Innovate is the coming together of five things that drive the building of your native Salesforce apps: Design Thinking; Value Engineering; Reflection; Experimentation; and, Vibe Coding.

Design Thinking.

Design Thinking¹ maximises stakeholder engagement by generating empathy and collaboration across the buying and selling cycle, whilst Value Engineering² builds robust business cases using ROI models to quantify and justify costs.

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 making it happen. The final stage involves finalising the solution design based on feedback, completing the development, and launching the innovation process. This ensures that the solution is fully understood and ready for everyday use.

Value Engineering.

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

Value Engineering was originally conceived by Lawrence D. Miles², 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 innovation in a timely manner. It is quantifying time-based value versus the cost of delay or doing nothing.

As Value Engineer, I set the scene mapping your investor's, buyer's or sponsor's needs with your offering. This is where we apply Design Thinking to enable you to build receptivity, rapport, trust and truth generated with investors, buyers or other sponsors - early and often.

From a financial perspective, I start with a simple question for the investor, buyer or sponsor:

What is the cost of NOT investing in the proposed innovation?

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, I 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

Reflection.

The ability to generate Receptivity, Rapport, Trust and Truth between all stakeholders in the process of simplifying business or tech is key. Reflection enables all stakeholders in Salesforce innovation to align with solutions empathetically. It's everyone³.

In The Creative Act: A Way of Being Rick Rubin⁴ expands on his philosophy on creativity as a fundamental aspect of human existence rather than a skill reserved for artists. Rubin says "Look for what you notice but no one else sees". Often this is likely the person closest to a process or task but who is invariably not the closest to the design and development of a related digitisation.

In my own work with digital innovation I see the big problem of bed-blocking in UK NHS hospitals as being best understood by discharge nurses and patients - not the executives or IT people. This was how I created the Social Care Cloud to solve this problem - it was the discharge nurses who understood the problem - and who were most motivated to solve it.

Receptivity through Empathy.
Reflection in Design Thinking begins with the Empathize phase, where stakeholders will pause to deeply understand the context, challenges, and aspirations of the problem(s) being addressed. This reflective pause, rather than rushing to pitch solutions, creates receptivity by demonstrating genuine care for each stakeholder's perspective. Reflective thinking allows probing questions, active listening, and uncovering unarticulated needs. For instance, instead of presenting a generic value proposition, a stakeholder might reflect on an unique pain or problem.

Rapport through Collaborative Ideation.
The Ideate and Define stages of Design Thinking rely on reflective synthesis—processing insights to co-create solutions with all stakeholders. This is engaging in collaborative problem-solving, reflecting on feedback to refine proposals. A reflective dialogue signals respect for each of your stakeholder's expertise and generates a sense of partnership.

Trust through Iterative Stages..
Trust in new digital innovations depends on credibility and reliability, which the Design Thinking Prototype and Test stages reinforce through reflection. Stakeholders can present say, Vibe Coded prototypes and reflect on buyer feedback to iteratively refine solutions. This iterative process demonstrates transparency and a commitment to meeting stakeholders needs.

Practice Structured Reflection.
Stakeholders should adopt reflective practices such as journaling or debriefing after interactions to capture insights about emotions, motivations, and pain points. For example, after a Mutual Value Discovery session, a stakeholder might reflect on the tone, hesitations, or priorities of other stakeholders, to refine their understanding. Tools like Empathy Maps can structure this reflection, helping stakeholder visualise their collective, broader perspectives.

Create Reflective Dialogue.
Stakeholders can use reflective questioning techniques, such as “What if we explored this option?” or “How does this align with your goals?” to engage buyers in co-creation. This requires pausing to reflect on buyer responses rather than pushing predefined solutions. Mutual Value Discovery Workshops or collaborative sessions, where say, sellers and buyers brainstorm together, can formalise this reflective dialogue.

Leverage Reflective Iteration.
You should prototype solutions incrementally, reflecting on buyer feedback at each stage. For example, in a high-value sale, a seller might present a draft proposal, reflect on any stakeholder's concerns about ROI, and iterate to include a detailed cost-benefit analysis. This reflective iteration demonstrates responsiveness and builds trust.

Cultivate a Reflective Culture.
Organisations can embed reflection by applying Design Thinking principles. This encourages reflective practices like post-meeting debriefs or peer reviews. Leaders can create a culture where pausing to reflect is valued over reactive actions.

Experimentation.

Consistent with the Design Thinking inspired by Stanford d.school I believe that it is vital that business and technical stakeholders fully embrace Experimentation⁵ as a state of mind that governs the innovation journey.

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

Framing the Testable Idea.
Defining Evidence.
Selecting The Test.
Building the Prototype.
Executing, Analysing, Testing.

