Agentic Software: Redefining AI, Product, and Value Delivery

In the rapidly evolving tech landscape, artificial intelligence (AI) is reshaping how products are built, evaluated, and deployed. From personalized customer interactions to intelligent automation, agentic software introduces a new paradigm where virtual coworkers autonomously act on our behalf. This article explores the critical elements of AI evaluation, the challenges and solutions in scaling data-driven assessments, and the evolving role of product management in this transformative domain.

The Fundamentals of Evaluating AI

Evaluations—or "evals"—are the cornerstone of understanding AI performance, revealing both strengths and areas for improvement. Effective evaluations transcend traditional benchmarks, delving into real-world nuances. For customer experience (CX) agents, this means assessments akin to performance reviews—measuring not only accuracy but the ability to exceed human expectations with proactive, empathetic support.

Scaling such evaluations poses significant challenges. From analyzing vast datasets to interpreting user interactions, personalization becomes vital. Tailored feedback yields deeper insights but necessitates rethinking established evaluation frameworks.

A successful evaluation balances two critical metrics: accuracy and user resonance. While accurate results matter, the true value lies in measuring what is most helpful and impactful to users. This shift from “getting it right” to “delivering value” defines the next wave of evaluation paradigms.

Rethinking AI Evaluations

AI evals must evolve into flexible, dynamic assessments that capture subtlety, behavior, and empathy. This shift demands close collaboration between product managers (PMs), database architects, and technologists, emphasizing guardrails to ensure AI outputs remain reliable and aligned with user expectations.

Modern PMs must master the art of designing and iterating evaluations. Prototyping plays a pivotal role—testing and refining models to adapt to ever-changing requirements. Tools like Claude offer advanced nuance and empathy, challenging PMs to align evals with metrics that measure intelligence, emotional connection, and usefulness.

Prototyping in High-Performance Teams

Innovation thrives in environments with high talent density and strong alignment. Exceptional PMs remove obstacles, facilitate collaboration, and create quick feedback loops. In agentic AI, prototyping extends beyond building systems—it involves understanding the mission, crafting solutions that anticipate problems, and driving outcomes that align with user needs.

Agentic software goes beyond solving problems; it predicts them. Features like automated recaps, meeting summaries, and asynchronous communication redefine productivity. By transforming AI into an active participant in workflows, agentic software embodies nuanced reasoning and proactive support—fundamentally altering how we approach work.

The Economics of Agentic Software

Agentic software is reshaping business models by redefining how value is delivered and monetized. Companies are transitioning to hybrid pricing models that combine seat-based fees with usage-based metrics. This approach better aligns costs with the actual value AI provides.

Enterprise clients increasingly demand demonstrable ROI. Longer sales cycles and higher expectations require companies to refine their Ideal Customer Profiles (ICP) and target mid-market and enterprise sectors. Pricing strategies must reflect outcomes delivered—if an AI agent saves $10 million, the cost should scale proportionally.

Data-driven methods, such as Monte Carlo simulations, help businesses model and optimize these pricing strategies. Blending outcome-based charges with ROI-sharing ensures AI solutions remain cost-effective and lucrative for both providers and clients.

The Rise of Agentic Platforms

AI agents are evolving from tools into indispensable team members. Much like websites became a necessity for businesses, personalized AI agents will soon be ubiquitous. These agents will handle CX, data analysis, and automation at scale—streamlining onboarding, document processing, and even integrating with legacy systems.

Platforms like ResponseCX and StateSet’s suite exemplify this shift, delivering agentic outcomes through automation, onboarding assistance, and proactive recaps. By integrating computing with empathy, these systems set the standard for competitive businesses.

Building the Future of Agentic Software

To succeed, companies must start small but think big. Initial traction with SMBs can provide the foundation for enterprise expansion. Go-to-market strategies should leverage partnerships, co-marketing, and ecosystem integrations to create a flywheel effect where early adopters drive awareness and growth.

The foundation of any agentic software platform is mission alignment and a focus on key talent. The best PMs drive product development with a clear vision, ensuring intelligence, speed, and cost efficiency. By leveraging analytics, companies can refine offerings, enhance user engagement, and solidify their competitive edge.

Conclusion: The Future of Work, Enhanced by Agentic Software

Agentic software is transforming how we work, delivering personalized, proactive outcomes that redefine productivity. The keys to success lie in innovative evaluations, strategic pricing models, and relentless prototyping. As businesses move toward this future, the question isn’t just about automation—it’s about creating AI agents that empower us to work smarter and interact more meaningfully.

Are we ready to embrace this evolution? With talent, innovation, and a commitment to user-centric design, the answer is a resounding yes. The future of AI isn’t just about tasks—it’s about delivering outcomes that elevate human potential.