Vibe Coding and stage four Software Engineering.

With Vibe Coding we are talking about an emphasis of what feels right to a subject matter expert, to produce outputs that match the desired aesthetic or social expectations, rather than being grounded in rigorous engineering or scientific principles.

Therefore, Vibe Coding may be accused of being an approach that often prioritises surface-level impressiveness or alignment with current trends over transparency, reproducibility, or genuine understanding of the underlying systems.

However, as a non-programmer I was a great believer in what Salesforce pioneered twenty years ago, sometimes referred to by IT people as 'declarative programming'. Salesforce was a pioneer in popularising declarative programming for business users, especially in the context of building Software-as-a-Service (SaaS) applications on its cloud platform.

In Salesforce’s terminology, declarative programming refers to the ability to create, configure, and customise applications using visual tools—such as point-and-click interfaces, wizards, and drag-and-drop builders—rather than writing traditional code (Salesforce, 2020¹⁷).

Vibe Coding must preserve the power of declarative programming and provide a balance of both the inherent nature of 'vibe' (what feels right) with being fully grounded in rigorous Software Engineering principles and practices. This leads to the idea of 'humans-in-the-loop' alongside AI, and the concept of Pair Programming expanded upon below.

Nicholas G. Carr’s seminal 2003 Harvard Business Review article, IT Doesn’t Matter argued that information technology (IT) was becoming a commodity—akin to electricity or railroads—rather than a source of sustained competitive advantage (Carr, 2003²⁰).

Carr contended that as IT infrastructure became more standardised, accessible, and affordable, its strategic value diminished. He urged organisations to manage IT as a utility: focus on cost control, risk mitigation, and reliability, rather than seeking differentiation through proprietary IT.

Fast forward from 2003 to today and the rise of Vibe Coding allows business users and 'citizen developers' to create sophisticated applications and workflows without traditional programming skills (Bender & Hanna, 2024¹⁶; Hiraku, 2025²¹).

Production-class apps must always meet stringent requirements for security, scalability, and maintainability. These apps often handle sensitive data, integrate with complex systems, and serve large user bases - all of which demand a level of precision and reliability, including:

• Security Risks: AI-generated code must avoid introducing vulnerabilities, such as SQL injection or cross-site scripting, due to a lack of context (Perry et al., 2022⁷).
• Scalability Challenges: AI tools optimised for performance and anticipating need for horizontal scaling, avoiding bottlenecks as user demand grows (Bass et al., 2019²).
• Business Logic Complexity: AI fully grasping the business rules or compliance requirements, which are often context-specific, require human judgment (Holstein et al., 2019⁵).
• Maintenance and Debugging: AI-generated code must be easy to maintain, including sufficient modularity and docs that human developers prioritise (Lwakatare et al., 2020⁶).
  

Working in pairs.

Our approach to Vibe Coding is Pair Programming: where a non-programmer (known as Vibe Coder) collaborates with one or more Software Developers to co-create a CRM app. Guided by AI, the Vibe Coder contributes domain expertise and high-level requirements, whilst the Software Developer ensures technical rigour.

Pair Programming leverages the strengths of both parties: the Vibe Coder’s understanding of the problem space and the Software Developer’s ability to implement scalable, secure solutions (Holstein et al., 2019⁵).

Over time, the ratio of Vibe Coders to Software Developers will change. The productivity gains from AI-powered Vibe Coding will become more measurable. This will mean more Vibe Coders, less Software Developers.

Vibe Coding tech (so far).

Any post created on the state of play in Vibe Coding technologies is inherently going to look out of date very quickly. As most IT industry people know, the rate of AI innovation and the creation of AI startups is superfast. Today, Vibe Coding has many market entrants.

My own choice of Vibe Coding technology options has been greatly influenced by paying equal attention to culture as to features. With Pair Programming, real world Vibe Coding app innovation always requires 'humans in the loop', (Knight. W. 2025¹²).

