Having worked in software development and IT for many years, I have seen the tools and application landscape evolve continuously. The era of generative AI does not bring any new challenges or approaches (But indeed at a completely new speed). The main drivers have been and will remain: to produce more in less time with higher quality and lower costs. 

The pyramid of balancing act between quality, time, and cost is a paradigm you couldn’t escape in the past. Will GenAI make it possible, at least in application and software development?

But the main issue I currently experience is that clients and business users don’t see the value for the money. Despite investment in AI-powered low-code platforms, the velocity often falls short. Business users hesitate to build, and when they do, the results are inconsistent.

Why Business Users Are Struggling

Let’s explore how to unlock all the capabilities and value chain of low-code platforms. In the following article, I aim to understand the root cause of the issue of missing outcomes and demonstrate how we at Teiva address these challenges. 

If you’re just interested in the result without reading further:

The root cause is that platforms are deployed as tools. Not as ecosystem of capabilities. There is a lack of contextual AI grounding, reusable patterns, scalable governance, and targeted enablement for citizen developers.

But let’s step back for a while.

We see the business users hesitate or fail to build well. IT provides tooling, runs the readiness assessments, invests into licenses and external consultants. 

When AI Outputs Fail: Lack of Context

And still, business users lack confidence, context, or training. Or all of that. They struggle to prompt effectively, interpret results, or know “what good looks like”. They never designed a business application. So the new innovative tools alone to build low-code / no-code applications aren’t enough.

That’s because the platform provides functional capability, but not domain-aware guidance, templates, or best practices that reduce ambiguity for non-developers. 

This results in AI outputs that are unreliable or generic, because without contextual grounding (such as RAG, prior builds, or enterprise data), AI generates irrelevant or poorly structured solutions.

Governance Gaps That Undermine Delivery

If tools are not enough to achieve specific results, then the governance surrounding them is likely lacking. Governance of training, enablement, release control, and security guidance. IT either locks down access (slowing delivery) or releases control without guidance (risking chaos). 

For the low-code and no-code app development, it means that a citizen developer lacks enablement. It is just ad hoc or absent altogether. 

The organisation (either IT or an innovation office) does not provide a structured onboarding, prompting guidance, or feedback loop. Business users are handed a tool, not a learning path.

At this stage, you are way beyond the typical application development. Analysts call it Application Generation (AppGen) and mean a more dramatic shift in how organizations design, build, and iterate digital solutions. F.e. instead of iterating more or less linear (like you do in waterfall or agile), you are much more iterative and prompt-driven with a speed of hours to days instead of weeks to months. The governance is no longer IT-controlled and needs to be much more scalable and risk-driven.  Also, in any typical application or software development organisation, you have a mindset of project delivery and product ownership. In the context of AI AppGen, your organisation must focus much more on platform curation and enablement of decentralized delivery.

Don’t mix up AppGen paradigm with approaches like Solution Factory and CoEI. A Solution Factory is a structured delivery model or operating framework designed to accelerate the creation, reuse, and scaling of digital solutions (typically on a low-code platform like ServiceNow). The COEI is a governance and enablement construct. 

AppGen goes beyond

It’s a next-generation development paradigm where AI, low-code, and platform integration enable business users to dynamically generate applications, rather than manually building them.

There is a very insightful and valuable webcast from ServiceNow, hosted by Jithin with John Bratincevic as a Guest.

AppGen introduces:

• AI-powered generation of apps based on prompts or context
• End-to-end automation across the SDLC
• Democratized access for citizen developers
• Platform-level orchestration (not just solution delivery)

To summarize, AppGen is faster, more inclusive, and more scalable. It changes the economics of software delivery. But success depends on mindset, governance, and enablement, not just tools and methodology.

And with a new mindset, it gets more demanding. 

The following table provides an overview of challenges and their implications:

Challenge	Insight	Strategic Implication
Citizen developers don’t build reliably or at scale.	Feedback loop is broken: output quality leads to user disengagement → less experimentation → low value delivery.	Boost AppGen quality and guidance to trigger a positive feedback loop.
There is a usability gap. Tools are hard to use and deliver poor results.	System lacks “efficiently interpretable” design feedback. AI-generated outputs are not immediately understandable or modifiable.	Introduce AI scaffolding, preview layers, and templated conversational UI for iteration.
Lack of context and domain-specific models and patterns.	Absence of contextual grounding (e.g. past builds, metadata, enterprise ontologies) → poor AI performance.	Implement contextual AI (RAG) and build verticalized design accelerators.
No Enablement, no adoption. Focus was on platform go-live, not enablement or patterns.	System imbalance: strong technical core, weak social/organizational infrastructure.	Redesign rollout as a capability build—platform + practice + culture.
Project was treated as a tool delivery, not a strategic transformation.	Misaligned mental models: AppGen is a new socio-technical system, not a tech refresh.	Shift from project mindset to platform operating model: IT as enabler, not gatekeeper.

You need to rethink your approach and redesign your governance completely; otherwise, application development will be a matter of luck. And not predictable results.

