Adaptive Software for Rapid Change

The New Global Dynamic

Recent global disruptions - Brexit, the COVID-19 pandemic, and new tariffs - have made one thing clear: external shocks strike fast and with little warning. These events originate beyond a company’s control, yet they demand immediate and strategic internal responses.

Flexibility is no longer a competitive advantage. It’s mandatory.

This principle isn't new. As far back as the late 1950s, organizational theorists Tom Burns and G.M. Stalker distinguished between two models: mechanistic organizations, optimized for stability and control, and organic organizations, designed for flexibility and responsiveness.

In stable environments, mechanistic structures perform well. Centralized decision-making, standardized policies, and predictable processes create efficiency.
But in dynamic conditions - characterized by rapid change and uncertainty - such rigidity becomes a liability. It delays responses, limits adaptability, and can ultimately threaten the survival of the business.

The Rigidity of Traditional Software

Traditional enterprise software deployment suffers from this problem of rigidity.

While the legacy systems excel in environments that demand consistency, they often struggle in today’s unpredictable, fast-paced business conditions.

And designed for stability, they tend to be expensive and challenging to adapt.

This challenge arises from a fundamental mismatch between the nature of software and the realities of business.

• Business reality is fluid, messy, and unpredictable
• Software requires precision, structure, and logic

Bridging this gap requires translation – a process often mediated by consultants, long implementation cycles, and extensive coordination.

Reality needs to be defined into business requirements which need to be translated into technical specifications. At the same time, all of these specifications must align with existing systems, workflows, and constraints.

This adds complexity. The result is a fragile process with countless dependencies. It's slow by design, costly to conduct, and uncertain in terms of ROI.

Knowledge Workers as the Glue

But when disruption hits, businesses must respond immediately.
There’s no time for traditional software development cycles that stretch across 6 to 12 months.

Even worse, by the time a solution ships, the conditions it was designed for may no longer exist.

Take international tariffs, for example. By the time a solution is scoped, developed, and deployed, the business environment has already shifted. The window for impact is gone. This is why teams often don’t even attempt to adapt their systems. They know the effort won’t pay off in time.

As a result, operations teams are forced to rely on people – knowledge workers – as the only viable response mechanism.

They step in to bridge the gaps using Email threads, Ticketing systems, spreadsheets, manual workflows and static manual documentation.

They act as improvised infrastructure, keeping operations running despite systemic misalignment. In practice, they serve as the "duct tape" holding fragmented processes together.

It’s especially visible in large, high-stakes shifts, but it’s just as present in the day-to-day. After go-live, a constant stream of small, evolving needs emerge – pricing tweaks, process exceptions, customer-specific adaptations. Traditional software ignores these. They’re too fluid, too uncertain and too small to justify a formal build.

The result: knowledge workers end up managing a big part of operational complexity and documentation manually. No interfaces. No tooling. No leverage.

The Shift: Language-Based Programming Empowers the Knowledge Worker

This is exactly where software that adequately leverages the potential of artificial intelligence comes in.

It introduces a powerful new way to adapt “software”.

Knowledge workers can now make changes themselves by giving direct instructions in natural language.
After all, while we have about 30 million software engineers on the planet, we have 8 billion “language speakers”.

With that they cover a big part of what’s needed to adapt to sudden changes. With 5% of the work they can often achieve >50% of the solution - fast.

What this looks like in practice:

• Finance: "Modify existing forecasting templates to automatically reflect a 15% cost increase in aluminum imports, highlighting impacts across product lines."
• Supply Chain: "Integrate dynamic recalculations of shipping routes in response to newly announced U.S. tariffs, automatically updating ERP delivery schedules."
• Compliance: "Automatically flag affected HS codes in the product catalog based on recent U.S. tariff changes and generate compliance summary reports."
• Procurement: "Enhance supplier database queries to rapidly identify and rank alternative suppliers to Chinese steel, meeting specific specs and lead times under four weeks."
• Sales: "Implement customizable email templates within CRM that automatically adjust pricing communications based on region-specific tariff impacts."
• Operations: "Automatically cross-reference Bill of Materials (BOMs) to identify tariff-affected components and propose pre-approved alternative materials."

By empowering operational teams to directly manage the dynamic complexities of daily operations, businesses reduce the reliance on consultants, product managers, and engineers for routine optimizations. This ensures issues are addressed precisely where expertise is highest, as operational teams inherently understand edge cases best. The result is not only improved solution quality but also significantly shorter iteration cycles.

Organizations can therefore respond effectively within hours, empowering operational teams to manage real-world dynamics with genuinely real-time tools.

This shift goes beyond mere speed; it fundamentally enhances business resilience and responsiveness, enabling teams to be supported directly and adequately by their software.

Simultaneously, product and IT teams are freed to focus on building robust foundational platforms, comprehensive integrations, and scalable automation workflows. They spend less time managing multiple custom implementations, thus reducing backlog accumulation and enhancing overall efficiency.

Why This Needs a Horizontal Platform

To support this shift, it takes a horizontal platform – one that works across departments and functions.

This is where traditional software often cannot support. Most tools are built for vertical, high-volume processes: invoicing, payroll, logistics. They work well for standardized, repeatable tasks that do not change a lot. And that’s fine – for those processes, they’ll continue to work and with AI agents built on top of these systems some of the additional edge-cases can be captured.

But the opportunity to reach a new level of efficiency now lies in the remaining 70% of operational work – where change is constant, and where software has so far failed to reach. This segment represents the hidden long-tail of tasks that are typically costly, manual, and unelastic. These include:

• Escalations across all departments and various scenarios
• Service management, internal onboarding processes, and help-desk activities
• Cross-departmental workflows that require seamless coordination
• Small-scale, high-value situations with significant impact, such as audit escalations
• One-off or unique situations that do not justify custom-built solutions

These areas are precisely where knowledge workers currently step in to fill gaps. Interloom is specifically designed to support these critical, yet underserved operational tasks, enabling businesses to effectively handle complexity and variability.

It empowers operational teams to act swiftly without direct reliance on central IT.

But it does this within a controlled, structured environment. It is not enabling thousands of employees to build core infrastructure. That remains the job of the IT department.

Instead, Interloom provides a dedicated layer for knowledge workers and expert operational teams – a safe, abstracted workspace that supports them.

By managing agents through natural language alone, Interloom unlocks the potential for millions of specialists to independently resolve issues, significantly enhancing organizational agility.