At the time of writing (or updating) this Journal post, I have been building CRM Pro as a CRM App Framework with five Vibe Coding technologies: Base44¹³, Cosmic²², Emergent²³, Lovable¹⁴ and Rocket¹⁵. I have provided a screenshots below of my Being Guided Vibe Coding build process with all five of these challengers.

I will be publishing much more about the detail of these Vibe Coding experiences, as I apply them to real world CRM Pro engagements. As you can see in the Base44, Cosmic, Emergent, Lovable and Rocket screenshots below, these tools are remarkably similar in user experience: natural langaguage prompts on the left and app preview on the right.

In this ever-changing landscape, Base44 has been acquired by Wix. This was a remarkable, albeit short life for a startup: acquired for $80million where the founder Maor Shlomo built the business in just 6 months, generating $189k profit in month 6, with 250,000 users¹³.

Over time, distinctive differences between these Vibe Coding technologies, new market entrants and acquisitions will all have a profound impact on this approach to No-Code digitl innovation.

Deep Coding alternatives.

Vibe Coding is still emerging as a class of AI technology. In addition to No-Code tools (Base44, Lovable and Rocket), there are Full-Code technologies such as Claude Code¹⁵ from Anthropic, to accelerate Software Developer productivity. This may be better described as 'Deep Coding'.

In Deep Coding mode, Software Developers can also use technologies such as Cursor, GitHub Copilot, OpenAI Codex and Abacus AI ChatLLM. Over time, we may see convergence between Vibe Coding and Deep Coding technologies.

My conclusion.

Vibe Coding takes advantage of best-in-class Large Language Models (Anthropic Claude Sionnet 4, Google Gemini 2.5 Pro, ChatGPT4, etc.). Vibe Coders can run natural langage prompts across multiple Large Language Models, powering tools, such as Base44, Lovable or Rocket.

Design Thinking⁸ and Value Engineering9 underpin Vibe Coding in our work at Being Guided. Design Thinking maximises stakeholder engagement by generating empathy and trust. Value Engineering builds robust business cases using ROI Models to defend value and quantify costs.

Consider a scenario where a knowledge-intensive services company needs a custom CRM app to manage client portfolios. A Vibe Coder describes the app’s requirements in natural language, and AI generates the code. Then a Software Developer refines the code.

At Being Guided our approach is to use collaborative methods, where Vibe Coders and Software Developers work together, guided by a Large Language Model (LLM) powering the AI options of Lovable or Rocket.

A paired Software Developer then refines this platform code, ensuring it meets best practices, security standards and integrates with existing business logic. It's an iterative, safe journey from first generation CRM, such as Salesforce, to next generation Vibe Coded SaaS apps.

Lets remember the motivations for change: faster, simpler and cheaper.

Faster. Vibe Coding is inherently many times faster in the design, development and delivery phases of Web apps when compared to customising Salesforce or other earlier generation Software-as-a-Service (SaaS) apps. It's days and hours versus months and weeks.

Simpler. At Being Guided we apply Fierce Reduction: the practice of simplifying all business processes, tasks and information systems by removing redundant or non-essential elements before considering Vibe Coding for next generation app development with AI.

Cheaper. With Salesforce Sales Cloud the annual subscription fees for licences is £120 per user per month for the Enterprise Edition. Added to this are professional services fees, often many times the annual subscription fees. With AI-powered CRM Pro apps, tailored to you exact needs, the costs are a fraction of Salesforce licences. The ROI Model is compelling: extend or replace.

Vide Coding screenshots.

Base44. CRM Pro Vibe Coding

Cosmic. CRM Pro Vibe Coding

Emergent Labs. CRM Pro Vibe Coding

Lovable. CRM Pro Vibe Coding.

Rocket. CRM Pro Vibe Coding.

Next?

Let's Meet to explore your Vibe Coding - one hour at a time.

References

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