Rajesh Jain

Foundations – 2

Progency

Progency—a fusion of product, AI agents, and agency—solves the critical “Who Will Do It?” problem that has limited martech’s impact. Unlike traditional agencies using third-party tools or martech vendors providing just software, Progency combines proprietary platform capabilities with specialist expertise and AI orchestration in a performance-based model. Through the PEAK framework (Platform, Experts, AI agents, Kaizen), Progency takes end-to-end responsibility for driving measurable business outcomes. Most revolutionary is its economic model: eliminating platform fees in favour of revenue-sharing tied directly to measurable results. This creates perfect alignment between vendor and client—Progency succeeds only when brands succeed. By focusing specifically on maximising value from “Rest” customers, Progency enables marketing teams to concentrate on their Best and Next customers while systematically reducing expensive reacquisition through deeper, more relevant engagement.

NeoMails

NeoMails transforms traditional static emails into interactive, app-like experiences that command attention and drive action. Through interactive technologies like AMP and CSS, NeoMails incorporates three revolutionary elements: Atomic Rewards (Mu) that gamify opens through micro-incentives; Microns that deliver 15-60 second “brain gain” experiences; and ActionAds that enable complete transactions directly within the email itself. This approach eliminates the “click-through penalty” that typically loses 80-90% of potential conversions when customers must navigate to external sites. By establishing reliable daily “hotlines” between brands and customers, NeoMails solves the “No Hotline” problem at the root of attention recession. The impact is transformative: increasing engagement rates by 4-10X while simultaneously creating new revenue opportunities through monetised attention. For brands, NeoMails represents the critical bridge that prevents Rest customers from sliding into expensive dormancy.

NeoN

NeoN reimagines advertising through authenticated identity, creating a direct marketplace that connects brands without expensive intermediaries. Unlike cookie-based targeting, NeoN leverages first-party data with deterministic, precise matching to enable brand-to-brand collaboration. Through this approach, one brand’s inactive “Test” customers can be precisely targeted through another brand’s engaged “Best” customer channels. Interactive ActionAds within partner emails enable complete transactions without leaving the inbox, dramatically increasing conversion rates. This creates a powerful dual advantage: publishers “print money” by monetising their engaged audience while advertisers “save money” through dramatically more efficient customer acquisition—cutting costs by 30-50% compared to traditional platforms. As third-party cookies disappear, NeoN’s authenticated approach represents not just another advertising channel but a fundamental reimagining of how brands reach both dormant customers and new prospects.

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To deliver on NeoMarketing’s twin promise—maximising LTV while minimising CAC—a dual-track approach becomes essential: Progency transforms Rest customers into Best through AI-powered personalisation, while NeoN slashes reacquisition costs through precision targeting and frictionless conversions.

Foundations – 1

I asked Claude to provide summaries of the six foundational ideas.

NeoMarketing

NeoMarketing represents marketing’s third great era, following Traditional Marketing (1950s-1990s) and Modern Marketing (2000s-2020s). This paradigm shift fundamentally inverts established priorities: retention before acquisition, relationships before transactions, and individuals before segments. Unlike current approaches where 70% of budgets fund wasteful reacquisition, NeoMarketing systematically eliminates AdWaste while maximising customer lifetime value. It solves the twin failures of modern marketing: the “Not for Me” problem through true 1:1 personalisation, and the “No Hotline” problem through reliable daily engagement channels. By transforming marketing from a cost centre into a profit engine, NeoMarketing delivers three revolutionary outcomes: eliminating AdWaste by solving attention recession at its source, re-engineering retention through AI-powered personalisation, and creating a flywheel for profitable growth that drives sustainable business success.

Best-Rest-Test-Next Segmentation

The BRTN framework revolutionises segmentation by categorising customers based on engagement patterns rather than demographics or psychographics. Best customers (top 20%) typically generate 60-80% of revenue and 200% of profits, warranting extreme retention with Velvet Rope Marketing’s hyper-personalised experiences. Rest customers (middle 40-50%) show declining engagement within the past 30-90 days and represent marketing’s greatest untapped opportunity—requiring immediate intervention before slipping into dormancy. Test customers (dormant 30-40%) have gone inactive for 90+ days, driving the AdWaste crisis as brands repeatedly pay to retarget them through expensive platforms. Next customers are genuinely new acquisitions who require thoughtful welcome experiences. This engagement-based approach creates a clear operational framework for allocating resources where they deliver maximum impact, systematically converting Rest customers to Best status while reducing expensive Test customer reacquisition.

AI Agents and Twins

AI Agents and Twins represent a quantum leap beyond traditional marketing automation. AI Agents function as autonomous specialists handling complex marketing tasks at scale—from audience segmentation and content creation to journey orchestration and performance analysis—all coordinated by an AI Co-Marketer that ensures alignment with brand guidelines and business objectives. Meanwhile, AI Twins create digital replicas of customers that continuously learn from every interaction, building increasingly accurate models of individual preferences and behaviours. This agent-twin ecosystem enables a “Department of One for a Segment of One”—where small marketing teams can deliver truly individualised experiences to millions of customers simultaneously. Unlike rules-based systems, these agents autonomously identify opportunities, execute complex workflows, and continuously self-improve, transforming marketing from manual orchestration to intelligent automation.

The Idea

Marketing stands at a crossroads, facing unprecedented challenges and opportunities in the AI era. As Google’s AI Overviews and AI answer engines like ChatGPT and Perplexity disrupt organic search traffic, and competitive pressures demand ever-accelerating growth, brands find themselves trapped in an increasingly expensive cycle. This perfect storm is forcing marketers to pour more resources into reacquisition—repeatedly paying premium prices to reach customers they already know—while traditional engagement channels continue to deteriorate.

I’ve written extensively about the profound inefficiencies plaguing modern marketing—what I call the “$500 billion AdWaste crisis.” This staggering figure represents the 70% of digital marketing budgets that brands squander on repeatedly reacquiring customers they already know through expensive adtech platforms.

The AdWaste crisis stems from two fundamental marketing failures: the “Not for Me” problem (generic messaging that fails to resonate with individual preferences) and the “No Hotline” problem (the absence of reliable engagement channels). These failures lead to attention recession, where customers mentally unsubscribe long before formally opting out, forcing brands into expensive reacquisition cycles.

During a recent meeting with an eCommerce client, this reality came into sharp focus. Despite building a successful business with $6 million in annual revenue, he struggled with balancing growth and profitability. His monthly acquisition spending through adtech platforms was $50,000—a stark contrast to the mere $2,000 he spent on martech solutions for retention.