With this approach to Experimentation, underpinned by Design Thinking and Value Engineering, a process that is incorporated in my work in creating AI-powered SaaS solutions:

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 offer, creating a solid business case for investors, buyers or sponsors. 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 to generate a strong business case for engaging in digital innovation.

Tasks.
Project Tasks may be 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 - all capturing in a tailored SaaS app.

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 layouts for Skills for eLearning and Certifications - also created in a tailored SaaS app.

Storyboards.
Alongside Snapshots, Storyboards are continuously updated via a Web Form and SaaS 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 investor, buyer or sponsor agrees and continuously refines 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 all stakeholders. This is where progressively clearer Solutions are developed and documented. This is 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 digital innovation. 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 and actual objerction handling situations. Example: "The buyer 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 all stakeholders.

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?"

Vibe Coding.

Vibe Coding was a terms first used by Andrej Karpathy to describe a radical departure from traditional software development methodologies. At its core, Vibe coding embodies a philosophy described as "fully give in to the vibes, embrace exponentials, and forget that code even exists" (Karpathy, 2025)⁶.

Vibe Coding generates mixed media reactions. Some technologists are concerned about the idea of amateurs creating Software-as-a-Service (SaaS) apps that will be inherently unstable and insecure. There is much truth in this concern, but the underlying sentiment about Vibe Coding is meaningful in the quest for simplifying digital innovation.

The idea that non-programmers can create SaaS apps, that was pioneered by Salesforce twenty years ago, is powerful. Salesforce is still the leader in enabling a 'No-Code First' approach to digital innovation. Building SaaS apps on a scalable secure technology like Salesforce is viable.

Expecting the Vibe Coding startups like Base44, Bolt, Lovable, Replit and Rocket to be safe and secure is wildly optimistic and, in my own hands-on evaluations, lacks the reliability of Salesforce. However, given the significant amount of venture capital poured into these startups, one or two of these raw startups might become credible in the future.

I see Vibe Coding as a set of new but reliable technologies that can accelerate the design and development of SaaS apps built on Salesfor^ce7 I use the visual No-Code First approach to Salesforce innovation, creating apps fast at lower cost with clicks, not code.

For complex innovations, there will always be the need for solid software engineering and the 'Low-Code' and 'Full-Code' capabilities of Salesforce Developers. Ultimately, it is a question of blending No-Code, Low-Code and Full-Code in an optimal way. This may be akin to the idea of Pair Programming⁹: combining No-Code Designers with Low-Code/Full-Code Developers.

Mob Programming

For Salesforce, Agentforce for Developers is a growing platform and 'movement' of 'AI-Native Engineers'⁹. This includes concepts that focus on how to increase the productivity of Software Developers, including the idea of 'Mob Programming', borne out of Pair Programming.

As Shruti Hardas⁹ reports in relation to Salesforce internal operations, acting as 'customer zero': "Intelligent automation tools have revolutionized this process. New hires can now quickly synthesize multiple design documents, grasp coding practices, and familiarize themselves with complex codebases within hours, rather than the weeks or months previously needed."

To quote author James Simone¹⁰: "Mob Programming is a collective programming discipline that fosters greater interaction with teammates, collective code ownership, and a sharp reduction in knowledge siloing. It can help a growing team to onboard new members and enables stable teams to produce quality work consistently without having to worry about scheduling."

Instead of focusing on specialisation, and parallel streams of work, Mob Programming empowers the team to work through each challenge together. Knowledge is shared broadly, as are the pitfalls associated with failed approaches. Work collapses into a single stream.

From https://devopedia.org/shift-left

As illustrated above, Mob Programming also embraces 'Shift-Left Testing'¹¹, which simply means performing testing earlier in the software development cycle. It also means working and solving problems as a team - and to stop burdening individuals in isolating silos.

Abacus.ai DeepAgent.

For Vibe Coding on Salesforce Lightning Platform Abacus.ai¹² DeepAgent provides:

Conversational Code Generation. Users describe what they want in plain English, and DeepAgent generates Salesforce code (Apex, LWC, Flows) or Monday.com configuration steps.

Real-Time Collaboration. Multiple users can interact with DeepAgent, review code, and iterate on solutions together.

Context Awareness.
DeepAgent understands Salesforce metadata (Objects, Fields, Relationships) and tailors its responses to your Salesforce Org Data Schema. DeepAgent also engages fully with other apps apps using Model Context Protocol (MCP) Integration¹³.

This Journal post presents a comprehensive framework for digital innovation that clearly positions Innovate as an integration five interconnected elements that work together to drive meaningful digital transformation with Salesforce.

Design Thinking.
Stanford d.school Design Thinking serves as the foundational methodology, adapted from this six-stage iterative process (Empathize, Define, Ideate, Prototype, Test, Implement). As a human-centered approach maximizes stakeholder engagement by generating sufficient empathy and collaboration throughout the innovation cycle. This ensures that solutions address real user needs rather than assumed requirements. The emphasis on the Empathize stage as the most critical component underscores the importance of building receptivity, rapport, and trust among all stakeholders before proposing solutions.