How to redesign your application development

I trully believe, that the future of application delivery lies in a collaborative, self-reinforcing process that empowers business experts to create and iterate applications directly. I see it a guided system supported by intelligent platforms, domain-relevant templates, and contextual AI.

The target flow or the process you might want to establish:

This approach creates a self-reinforcing loop:

This creates a positive feedback loop where better results lead to higher trust, increased adoption, and greater reuse – making every build smarter than the last. It shifts development from a bottlenecked IT function to a decentralized innovation engine, while IT evolves into a strategic enabler and curator of quality and security.

AppGen Principles

There are five core principles you must following during the journey:

• Bespoke is Best

  Prioritize domain-specific builds over generic templates. AI thrives with context.

• Governance Must Scale Innovation, Not Block It

  Use business impact as the gating factor, not role/title.

• Prompting is a Skill, Not a Hack

  Train citizen developers in structured prompting & app design thinking.

• AppGen Is a Capability, Not a Feature

  Treat it like DevOps or Agile—organize around it, measure it, improve it.

• Measure Feedback Loops, Not Just Output Volume

  Success = engagement depth, iteration velocity, time-to-value.

This is not just a technology adoption. It’s an organizational capability shift. Enterprises that succeed in Application Generation will be those that build the systems, training, and governance structures to empower domain experts, reinforce good practices, and continuously improve. It’s how you go from experimenting with AI to transforming your entire approach to building business software.

So, how do you make this shift real in your organization, without compromising quality, security, or control?

Let me show you how we can help you address these challenges and unlock the full potential of application generation in your enterprise.

How Teiva Systems helps you addressing the challenges?

Teiva Systems helps enterprises not just implement low-code and AI, but operationalise Application Generation (AppGen) as a strategic capability. We understand that success in this space depends on more than having the right tools – it requires the right structure, enablement, and mindset.

Our approach is pragmatic and outcome-driven. We begin with a hands-on AppGen Assessment to identify areas of friction across your platform, processes, and citizen developer ecosystem. From there, we draw on our internal IP (such as AI-augmented Solution Factory Blueprints) to accelerate delivery of high-impact use cases with consistency and reuse.

We also help your teams scale sustainably. Through thought leadership and executive advisory, we equip you with strategic narratives to align stakeholders. And with our AppGen Specialist enablement program, we build internal champions skilled in low-code, AI orchestration, and platform strategy – ensuring your teams can scale innovation confidently and independently.

Client Engagement

Our IP

Enablement

We offer an “AppGen Assessment” to identify friction points in their platform, context, and citizen developer flow.

This is not a generic platform health check—it’s a focused evaluation of the value chain required to make AppGen work at scale:

• We assess how your low-code and AI capabilities are currently used, including telemetry, usage patterns, and governance constraints.
• We identify points of hesitation and failure—e.g., where business users drop off, where AI generation quality declines, or where process bottlenecks persist.
• We analyze developer (pro and citizen) workflows to ensure the platform experience is aligned with skill level and business objectives.
• We benchmark your organization against AppGen maturity dimensions: platform curation, domain reuse, governance, AI grounding, and enablement.

ATo enable rapid, consistent, and context-aware delivery, we’ve developed a library of proprietary IP assets that act as the scaffolding for Application Generation. These assets help clients avoid building from scratch, improve AI output reliability, and reduce delivery cycles from weeks to days.

• Predefined patterns for common business scenarios (e.g., onboarding workflows, service request flows, risk capture modules) enhanced with GenAI prompts and flow logic.
• Verticalized data models tailored for HR, ITSM, CSM, and operations, with reusable connectors and policies.
• Prebuilt rulebooks, access-tier models, and compliance guardrails aligned with business risk thresholds.
• Domain-specific prompt sets and examples to guide business users in generating quality outcomes from GenAI features.

• Modular review/feedback experiences to close the quality loop during AppGen cycles.

Launch an internal enablement track for AppGen Specialists: low-code fluency + GenAI best practices + platform strategy.

We invest deeply in client enablement to ensure that AppGen becomes a sustainable capability embedded in your workforce and culture.

Our enablement offering includes:

• AppGen Specialist Enablement Track
• Executive Advisory & Change Management
• Embedded Coaching & Design Sprints

Launch an internal enablement track for AppGen Specialists: low-code fluency + GenAI best practices + platform strategy.

So yes, GenAI can bend the rules of the triangle “Quality – Time – Cost”. But only if you change how you build the system that builds the software. GenAI will not fully erase the triangle, but it reshapes the dynamics.

Teiva’s mission is to help you realize the full potential of AI and low-code – not just by implementing a platform, but by establishing an ongoing, scalable system of innovation. By aligning technical capabilities with human enablement, governance, and reusable knowledge assets, we turn Application Generation from a promising concept into a practical, repeatable engine of transformation.

It’s not about building faster. It’s about building smarter, safer, and at scale.
With Teiva Systems, you move from tools to transformation.

From outputs to outcomes.

From experiments to enterprise-grade capability.

Ready to empower your organization to build what it needs – when it needs it?

Let’s make it real.

Kostya Bazanov, Managing Director, Jun 23, 2025

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