When I pointed out this imbalance, his response captured the fundamental challenge facing marketers today: “Acquisition is easy—I just call up an agency, give them a budget, and they deliver the clicks. ABC. Agency, Budget, Clicks. Retention is tough. Martech platforms are complex. I know my team doesn’t make full use of your platform. I know we need better segmentation, sharper content, more targeted campaigns. But all that is hard work. Can you make martech as easy as adtech? And also provide agency support so you price on outcomes rather than inputs. Become a partner, not a vendor.”

This conversation crystallised the core ideas I’ve been exploring: NeoMarketing, the BRTN (Best-Rest-Test-Next) framework, AI Marketing Agents and Twins, Progency, NeoN, and NeoMails. These concepts represent a fundamental reimagining of marketing for the AI era—one that addresses the AdWaste problem while maximising Customer Lifetime Value (LTV) and minimising Customer Acquisition Cost (CAC) to deliver “Rule of 40” profitable growth.

As I reflected on this and other conversations during my flight back to Mumbai, I realised I needed a simple slogan to capture the essence of NeoMarketing: “Double the Best, Halve the Waste.” This encapsulates the dual mission of NeoMarketing—doubling the Best customer base (those top 20% who deliver 60-80% of revenue and 200% of profits) while cutting AdWaste (primarily spent on reacquisition) by 50%.

In this series, I’ll explore how breakthroughs like Progency (combining Platform, Experts, AI Agents, and Kaizen-driven continuous improvement) and NeoN (an alternate ad network based on authenticated identity) can transform marketing from a cost centre into a profit engine. I’ll demonstrate how these innovations enable brands to establish reliable hotlines with customers, deliver true N=1 personalisation at scale, and eliminate the wasteful reacquisition cycle that drains marketing budgets and stunts profitability.

Together, we’ll discover how to make NeoMarketing’s “Double the Best, Halve the Waste” vision a reality for businesses.

Published May 20, 2025

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Past, Present, Future

The $500 billion annual AdWaste crisis—where 70% of marketing budgets evaporate reacquiring customers brands already know—has become marketing’s accepted tragedy. This systemic inefficiency persists unchallenged: Big Adtech platforms remain silent to protect their profits, CMOs avoid the topic in boardrooms fearing budget cuts, and CEOs remain largely unaware of this massive profit leak. With each passing quarter, this insidious drain tightens the vice between skyrocketing Customer Acquisition Costs (CAC) and declining Customer Lifetime Value (LTV), slowly strangling business profitability and hurting shareholder value. Two breakthrough innovations now offer a path to liberation from this costly cycle.

The Root of AdWaste: Marketing’s Twin Failures

AdWaste isn’t merely inefficient spending—it’s the symptom of two fundamental marketing failures. First, the “Not For Me” problem: generic messaging that fails to resonate with individual needs and preferences. Second, the “No Hotline” problem: the absence of reliable engagement channels between brands and customers. When these failures combine, attention recession follows—customers mentally unsubscribe long before formally opting out, forcing brands into expensive reacquisition through Google and Meta’s auction-based platforms.

This vicious cycle creates a mathematical impossibility: sustainable profitable growth cannot coexist with perpetual reacquisition. For decades, this systemic inefficiency persisted unchallenged—until now. Progency and NeoN dismantle AdWaste, offering brands new hope: slashing reacquisition costs by 30-50% while unlocking trapped profit potential.

Progency: Transforming Martech’s Promise

What if martech platforms evolved beyond selling software to guaranteeing outcomes? Today’s powerful martech platforms sit largely underutilised—victims of the execution gap between technological capability and operational reality. Most brands leverage just 30-40% of their martech features despite significant investments.

Progency—a fusion of product, expertise, AI agents, and continuous improvement—represents the missing link. Through the PEAK framework (Platform, Experts, AI agents, Kaizen), Progency delivers true N=1 personalization at scale, transforming martech economics from cost-centre software to performance-based profit engines. This isn’t outsourcing—it’s a revolutionary approach where compensation ties directly to measurable business impact.

NeoN: The Authenticated Attention Exchange

Simultaneously, NeoN introduces a paradigm shift in reacquisition through PII-based (Personally Identifiable Information) targeting. This authenticated identity network enables brand-to-brand collaboration without expensive intermediaries. Through NeoN, one brand’s inactive “Test” customers can be precisely targeted through another brand’s engaged “Best” customer channels.

This creates a powerful dual advantage: publishers “print money” by monetising their engaged audience while advertisers “save money” through dramatically more efficient reacquisition—cutting costs by 30-50% compared to traditional platforms.

The NeoMarketing Revolution

Together, Progency and NeoN form the twin pillars of NeoMarketing—marketing’s third great era following Traditional Marketing (1950s-1990s) and Modern Marketing (2000s-2020s). This transformation fundamentally inverts established priorities: retention before acquisition, relationships before transactions, and precision before volume.

For CMOs, this represents an unprecedented opportunity to evolve from money guzzling managers into C-Suite MVPs—the executives who transform marketing from necessary expense into the primary profit engine driving sustainable business growth.

In this series, I’ll build upon my previous writings to outline a practical pathway toward this new future—one where AdWaste becomes a relic of the past, and marketing finally fulfils its promise as the catalyst for profitable, sustainable growth.

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Best and Rest Customers

I have written multiple essays recently about Progency:

• Progency: The AI-First Agency of the Future
• Progency’s Problem-solving Prowess
• From SaaS to Success: The Progency Proposition

Progency’s transformative power lies in its singular focus: driving revenue upside to maximise Customer Lifetime Value (LTV). Unlike traditional agencies or martech implementations, Progency operates exclusively on performance-based economics—taking ownership of interactions with specific customer segments whilst being compensated solely on incremental revenue generated above established baselines. This distinctive approach aligns incentives perfectly: Progency succeeds only when brands succeed.

What enables Progency to outperform brands’ internal marketing departments? The answer lies in its comprehensive PEAK framework:

• Platform Mastery: As an extension of the martech vendor, Progency possesses unparalleled platform expertise. This intimate knowledge unlocks the full potential of martech systems that typically sit 60-65% unutilised within brand environments. Whilst internal teams struggle with limited bandwidth to leverage advanced features, Progency operates with complete command of every capability, from sophisticated segmentation algorithms to complex journey orchestration.
• Expert Specialisation: Progency deploys vertical industry specialists with deep domain knowledge—professionals who understand not just the technology but the specific business contexts in which it operates. These experts bring contextual intelligence that general marketers cannot match, identifying revenue opportunities and optimisation levers that internal teams often miss due to operational constraints or knowledge gaps.
• AI Agent Orchestration: Whilst marketing departments wrestle with incorporating rudimentary AI into their workflows, Progency deploys sophisticated AI agent ecosystems operating at unprecedented scale. These include specialised agents for segmentation, content creation, journey orchestration, and performance analysis—all coordinated by an AI Co-Marketer that ensures alignment with brand guidelines and business objectives. This “Department of One” enables true N=1 personalisation without proportional staffing increases.
• Kaizen Methodology: Progency implements continuous improvement systems that transcend traditional campaign-based thinking. Through rigorous A/B testing, real-time performance monitoring, and systematic optimisation across all customer touchpoints, Progency creates a virtuous cycle where every interaction generates insights that improve future engagements. This systematic approach ensures compounding performance improvements that outpace episodic campaign optimisations.