Value Engineering.
You strengthen the Design Thinking approach by providing robust financial justification through sophisticated ROI models. The method goes beyond traditional cost-benefit analysis by asking the fundamental question: "What is the cost of NOT investing in the proposed innovation?" This approach quantifies the cost of delay and inaction, creating compelling business cases that defend value over price and enables informed investment decisions.

Reflection.
As a critical practice, Reflection enables stakeholders to generate genuine Receptivity, Rapport, Trust and Truth throughout the innovation process. This approach emphasises that those closest to business processes often possess the most valuable insight stakeholder relationships through structured practices, collaborative dialogue, and iterative refinement.

Experimentation.
As an operational framework for testing and validating innovations, Experimentation takes you through a five-step process: Framing the Testable Idea; Defining Evidence; Selecting The Test; Building the Prototype; and Executing, Analysing, Testing. This systematic approach translates Design Thinking insights and Value Engineering models into practical Salesforce solutions with clearly defined components that includes Models, Projects, Tasks, Resources, Storyboards, Decisions, Solutions, Checklists, Objections, Calculations, and Guidance.

Vibe Coding.
The latest tech enabler that accelerates software building is Vibe Coding. This demonstrates how tools like Abacus.ai DeepAgent¹² and Agentforce Vive Codey⁹ can implement a safe, No-Code First strategy that enables rapid prototyping while maintaining human oversight. This approach democratizes SaaS application development by allowing Citizen Developers to create functional Salesforce solutions through conversational interfaces, yet build on a scalable, secure platform.

Summary.

This Journal post is all about Salesfoce innovation, adopting a No-Code First approach to building Software-as-a-Service (SaaS) apps and combining Design Thinking, Value Engineering, Reflection, Experimentation and Vibe Coding to deliver success.

References

1. The Hasso Plattner Institute of Design. (2004) Stanford d.school. https://dschool.stanford.edu/about
2. Miles, L.D. (1947). The Lawrence D. Miles Value Engineering Reference Center Collection.
   https://minds.wiscon.edu/handle/1793/301
3. Kelley, T., & Kelley, D. (2013). Creative confidence: Unleashing the creative potential within us all. Crown Business.
   https://ssir.org/books/excerpts/entry/creative_confidence_unleashing_the_creative_potential_within_us_all
4. Rubin, R. (2023). The Creative Act: A way of being. Penguin Press.
   https://canongate.co.uk/books/4336-the-creative-act-a-way-of-being/
5. Liedtka, J., Chen, E., Foley, N., & Kester, D. (2021). The Experimentation Field Book: A Step-by-Step Project Guide. Columbia Business School Publishing.https://cup.columbia.edu/book/the-experimentation-field-book/9780231214179/
6. Karpathy, A. [@karpathy]. (2025, February 2). There’s a new kind of coding I call “vibe coding”, where you fully give in to vibes, embrace exponentials, and forget that code even exists. X. https://x.com/karpathy/status/1753472166197080428
7. Stutz, A., & Kolb, R. (2021). *Salesforce Lightning Platform Enterprise Architecture* (3rd ed.). Packt Publishing.
   [https://github.com/PacktPublishing/Salesforce-Lightning-Platform-Enterprise-Architecture-Third-Edition](https://github.com/PacktPublishing/Salesforce-Lightning-Platform-Enterprise-Architecture-Third-Edition)
8. Williams, L., & Kessler, R. (2003). Pair programming illuminated. Addison‑Wesley. https://books.google.com/books/about/Pair_Programming_Illuminated.html?id=LRQhdlrKNE8C
9. Hardas, S. (​2​025, August 25). The AI‑native engineer: How Salesforce’s next generation is redefining software development. Salesforce Engineering Blog. https://engineering.salesforce.com/the-ai-native-engineer-how-salesforces-next-generation-is-redefining-software-development/
10. Simone, J. (​2​025, January 18). An ​Intro to ​Mob ​Programming. Salesforce Engineering Blog. https://engineering.salesforce.com/an-intro-to-mob-programming-1a95da040b8b/
11. Donald Firesmith (2015, 23 March 23). Four Types of Shift Left Testing. Archived from the original on 2015-09-05. Retrieved 27 March 2015.
    https://web.archive.org/web/20150905082941/https://insights.sei.cmu.edu/sei_blog/2015/03/four-types-of-shift-left-testing.html
12. Abacus.ai. (2025). Abacus AI platform overview.
    https://abacus.ai/platform
13. Anthropic. (2024, November 25). Introducing the Model Context Protocol. Anthropic. https://www.anthropic.com/news/model-context-protocol