At Being Guided we help organisations who engage in a high-value, high-touch sell to increase sales effectiveness by combining four things: Design Thinking⁸, Value Engineering⁹, Vibe Coding¹ and AI Sales Coaching²¹.

In this Journal post I am writing about Design Thinking and how this creates a solid foundation for enabling all buyside and sellside stakeholders in digital innovation to embrace Experimentation in creating new digital innovations.

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.

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.

The power of Reflection.

The ability to generate receptivity, rapport, and trust between buyers and sellers is key in the high-value, high-touch sell.. eflective thinking enables sellers to deeply understand buyer needs, align solutions empathetically, and build enduring trust.

Receptivity through Empathetic Understanding
Reflection in Design Thinking begins with the Empathize phase, where sellers pause to deeply understand the buyer’s context, challenges, and aspirations. This reflective pause, rather than rushing to pitch solutions, creates receptivity by demonstrating genuine care for the buyer’s perspective. Reflective thinking allows sellers to ask probing questions, listen actively, and uncover unarticulated needs. For instance, instead of presenting a generic value proposition, a seller might reflect on a buyer’s unique pain Budget, Authority, Need, and Timeline (BANT) to tailor their approach, making the buyer feel seen and understood. This aligns with Brown’s (2008)²³ assertion that empathy in Design Thinking builds deeper connections by prioritising human needs over immediate solutions.

Rapport through Collaborative Ideation
The Ideate and Define stages of Design Thinking rely on reflective synthesis—processing insights to co-create solutions with buyers. In high-touch sales, rapport is built when sellers engage buyers in collaborative problem-solving, reflecting on feedback to refine proposals. This reflective dialogue signals respect for the buyer’s expertise and fosters a sense of partnership. For example, a seller might reflect on a buyer’s feedback about budget constraints and ideate flexible payment structures, strengthening rapport through shared ownership of the solution. Liedtka (2015)²⁴ highlights that collaborative ideation in Design Thinking enhances stakeholder engagement, which is critical for building rapport in complex buying and selling cycles.

Trust through Iterative Prototyping and Testing
Trust in high-value sales hinges on credibility and reliability, which Design Thinking’s Prototype and Test stages reinforce through reflection. Sellers can present lsay, Vive Coded prototypes (e.g., mock-ups or trial plans) and reflect on buyer feedback to iteratively refine solutions. This iterative process demonstrates transparency and a commitment to meeting buyer needs, building trust. For instance, a seller offering a high-value software solution might reflect on a buyer’s concerns about scalability, prototype a Vibe Coded phased implementation plan, and test it with the buyer’s team. This reflective iteration aligns with Kolko’s (2015)²⁵ view that prototyping in Design Thinking builds trust by making solutions tangible and adaptable.

Practice Structured Reflection in the Empathize Phase
Sellers should adopt reflective practices such as journaling or debriefing after buyer interactions to capture insights about emotions, motivations, and pain points. For example, after a Mutual Value Discovery session, a seller might reflect on the buyer’s tone, hesitations, or priorities to refine their understanding. Tools like Empathy Maps can structure this reflection, helping sellers visualize the buyer’s perspective. Schön’s (1983)²⁶ concept of 'reflection-in-action' supports this, emphasising real-time and post-interaction reflection to enhance professional practice.

Create Reflective Dialogue in Ideation
Sellers 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 sellers and buyers brainstorm together, can formalise this reflective dialogue. Beckman and Barry (2007)²⁷ note that such collaborative processes in Design Thinking enhance mutual understanding and commitment.

Leverage Reflective Iteration in Prototyping
Sellers should prototype solutions incrementally (eg. Vibe Coding), reflecting on buyer feedback at each stage. For example, in a high-value sale, a seller might present a draft proposal, reflect on the buyer’s concerns about ROI, and iterate to include a detailed cost-benefit analysis. This reflective iteration demonstrates responsiveness and builds trust. Kolko (2015)²⁵ emphasises that iterative prototyping reduces risk perception, a key factor in high-stakes purchasing decisions.

Cultivate a Reflective Sales Culture
Organisations can embed reflective thinking by training sales teams in Design Thinking principles and encouraging reflective practices like post-meeting debriefs or peer reviews. Leaders can create a culture where pausing to reflect is valued over reactive selling. Liedtka and Ogilvie (2011)²⁸ advocate for organisational cultures that prioritise reflective learning to sustain innovation and customer-centricity.

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 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 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 a CRM 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 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 seller 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 and 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?"

Summary. Design Thinking

At Being Guided we bring four things together in pursuit of improving the high-value, high-touch sell: Design Thinking⁸, Value Engineering⁹, Vibe Coding¹ and AI Sales Coaching²¹. The common thread in all of this is design.

Design Thinking is a great way to engage the broadest, deepest number of stakeholders on bothe the buyside and sellside of any high-value sales motion. Value Engineering ensures that the business case for a Value proposition is fully quantified and justified by the buyside.

In high-value, high-touch sales, the thinking in Design Thinking - rooted in reflective practice - unlocks receptivity, rapport, and trust. By empathizing deeply, co-creating collaboratively, and iterating transparently, sellers can align solutions with buyer needs in a way that feels authentic and trustworthy.

Reflection transforms sales from transactional exchanges into meaningful partnerships, positioning Design Thinking as a powerful framework for modern selling. Organisations that cultivate reflective practices in their sales teams will not only drive revenue but also build lasting relationships that define success in high-stakes markets.