By mastering the platform, leveraging expert specialisation, employing AI agents, and implementing continuous improvement, Progency directly addresses the “Not For Me” and “No Hotline’ problems” that fuel AdWaste.

Progency delivers its greatest impact across two critical customer segments:

• Best Customers (top 20% who deliver 60-80% of revenue and 200% of profits) benefit from hyper-personalised experiences that maximise individual LTV potential. By understanding specific preferences and behaviours at granular levels, Progency identifies cross-sell and upsell opportunities that generic segmentation approaches invariably miss.
• Rest Customers (the middle 40-50% showing declining engagement) receive precisely timed interventions that prevent the slide into dormancy. Through AI-orchestrated personalisation and daily hotlines crafted via NeoMails, Progency systematically converts these wavering relationships into Best customer status—unlocking substantial revenue currently left unrealised by resource-constrained marketing departments.

Additionally, Progency harnesses these engaged segments to drive referral programmes that simultaneously reduce CAC and increase Earned Growth—transforming existing customers into acquisition engines that bypass expensive adtech platforms entirely.

The cumulative advantage becomes clear: whether performing complex segmentation, creating personalised content, orchestrating sophisticated journeys, or executing multichannel campaigns, AI-powered Progency consistently outperforms human-centric marketing departments. The result isn’t merely improved efficiency but a fundamental transformation in how brands monetise customer relationships—shifting marketing from cost centre to profit engine through measurable, sustainable revenue growth.

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Test and Next

I have written multiple essays recently about NeoN:

• Inbox to Income: BEAN for Revenue and Reactivation
• NEON: Breaking Free from Big AdTech with an Open Collaborative Network
• NEON: How Emails can Print and Save Money

AdWaste represents the single greatest destroyer of brand profitability today—a staggering $500 billion globally squandered on reacquiring customers who already exist in brands’ databases. This inefficiency stems primarily from dormant, inactive, or churned “Test” customers who become unreachable through owned channels, forcing brands into expensive retargeting through Google and Meta’s auction-based platforms.

While Progency’s mission is building reliable hotlines to prevent customers falling into attention recession, NeoN addresses the inevitable reality: some customers will still disengage. For these Test customers—and for genuinely new Next customers—NeoN provides a revolutionary alternative to traditional adtech platforms, fundamentally transforming both reacquisition and new acquisition economics.

The PACE framework powers NeoN’s disruptive approach:

• PII Matching Engine: Unlike cookie-based targeting that relies on probabilistic matching, NeoN’s core innovation is its authenticated identity engine. This precise system enables brands to reach their dormant Test customers through the active email engagement channels of non-competing brands. When Brand A wants to reconnect with inactive customers, NeoN identifies where those individuals appear as engaged Best customers for Brand B—creating a direct, privacy-compliant pathway for reacquisition without platform intermediaries.
• ActionAds: Traditional digital advertising suffers from a devastating “click-through penalty” where 80-90% of potential conversions are lost when customers must leave their current environment. NeoN eliminates this friction through AMP-powered ActionAds embedded within partner emails. These interactive mini-applications enable customers to browse products, complete forms, and make purchases without ever leaving their inbox—dramatically increasing conversion rates whilst reducing acquisition costs.
• Cooperative Structure: NeoN creates a brand-to-brand marketplace where companies simultaneously play dual roles—as publishers monetising their Best customers’ attention and as advertisers efficiently reacquiring their Test customers. This cooperative approach bypasses expensive platform intermediaries whilst creating powerful network effects: each new brand joining the ecosystem adds both valuable inventory and targetable audiences.
• Ecosystem Services: Beyond its core matching capabilities, NeoN builds complementary utilities that expand email inventory opportunities whilst enhancing data capabilities. These include inbox intelligence utilities, AI-powered daily newsletters and games, an Atomic Rewards system for micro-actions, and sophisticated data management platform (DMP) functionality for identifying high-potential audiences for new acquisition.

Through PII matching, ActionAds, a cooperative structure, and its ecosystem services, NeoN provides a powerful alternative to traditional adtech, directly addressing the inefficiencies of customer reacquisition.

NeoN delivers transformative value across the other two customer segments:

• For Test customers (dormant 90+ days), NeoN enables precision reacquisition at 30-50% lower cost than traditional platforms. By reaching these individuals through channels where they’re actively engaged, brands can reconnect relationships at a fraction of typical adtech costs—immediately improving marketing ROI whilst reducing platform dependency.
• For Next customers (genuinely new acquisitions), NeoN leverages its accumulated cross-brand intelligence to identify high-potential prospects with unprecedented precision. Unlike traditional lookalike modelling that relies on superficial behavioural signals, NeoN’s authenticated approach enables acquisition targeting based on genuine affinity and proven engagement patterns, with a specific focus on in-market segments (akin to what Google and Meta do).

The revolutionary impact lies in NeoN’s ability to create a virtuous cycle where brands simultaneously “print money” by monetising their engaged audience and “save money” through dramatically more efficient customer acquisition to reduce CAC. This dual advantage fundamentally rewires marketing economics—liberating brands from platform dependency whilst transforming customer attention from cost centre to profit engine.

By creating a viable alternative to Big Adtech for both reacquisition and new customer acquisition, NeoN delivers the missing piece in the AdWaste solution puzzle: a pathway to sustainable, profitable growth that isn’t built on platform dependency and endless acquisition cycles.

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Email Utilities

NeoN’s true power lies not just in its PII-based matching engine, but in the complementary suite of email-focused utilities that extend its reach and sharpen its targeting precision. These utilities create new inventory channels while simultaneously collecting zero-party data—fuelling high-accuracy targeting for both reacquisition and new customer acquisition, and dramatically accelerating the fight against AdWaste.

