The Mission
Agent Experience Management.
We're pioneering the discipline of designing, measuring, and managing how AI agents work — across every touchpoint in your organization.
Just as Customer Experience (CX) became essential for managing human interactions, Agent Experience (AX) is essential for managing AI interactions. Maxism provides the framework, the metrics, and the infrastructure.
The Reckoning
The Year of the Agent Became the Year of Math
2025 was heralded as "The Year of the AI Agent." Autonomous agents would book hotels, manage workflows, transform how we work.
Reality delivered something else.
The math doesn't work. Even with 95% reliability per step, a 20-step workflow succeeds only 36% of the time. Production systems require 99.9%+. This isn't a bug to fix — it's compounding probability. An agent planning a trip suggested a stop in the middle of the Gulf of Mexico. Advanced models still hallucinate at ~10% rates.
The economics don't work. Long conversational contexts scale quadratically in cost. Some agent sessions cost hundreds of dollars in API fees. Successful implementations are pushing toward stateless, bounded tools — the opposite of the "autonomous agent" vision.
The security doesn't work. Q4 2025 saw attackers exploiting agent capabilities — web browsing, tool calling — to conduct indirect attacks more effective than traditional prompt injections. As agents become more capable, they expand the attack surface.
The industry is recalibrating. Sam Altman has de-emphasized agent development, shifting focus back to core chatbot capabilities. Experts now describe this as the "Decade of the Agent" rather than the year. Most enterprise projects remain stuck in pilot stages.
This isn't the trough of disillusionment. This is an existential reckoning — the moment when the industry confronts a hard truth: AI agents built on hope don't work.
Whitepaper
AI in the Trough of Existential Crisis
Why most will fail and how a few will win. The mathematical limits of LLMs, the BS optimization loop, and what separates aqueduct-builders from those pouring water into the ground.
What We Recognize
The industry keeps promising bigger models will fix the problem. They won't.
AI cognition operates on fundamentally different principles than human cognition. The failures aren't bugs — they're architectural features. You can't scale your way out of compounding probability.
But here's what we also recognize: These limitations aren't fatal. They're designable.
The same data shows where agents succeed: bounded workflows, human oversight, rollback mechanisms. Code generation, refactoring, CI/CD automation — tasks with clear constraints and verifiable outputs.
The question isn't whether AI is powerful. The question is whether you have the infrastructure to channel that power reliably.
The Maxism Approach
Engineering Reliability Through Agent Experience
We don't make AI smarter. We make it systematically reliable.
Agent Experience Management (AXM) is built on three principles:
1. Design for AI Cognition
Quest Blueprints structure agent work around how AI actually thinks — not how we wish it would. Small contexts. Clear boundaries. Verifiable outputs. Bounded workflows that work with compounding probability, not against it.
2. Measure What Matters
AXIS scoring provides universal metrics from individual actions to C-Suite dashboards. The "NPS of AI" — finally giving organizations visibility into where agents succeed and where they fail.
3. Manage the Full Value Chain
From customer-facing agents to internal automation to autonomous processes — one framework for the entire agent experience. Zero-trust verification at every gate. Human oversight where it matters.
Why Now
The industry is recalibrating. The hype is fading. The hard work of building reliable systems is beginning.
This is exactly when new paradigms emerge.
The companies that get agent experience right will capture the value. Those who keep chasing autonomous fantasies will keep failing. Those who wait will be retrofitting reliability into systems designed without it.