As a design first business, at Being Guided we embrace simplicity as our underlying principle that governs everything we do. You can ready more this design principle in my Journal post Simplify, where Steve Jobs and his work from over forty years ago still resonates²².

References

1. 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
2. Bass, L., Clements, P., & Kazman, R. (2019). Software architecture in practice (4th ed.). Addison-Wesley.
   https://www.oreilly.com/library/view/software-architecture-in/9780136885979/
3. Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. D. O., Kaplan, J., ... & Zaremba, W. (2021). Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374.
   https://arxiv.org/abs/2107.03374
4. Dahlin, M. (2021). The role of AI in software engineering: A review. Journal of Systems and Software, 174, 110887.
   https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3633525
5. Holstein, K., Wortman Vaughan, J., Daumé III, H., Dudík, M., & Wallach, H. (2019). Improving fairness in machine learning systems: What do industry practitioners need? Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-16.
   https://arxiv.org/abs/1812.05239
6. Lwakatare, L. E., Raj, A., Bosch, J., Olsson, H. H., & Crnkovic, I. (2020). A taxonomy of software engineering challenges for machine learning systems: An empirical investigation. Journal of Systems and Software, 162, 110496.
   https://colab.ws/articles/10.1007%2F978-3-030-19034-7_14
7. Perry, D. E., Porter, A. A., & Votta, L. G. (2022). Empirical studies of software engineering: A roadmap. ACM Computing Surveys, 54(3), 1-36.
   https://dl.acm.org/doi/10.1007/s10664-009-9121-0
8. The Hasso Plattner Institute of Design. (2004) Stanford d.school. https://dschool.stanford.edu/about
9. Miles, L.D. (1947). The Lawrence D. Miles Value Engineering Reference Center Collection.
   https://minds.wiscon.edu/handle/1793/301
10. Bratincevic, J. (2024, November 13). AppGen is an existential threat to the enterprise app business. Forrester.
    https://www.forrester.com/blogs/appgen-is-an-existential-threat-to-the-enterprise-app-business/
11. NHS England. (2025, March 27). Financial performance update. https://www.england.nhs.uk/long-read/financial-performance-update-5/
12. Knight, W. (2025, June 25). Vibe coding is coming for engineering jobs. Wired. https://www.wired.com/story/vibe-coding-engineering-apocalypse/
13. Bort, J. (2025, June 18). Six-month-old, solo-owned vibe coder Base44 sells to Wix for $80M cash. TechCrunch.
    https://techcrunch.com/2025/06/18/6-month-old-solo-owned-vibe-coder-base44-sells-to-wix-for-80m-cash/
14. Endo, T. (2025, April 18). Lovable case study: How an AI coding tool reached $17M ARR in 90 days. Medium.
    https://medium.com/@takafumi.endo/lovable-case-study-how-an-ai-coding-tool-reached-17m-arr-in-90-days-f4816e7b3f2b
15. Bhagat, P. K. (2025, June 6). Claude Code, Lovable, Rocket: Vibe Coding. Netizen Page. https://www.netizen.page/2025/06/claude-code-lovable-rocket-vibe-coding.html?m=1
16. Bender, E. M., & Hanna, A. (2024). The AI Con: How Big Tech Hijacked the World, Cheated the Future, and How We Fight Back. W. W. Norton & Company.
    https://thecon.ai/
17. Salesforce. (2020). Declarative tools and programmatic tools on the Salesforce Platform. Salesforce Developers Documentation.
    https://developer.salesforce.com/docs/atlas.en-us.platform_events.meta/platform_events/platform_events_intro_tools.htm
18. Follett, M. P. (1924). Creative Experience. Longmans, Green and Co.
    https://archive.org/details/creativeexperien00foll
19. Graham, P. (Ed.). (1995). Mary Parker Follett. Prophet of Management: A Celebration of Writings from the 1920s. Harvard Business School Press.
    https://www.academia.edu/25438080/Mary_Parker_Follett_Prophet_of_Management_A_Celebration_of_Writings_from_the_1920s
20. Carr, N. G. (2003). IT doesn’t matter. Harvard Business Review, 81*(5), 41–49. https://hbr.org/2003/05/it-doesnt-matter
21. SecondNature. Case studies and resources. Retrieved June 27, 2025.
    https://secondnature.ai/resources/
22. Segall, K. (2010). Insanely Simple. The Obsession That Drives Apple's Success. Penguin Group (USA), Inc.
    https://kensegall.com/books/
23. Brown, T. (2008). Design thinking. Harvard Business Review, 86(6), 84–92.
    https://hbr.org/2008/06/design-thinking
24. Liedtka, J. (2015). Perspective: Linking design thinking with innovation outcomes through cognitive bias reduction. Journal of Product Innovation Management, 32(6), 925–938. https://doi.org/10.1111/jpim.12163
25. Kolko, J. (2015). Design thinking comes of age. Harvard Business Review, 93(9), 66–71.
    https://hbr.org/2015/09/design-thinking-comes-of-age
26. Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
    https://www.academia.edu/36335079/Donald_A_Sch%C3%B6n_The_Reflective_Practitioner_How_Professionals_Think_In_Action_Basic_Books_1984_pdf
27. Beckman, S. L., & Barry, M. (2007). Innovation as a learning process: Embedding design thinking. California Management Review, 50(1), 25–56.
    https://doi.org/10.2307/41166415
28. Liedtka, J., & Ogilvie, T. (2011). Designing for growth: A design thinking toolkit for managers. Columbia University Press.
    https://cup.columbia.edu/book/designing-for-growth/9780231158381/