The development of proprietary utilities follows a proven strategic playbook employed by digital giants—one that has redefined the digital landscape. Google built its empire atop Search, Gmail, Maps and YouTube, whilst Meta constructed its walled garden through Facebook, Instagram and WhatsApp. These owned properties serve a dual purpose that transcends their consumer-facing utility: they generate both first-party inventory and invaluable user data. By establishing its own ecosystem of email utilities, NeoN creates a virtuous cycle where consumer value drives adoption, adoption creates inventory, inventory enables monetisation, and interaction data enhances targeting precision. This strategic approach allows NeoN to gradually reduce dependency on third-party inventory sources whilst simultaneously building targeting capabilities that rival or exceed traditional platforms—all whilst maintaining complete ownership of the value chain. Unlike traditional ad networks that merely broker others’ attention, NeoN’s owned properties establish direct consumer relationships that create sustainable competitive advantages in both inventory quality and targeting precision.

Mindmap: Intelligent Inbox Assistant

Mindmap serves as NeoN’s intelligent inbox layer, applying sophisticated AI to transform email from an overwhelming stream of messages into actionable intelligence. Unlike conventional email clients that simply organise messages chronologically or by sender, Mindmap analyses content to extract meaningful patterns, commitments, and opportunities.

Key features include:

• Receipt Analysis: Automatically identifying and categorising purchases to create valuable in-market segments based on actual spending behaviour rather than mere browsing signals
• Commitment Detection: Surfacing promises made or received within emails (“I’ll send you that report by Friday”) to create contextual task lists without manual entry
• Intelligent Summarisation: Distilling lengthy messages into actionable bullet points, enabling users to process information more efficiently
• Predictive Organisation: Clustering related communications across time to provide conversation threads that transcend traditional folder structures
• “Just One Thing”: Curating a single high-value insight or action item every few hours, creating a habit-forming engagement pattern

Mindmap addresses a fundamental consumer pain point—email overwhelm—whilst simultaneously providing NeoN with invaluable insights into purchase patterns, brand relationships, and consumer preferences. This zero-party data, gathered with explicit consent, powers targeting capabilities that match or exceed what Google and Meta offer through tracking and inference.

MyToday: Personalised Micron Delivery

MyToday reimagines newsletters through AI-powered personalisation and interactive AMP experiences. Unlike traditional email newsletters that deliver identical content to all subscribers, MyToday creates truly individualised daily experiences:

• AI-Generated Content: Tailored news, information, and entertainment based on demonstrated interests and engagement patterns
• Interactive Microns: 15-60 second “brain gain” experiences including games, puzzles, quizzes, and micro-learning modules
• Personalised Timing: Delivery optimised for each recipient’s engagement patterns rather than arbitrary scheduling

MyToday serves two crucial functions within the NeoN ecosystem: creating valuable daily inventory for ActionAds whilst simultaneously deepening user profiles through engagement data. Each interaction reveals preferences, interests, and receptivity to different content types—information that enhances targeting precision across the entire network.

Muniverse: The Atomic Rewards Platform

Muniverse introduces a revolutionary approach to attention economics through its Atomic Rewards (Mu) system. This micro-incentive framework transforms mundane digital interactions into rewarding experiences:

• Micro-Earning Opportunities: Points awarded for small actions like opening emails, completing surveys, providing preferences, or engaging with content
• RaffleCash System: A gamified redemption approach where accumulated points enter users into daily, weekly, and monthly prize draws
• Attention Marketplace: A self-sustaining economy where brands fund rewards in exchange for verified attention
• Cross-Brand Portability: Rewards earned across participating NeoN partners, creating powerful network effects

Muniverse addresses a fundamental market failure in digital marketing: the asymmetrical value exchange between consumers and advertisers. By creating a transparent system where attention is properly valued and compensated, Muniverse transforms the traditional adversarial relationship into a mutually beneficial partnership.

From NeoN’s perspective, Muniverse serves as both an engagement driver and a precision targeting enhancer. The granular preference data gathered through reward-incentivised actions enables targeting capabilities that far exceed traditional lookalike modelling, particularly for in-market segments with demonstrated purchase intent.

Micronbox: The Future-Proof Messaging Platform

Micronbox represents NeoN’s strategic hedge against platform dependency. This lightweight messaging system linked to both mobile numbers and email addresses provides:

• Universal Inbox: Messages accessible regardless of device or primary messaging platform
• Platform Independence: Control over delivery mechanisms without dependence on potentially restrictive platforms
• Rich Interactive Experiences: Native support for AMP elements, allowing sophisticated in-message applications
• Identity Verification: Multi-factor authentication enhancing the reliability of PII matching

While initially positioned as a complementary channel, Micronbox provides crucial insurance against potential restrictions from email providers like Gmail. Should platform policies change, Micronbox offers a direct, owned channel to verified audiences—maintaining NeoN’s ability to deliver authenticated targeting at scale.

The Integrated Ecosystem Advantage

Individually, each utility delivers significant consumer value whilst enhancing NeoN’s core capabilities. Together, they create a self-reinforcing ecosystem with powerful network effects:

1. Complementary Data Signals: Behavioural patterns across utilities provide multi-dimensional understanding of consumer preferences
2. Cross-Utility Engagement: Users of one service naturally discover and adopt others, creating efficient customer acquisition
3. Enhanced Targeting Precision: Combined intelligence enables targeting capabilities that rival or exceed traditional platforms
4. Sustainable Value Exchange: Genuine utility ensures ongoing consumer engagement, creating persistent rather than transactional relationships

This ecosystem approach transcends traditional adtech strategies that focus solely on targeting efficiency without addressing the fundamental attention recession crisis. By creating services people actively value, NeoN establishes reliable “hotlines” to consumers—solving the very problem that creates AdWaste in the first place.

For brands seeking alternatives to Google and Meta’s increasingly expensive walled gardens, NeoN’s email utilities create not merely another advertising channel but a fundamentally different approach to consumer relationships: one built on authenticated identity, genuine value exchange, and sustainable attention economics.

Additional Readings:

• Epps Footers: New Frontiers in Email Marketing
• Email Envelope: Eight Elements to Energise Engagement
• Mu: The Currency of Email Engagement
• NeoMarketing’s Crux: Creating AI-Powered Micro-Moments That Amaze
• Brain Rot to Brain Gain: Can Microns in NeoMails be the Answer?

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The NeoMarketing Era

For far too long, marketing has been trapped in a cycle of profitless prosperity—growing revenues that never translate into sustainable profits due to spiralling acquisition costs and stagnant customer lifetime value. This dysfunctional system redirects approximately $500 billion annually into “AdWaste”—money spent reacquiring customers brands already know, creating perhaps the greatest untapped profit opportunity in modern business.

Marketing’s mission must fundamentally change. Beyond building brands and driving performance campaigns, marketing must become the primary engine for profitable growth by systematically eliminating AdWaste and driving Earned Growth. This transformation heralds NeoMarketing—marketing’s third great era following Traditional Marketing (1950s-1990s) and Modern Marketing (2000s-2020s).

NeoMarketing is built on a revolutionary segment-based framework. Unlike demographic or psychographic segmentation, the BRTN approach categorises customers based on their actual engagement patterns and value contribution:

Best customers (top 20%) receive hyper-personalised experiences that maximise individual LTV and transform them into referral engines through Progency’s AI-orchestrated journeys.

Rest customers (middle 50%) benefit from NeoMails (and Progency) that establish reliable daily hotlines, preventing the attention recession that leads to dormancy and costly reacquisition.

Test customers (dormant 30%) are precisely targeted through NeoN’s authenticated identity network at a fraction of traditional platform costs, dramatically reducing reacquisition waste.

Next customers (new acquisitions) are efficiently targeted through NeoN’s sophisticated DMP capabilities, leveraging cross-brand intelligence to identify genuinely high-potential prospects.

Two breakthrough innovations make this vision achievable:

• Progency transforms martech from “software without service” into “software with success”—combining proprietary platform capabilities with specialist expertise and AI agent orchestration in a performance-based model. By eliminating platform costs in favour of revenue-sharing tied directly to measurable outcomes, Progency creates perfect alignment between technology providers and business results.
• NeoN reimagines advertising through authenticated identity, enabling brand-to-brand collaboration without expensive intermediaries. This cooperative approach simultaneously allows brands to “print money” by monetising their engaged audience and “save money” through dramatically more efficient customer acquisition.

These innovations are enhanced through proprietary email utilities that generate both invaluable first-party data and additional inventory channels—creating a self-reinforcing ecosystem that gradually reduces dependency on third-party platforms whilst building targeting capabilities that rival or exceed traditional adtech giants.

The cumulative impact of these innovations isn’t merely improved efficiency but a fundamental transformation in marketing economics. By maximising LTV through deeper, more valuable customer relationships whilst simultaneously minimising CAC through precision targeting and referral programmes, NeoMarketing creates a sustainable growth engine that eliminates the wasteful acquisition cycles plaguing modern businesses.

For CMOs, this is an unprecedented opportunity to evolve from managing a cost centre to becoming C-Suite MVPs—executives who transform marketing from a necessary expense into the central profit engine driving sustainable business growth. By abandoning the sinking ship of acquisition addiction and embracing the lifeline of NeoMarketing’s retention-first approach, CMOs can finally deliver the profitability metrics that cement their strategic importance in the boardroom.

The future belongs to organisations that recognise this shift—those who redirect resources from wasteful acquisition to value-creating retention strategies focused on genuine customer needs rather than platform metrics. Brands that continue the acquisition addiction will find themselves trapped in an increasingly expensive race to the bottom, whilst those who embrace NeoMarketing will discover the ultimate competitive advantage: profitable growth through authentic, valuable customer relationships.

Published May 19, 2025

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The recent SaaSBoomi Annual 2025 was a watershed moment that crystallised a fundamental truth: the traditional SaaS model is reaching its evolutionary endpoint. While conversations buzzed about “SaaS AI” and the opportunity to capture “salary TAM” through Agentic AI (alongside India’s domestic software market), these discussions merely scratched the surface of a more profound shift required in how software delivers value in the AI era

I asked Perplexity to summarise the key themes discussed:

1. Transition from SaaS to AI: The event emphasised the pivotal shift from traditional SaaS to AI-powered solutions. Sessions explored how companies can integrate AI into their products and processes, reinvent business models, and address challenges posed by this transition.
2. AI Product and Technology: A significant focus was placed on moving beyond AI hype to delve into practical engineering and product design efforts. This included frameworks for scalable architectures, data mastery, compliance, security, and personalized user experiences.
3. Vertical AI Opportunities: The event highlighted sector-specific opportunities in industries such as manufacturing, energy, and life sciences. Founders were encouraged to collaborate with industry leaders to solve real-world problems using AI solutions/
4. India’s SaaS Advantage: The event spotlighted India’s potential to become a global hub for SaaS and AI innovation, leveraging its talent pool and market opportunities. Discussions also covered India’s software market outlook for 2035.
5. New World Order: A recurring theme was the emergence of a “New World Order,” where mastering AI integration with industry expertise would define successful companies of the future. This theme underscored India’s role in leading this transformation.

A post-event Rothschild report added more colour to the impact of AI on SaaS:

• AI is fundamentally changing SaaS, making conventional subscription-based models irrelevant as AI-driven automation takes over
• Future software will not just offer tools but will act as autonomous agents executing business processes without human intervention
• Companies relying on feature-based SaaS offerings will struggle as AI-driven automation reshapes the landscape
• AI-powered business applications will move from static workflows to self-learning systems capable of real-time decision-making
• The age of static, subscription-based SaaS pricing is coming to an end as
• AI disrupts how software is sold and monetized
• Future AI-first solutions will shift towards usage-based, outcome-driven pricing where businesses pay for automation, intelligence, and efficiency, not just access to software

Yet these observations, while insightful, don’t address the most critical evolutionary leap SaaS must make: transforming from software vendors to success partners. This is the essence of Progency—the fusion of product, agents, and agency that reimagines how software creates value. The harsh reality is that SaaS has largely been software without service, leaving customers with powerful tools but inadequate expertise to leverage them effectively.

This fundamental disconnect has created an execution gap where brands typically utilise only 30-40% of their platform capabilities despite significant investments. SaaS companies must now add a thin service layer—initially human-led but increasingly powered by AI agents—that ensures customer outcomes rather than merely providing access to features.

By embracing performance-based pricing tied directly to business results, SaaS companies create perfect alignment with their customers: they win only when their customers win. This shift from selling inputs (features, seats, API calls) to guaranteeing outputs (revenue growth, cost savings, measurable business improvements) transforms the SaaS business model from a capped subscription revenue stream to an unlimited upside opportunity with truly “infinite” TAM.

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Previous Writings

NeoSaaS: From India First to Global Leader in Big Martech (Dec 2024): “As the world’s foremost hub of software engineering talent still awaits its first homegrown software products multinational, this series explores how a powerful convergence of Indian innovation, US market access, AI capabilities, and strategic acquisitions could finally produce that elusive global colossus – one that dominates at home while becoming a formidable player in the US and beyond. Let’s call this company “NeoSaaS”. The name signifies more than just another software venture – it represents a transformational business model built on the foundation of four interconnected pillars: strategy, software, services, and profit sharing (the 4S framework). This unique approach transcends traditional SaaS boundaries, creating a blueprint for a world-class software entity emerging from India.” I focused on the AdWaste opportunity in marketing. “While most SaaS companies focus heavily on their software offerings, merely providing great software is insufficient for creating a game-changing solution. NeoSaaS must transcend traditional SaaS limitations by embracing a comprehensive 4S framework that combines product and agency (Progency) and transforms it from a vendor into a true partner in customer success: Strategy, Software (Stack), Service (Kaizen Progency), Sharing (Profit)… This 4S framework ensures that NeoSaaS delivers comprehensive solutions rather than just tools. By combining strategic guidance, powerful software, continuous service improvement, and aligned incentives, NeoSaaS creates an ecosystem that truly enables customer success. The result is not just a product deployment but a transformative partnership that drives measurable business impact.”

SaaS Futures: Exploring New Revenues Streams (Aug 2024): In this series, I focused on new products, new markets, new geos, services, and M&A. On services, I wrote: “SaaS and Services have traditionally been viewed as fundamentally different business models, akin to chalk and cheese for most companies. The mindsets driving these two approaches are indeed quite distinct. SaaS companies typically focus on scalability, product development, and recurring revenue, while service-oriented businesses emphasise customisation, client relationships, and project-based work. The economic metrics for these models also diverge significantly. SaaS companies are often valued based on their high gross margins and the predictability of their recurring revenue, resulting in higher valuation multiples. In contrast, services businesses generally have lower gross margins due to the labour-intensive nature of their work and are typically valued at lower multiples. However, in today’s challenging business landscape, where competition is fierce and customer expectations are ever-increasing, software companies must be open to exploring new avenues for growth and customer satisfaction. This is where a thin layer of services as an add-on capability can prove invaluable.”

New SaaS: Services, AI Agents, Sharing (May 2024): I wrote about the new SaaS: Services, AI Agents, Sharing. “Services…bring in people into the product proposition to ensure continuous monitoring and improvement. This component integrates human expertise and intervention into the digital offering, enhancing the adaptability and personalisation of the software…AI Agents help automate conversations, tasks, and ‘next best action’ predictions. These autonomous, intelligent systems empower the platform by automating interactions, streamlining tasks, and providing predictive insights…Sharing (a “progency” business model) combines product and agency, to price based on performance and outcomes. It redefines the economic relationship between service providers and their customers. By adopting a performance-based pricing strategy, the focus shifts towards shared success and outcomes…The “New SaaS” can be defined as an integrated, outcome-driven ecosystem that leverages the synergistic potential of services, AI agents, and performance-based collaboration.”

Additional writings:

• Bundled Kaizen Services: An Advantage for Indian SaaS
• FAB: A New Model for Enterprise Software
• Profishare: A New Business Model for Enterprise Software
• LEMMMA: A Playbook for US SaaS Success at Scale

3

3D Evolution

As I see it, SaaS needs to evolve along three axes: a thin layer of services, AI Agents, and success-based pricing. This three-dimensional transformation will fundamentally redefine the relationship between software providers and their customers.

1. Thin Layer of Services: From Tool Provider to Success Partner

Traditional SaaS deploys powerful platforms but leaves implementation largely to customers, creating an execution gap where capabilities exceed utilisation. A thin layer of specialised services—strategically added without transforming into a full-service consultancy—bridges this critical divide.

This services layer includes:

• Implementation specialists who understand industry-specific workflows
• Vertical experts who translate software capabilities into business outcomes
• Ongoing optimisation consultants focused on continuous improvement

The goal isn’t providing extensive professional services but ensuring customers extract maximum value from their software investment. This approach transforms the vendor-client relationship from “here’s your license, good luck” to “we’re invested in your operational success.”

2. AI Agents: From Passive Tools to Active Participants

The second evolutionary axis introduces AI agents that transform software from tools that await human instructions into systems that proactively execute business processes. These agents fundamentally alter how organisations interact with software:

• Autonomous Operations: Agents handle routine tasks without human intervention, from data analysis to workflow orchestration
• Predictive Intelligence: Systems that anticipate needs before users articulate them
• Continuous Learning: Capabilities that improve automatically through usage patterns
• Cross-Functional Coordination: Multiple specialised agents working in concert to accomplish complex business objectives

This shift goes beyond automating existing processes—it fundamentally reimagines how work gets done. AI agents don’t just augment human capabilities; they create entirely new operational paradigms where systems take initiative rather than merely responding to commands.

3. Success-Based Pricing: From Access to Outcomes

Perhaps the most revolutionary axis is the shift from subscription-based pricing (paying for access) to success-based models (paying for outcomes):

• Performance Metrics: Compensation tied to specific KPIs relevant to the customer’s business
• Risk-Sharing: Vendors assume partial responsibility for implementation success
• Unlimited Upside: Both parties benefit proportionally from exceptional results
• Value Quantification: Rigorous measurement of software’s business impact

This approach requires vendors to develop sophisticated measurement frameworks and prediction capabilities. More importantly, it demands the courage to stand behind one’s product with financial commitments.

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The combination of these three axes—services, AI agents, and success-based pricing—creates a new entity that transcends traditional SaaS – Progency. This isn’t incremental improvement but fundamental reinvention. Companies making this transition aren’t merely selling better software; they’re guaranteeing better business outcomes through an integrated approach that combines human expertise, autonomous intelligence, and aligned economic incentives.

For enterprise buyers, this evolution eliminates the frustration of underutilised software investments. For vendors, it transforms the addressable market from software budgets to business outcomes—exponentially increasing potential revenue while creating deeper, more strategic client relationships.

4

What’s Changed

For several years, I’ve been exploring the Progency concept within martech—the powerful fusion of product and agency capabilities. Initially, my conversations with marketers revealed a fundamental misunderstanding: many interpreted the “agency” component as merely outsourced labour performing the same tasks as their internal teams. This approach would simply shift costs without addressing the core inefficiencies that prevent outcome-based pricing models.

My perspective transformed fundamentally a few months ago during a demonstration of Netcore’s Agentic AI system. Unlike isolated agents performing discrete tasks, I witnessed a sophisticated multi-agent ecosystem working collaboratively toward complex business objectives. This revelation crystallised a crucial insight: the “gen” in Progency shouldn’t represent generic services but rather AI agents—autonomous systems that could transform execution capabilities while dramatically reducing operational costs.

Yet this insight revealed another challenge. While organisations could theoretically deploy these AI agents themselves, the reality of effective AI utilisation remains stubbornly difficult. Even after two and a half years of widespread ChatGPT adoption, most professionals still struggle with effective prompting. As I frequently remind colleagues, crafting the right instructions to generate optimal AI outputs remains an underappreciated skill—one that prevents organisations from fully leveraging even the most sophisticated AI systems.

The integration of AI agents into the Progency model transcends the original vision of a thin services layer with performance-based pricing. While that approach would have offered incremental improvements and modest upside potential, it wouldn’t have created the scale necessary to make Progency economically transformative across diverse client portfolios. AI agents fundamentally alter this equation by enabling a previously unimaginable economic model: zero upfront platform costs coupled with compensation tied exclusively to measurable business outcomes.

This revolutionary approach draws inspiration from adtech’s remarkable trajectory over the past two decades. The advertising technology sector has grown into a $700 billion industry boasting some of the highest gross margins and profitability in the technology sector. This extraordinary success didn’t occur through traditional software licensing or agency service models—it emerged when the industry decisively shifted from input-based metrics (cost per thousand impressions, or CPM) to outcome-based models (cost per click, or CPC).

By directly tying costs to measurable business results, adtech created perfect alignment between platform capabilities and client objectives. The platforms that delivered superior outcomes thrived; those that couldn’t deliver results quickly perished. This ruthlessly efficient model drove unprecedented innovation and value creation for both providers and their clients.

For established SaaS companies, the Progency model represents both an extraordinary opportunity and an existential imperative: disrupt your own business model before newcomers inevitably do. As AI capabilities accelerate, the window for this transformation is rapidly narrowing. The first-movers who successfully implement the Progency approach—integrating specialised services, AI agent orchestration, and outcome-based economics—will establish competitive advantages that laggards simply cannot overcome.

This is more than just a pricing shift or a service enhancement; it’s a fundamental reimagining of the relationship between software providers and their customers. In the Progency future, vendors don’t sell access to capabilities—they guarantee business results, creating a virtuous cycle of continuous improvement where both parties’ interests align perfectly around measurable outcomes.

5

Startup!

What should SaaS companies do to embrace this revolutionary model? This question has occupied my thoughts particularly in relation to Netcore’s Martech SaaS platform, though the principles apply broadly across the enterprise software landscape. My recommendation: create an internal startup dedicated to building a Progency offering, focusing initially on prospects where it is a struggle to gain traction. In essence, carve out a blue ocean opportunity within the increasingly commoditised red ocean of SaaS.

Incumbent SaaS companies possess three critical advantages: established clients, recurring contracts, and predictable cashflows. These should continue undisturbed while a separate, dedicated team launches a “Progency Startup” within the organisation. This new venture leverages the full capabilities of the existing platform alongside the thin managed services layer that the SaaS business has already developed. Over time, the human elements within these services will be systematically augmented and eventually replaced by AI agents, creating unprecedented economies of scale.

The fundamental differentiators for this internal startup lie in its go-to-market strategy and pricing model.

Every business exhibits a power law distribution across its customer base: approximately 20% of customers (the “Best” segment) typically generate 60-80% of revenue. The Progency Startup should strategically target the next 40%—the “Rest” customers who account for the remainder of revenue but often receive disproportionately less attention. (The final category, “Test,” encompasses dormant and churned customers requiring separate reactivation/reacquisition strategies.)

The Progency Startup’s revolutionary proposition to prospective clients is straightforward yet compelling: “Let us take ownership of your ‘Rest’ customer segment with zero platform fees. This allows your team to focus exclusively on your highest-value customers while we apply our PEAK framework—Platform, Experts, AI Agents, and Kaizen methodology—to maximise value from your underserved middle segment.”

This approach creates a win-win scenario. Clients eliminate costs associated with servicing these customers while maintaining revenue streams. Meanwhile, the Progency demonstrates its superior capabilities through a genuine skin-in-the-game approach—earning money only when it delivers revenues exceeding established baselines. The underlying thesis is powerful: Progency’s orchestrated AI agents will consistently outperform the client’s human teams in addressing the personalised needs of this long-tail customer segment.

While the “Best” customers ultimately represent the more lucrative prize, successfully demonstrating measurable results with the “Rest” segment accomplishes something far more valuable than gaining initial market entry—it earns the Progency a strategic seat at the decision-making table. Success creates an irrefutable case for expanding the model to encompass the client’s entire customer base.

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The path forward for SaaS companies is clear: reinvent themselves through the Progency model before market forces make this transition inevitable. Begin at the periphery where resistance is lowest, demonstrate compelling results through outcome-based economics, and methodically expand toward the core business. The performance-based paradigm of Progency it the destined evolution for enterprise software that will separate tomorrow’s winners from legacy providers clinging to yesterday’s business models.

The question isn’t whether this transformation will occur, but rather: which visionary companies will lead this revolution, and which will follow belatedly—if they survive at all?

6

Other Industries

I asked the AIs to provide examples of success-based models from other industries.

While the evolution from SaaS to Progency draws significant inspiration from adtech’s transformation, numerous other industries have successfully implemented outcome-based economic models. These precedents not only validate the viability of success-based approaches but offer valuable blueprints for implementation within the enterprise software sector.

Healthcare’s Value-Based Revolution

Perhaps the most ambitious shift toward outcome-based economics is occurring in healthcare, where fee-for-service models are gradually giving way to value-based care arrangements. Under these frameworks, providers receive compensation based on patient outcomes rather than the volume of procedures performed.

Accountable Care Organisations (ACOs) in the US exemplify this approach—receiving financial rewards when they improve patient health metrics while simultaneously reducing overall treatment costs. This transformation fundamentally realigns healthcare provider incentives from maximising billable procedures to optimising patient health outcomes—a perfect parallel to Progency’s shift from selling software access to delivering measurable business results.

Energy Sector’s Performance Contracting

Energy Service Companies (ESCOs) have pioneered performance-based models through Energy Savings Performance Contracts. These innovative arrangements allow organisations to implement energy efficiency upgrades with zero upfront capital investment. The ESCO finances and implements the improvements, then receives compensation exclusively from the documented energy savings achieved over time.

This model has transformed energy efficiency from a capital expenditure decision to an operational improvement with guaranteed positive ROI. The parallel for SaaS is compelling: rather than requiring customers to invest in software licenses hoping for eventual returns, Progency enables organisations to implement solutions with compensation tied directly to measurable efficiency gains or revenue improvements.

Legal Services’ Contingency Approach

The legal industry has long employed outcome-based economics through contingency fee arrangements, where law firms receive payment only upon successful case outcomes. This approach fundamentally transforms the attorney-client relationship by creating perfect alignment around a common objective—winning the case.

What makes this model particularly relevant to Progency is its risk-shifting mechanism. The service provider (law firm) assumes significant upfront investment with compensation contingent on delivering specific results. This arrangement has democratised access to legal representation while ensuring lawyers are incentivised to maximise client outcomes rather than billable hours.

Manufacturing’s “Power-by-the-Hour”

Traditional industrial manufacturers have revolutionised their business models through outcome-based approaches like Rolls-Royce’s pioneering “Power-by-the-Hour” concept. Rather than selling jet engines outright, Rolls-Royce charges airlines based on engine uptime and performance. This transforms the relationship from a transactional hardware purchase to an ongoing partnership focused on operational reliability.

This approach mirrors Progency’s potential in enterprise software—shifting from selling products to guaranteeing operational performance. The customer no longer bears all the risk of implementation success; instead, the provider is directly incentivised to ensure continuous optimal performance.

Education’s Income Share Agreements

Perhaps the most innovative recent application of outcome-based economics appears in education, where coding bootcamps and alternative educational providers implement Income Share Agreements (ISAs). Students pay no upfront tuition, instead committing to share a percentage of their post-graduation income for a defined period.

This model creates extraordinary alignment between educational providers and students—schools succeed financially only when their graduates secure well-paying positions, driving relentless focus on employable skills and job placement. Similarly, Progency succeeds only when its clients achieve measurable business improvements, creating an educational incentive to continuously enhance capabilities and outcomes.

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The Common Thread: Risk Shift and Incentive Alignment

What unites these diverse examples is a fundamental reallocation of risk and realignment of incentives. In each case, service providers assume greater upfront risk in exchange for participation in the value they create. This arrangement naturally drives continuous improvement, as providers constantly seek to enhance outcomes that directly impact their compensation.

For SaaS companies considering the Progency model, these precedents demonstrate that success-based approaches can create thriving economic ecosystems across widely varying industries. More importantly, they illustrate how such models can transform client relationships from transactional vendor interactions to true strategic partnerships—precisely the evolution enterprise software needs in the age of AI and growing customer expectations.

7

Critique

I then asked the AIs for a critical assessment of the Progency ideas.

Implementation Hurdles

Measurement Complexity
The success-based model hinges on accurately measuring outcomes attributable to the software. In complex business environments, establishing clear causality between software usage and business results can be exceptionally difficult. Factors beyond the software’s control—market conditions, competitor actions, internal execution—significantly impact outcomes, creating potential attribution disputes that could undermine the entire model.

Scope Definition and Baseline Establishment
Defining what constitutes “success” and establishing appropriate performance baselines presents considerable challenges. Without rigorous, mutually agreed frameworks, companies risk either setting targets too low (creating windfall profits for Progency providers) or too high (making success impossible). The initial negotiation period could become protracted and contentious.

Economic Viability Concerns

Cash Flow Challenges
The zero-upfront cost model, while attractive to clients, creates significant cash flow challenges for providers. Traditional SaaS businesses rely on predictable subscription revenue to fund ongoing operations, development, and growth. Progency providers must secure substantial capital to sustain operations during the potentially lengthy period before success metrics generate revenue—particularly problematic for smaller SaaS companies or startups.

Risk Allocation Imbalance
While sharing risk theoretically creates alignment, the Progency provider potentially assumes disproportionate risk. Factors outside their control (executive decisions, organisational changes, market shifts) can undermine performance, creating financial exposure without corresponding control. This imbalance may necessitate complex contract provisions that reintroduce the very complexity Progency aims to eliminate.

Practical Business Constraints

Scalability Limitations
The thin services layer, even augmented by AI agents, may face scalability challenges across diverse client requirements. Each client implementation requires customisation and contextual understanding that may resist full automation. As the client base grows, maintaining quality while expanding AI agent capabilities across different industries and use cases presents substantial technical and operational challenges.

Vertical Expertise Requirements
Effective implementation demands deep industry-specific knowledge that most horizontal SaaS providers lack. Building this expertise across multiple verticals requires significant investment and time, potentially limiting Progency’s applicability to specific industries or use cases in the near term.

Strategic Risks

Competitive Positioning Challenges
Progency represents a hybrid model between pure SaaS and consulting services. This creates potential competitive disadvantages against both specialised SaaS providers (with lower operational costs) and established consultancies (with deeper domain expertise). Finding the optimal positioning in this landscape may prove challenging.

Client Dependency Concerns
The success-based model could inadvertently create unhealthy dependencies on specific clients. If a disproportionate share of revenue comes from a few high-performing implementations, the Progency provider becomes vulnerable to client leverage or loss.

Organisational Resistance
Established SaaS companies with traditional subscription-based models may face significant internal resistance to adopting such a radical shift. The transition requires not just technological changes but fundamental cultural and mindset shifts across the organisation.

Technological Limitations

AI Capability Reality Check
Your model heavily relies on AI agents reaching a sophistication level that may be further away than anticipated. While AI capabilities are advancing rapidly, fully autonomous agent systems capable of replacing human expertise across complex business functions remain largely theoretical. Over-promising and under-delivering on AI capabilities could undermine client trust in the entire model.

Integration Complexity
The seamless operation of AI agents requires robust integration with client systems. Legacy infrastructure, data quality issues, and API limitations could significantly constrain effectiveness, particularly in enterprises with complex technology landscapes.

Ethical and Regulatory Considerations

AI Governance and Oversight
As autonomous AI agents take on more critical workflows, questions of accountability and liability become increasingly important. Who bears responsibility for AI errors? A comprehensive governance framework would be essential to maintain trust and transparency.

Compliance Challenges
Industry-specific regulations (GDPR, HIPAA, financial services requirements) add layers of complexity to AI agent deployment. Each vertical may require specialised compliance approaches, further complicating scalability.

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Conclusion: Promising but Nuanced

The Progency model presents a genuinely innovative vision for SaaS evolution, addressing fundamental limitations in the current subscription paradigm. However, its successful implementation will require careful navigation of the challenges outlined above.

A more measured approach might involve:

1. Hybrid Models: Combining baseline subscription fees with performance-based upside to balance cash flow needs while maintaining outcome alignment
2. Controlled Scaling: Starting with specific vertical markets where outcomes are more easily measured and attributed
3. Phased AI Integration: Gradually introducing AI agents alongside human expertise rather than assuming immediate wholesale replacement
4. Selective Client Partnerships: Initially targeting clients with modern tech stacks and collaborative mindsets to establish proof points