Most human-in-the-loop AI checks fail for one of three reasons: the reviewer lacks context, lacks authority, or stops paying attention once the AI is right often enough. That third failure, automation bias, is the one most governance conversations skip, and it turns a real safeguard into a rubber stamp. At the CIO 100 Conference, Doug […]
Your Human in the Loop Might Just Be a Rubber Stamp Read More »
Every custom agent harness makes assumptions about what the model can and can’t do on its own. Those assumptions go stale as the model improves. An earlier version of Claude would wrap up tasks prematurely as its context window filled, a behavior sometimes called context anxiety. Teams built context resets into their harness to compensate.
Inside Claude Managed Agents: Architecture, Primitives, and Cost Tradeoffs Read More »
A finance team recently automated its monthly close process after losing its controller. A sales team built an agent that takes a company name and a contact, researches the account, and generates a ready-to-send outreach asset. A marketing team cut the cost of building a client-ready slide deck from $30 to $50 down to under
Claude Managed Agents: What They Are & When to Use Them Read More »
TL;DR: When our controller gave notice, we automated our own month-end close process in six weeks. A governed AI system now prepares about 80% of each close, payroll reconciliation dropped from two days to two hours, and we save $100,000 a year. The AI never posts a journal entry. A person reviews and posts every
How AnswerRocket Cut Its Own Month-End Close Process by 80% Read More »
This is Part 1 of my series on the 7-Layer Agentic AI Framework. This post covers the Perception Layer, how agents transform raw inputs into structured intelligence before any reasoning happens. Part 2 covers the Semantic Layer, which picks up right where perception leaves off: perception handles what the agent sees; the semantic layer governs
The Perception Layer: Why Your AI Agent Needs to See Before It Can Think Read More »
The AI landscape is evolving faster than most enterprises can adapt. We asked our leadership team for their predictions on where AI is heading in 2026. Here’s what they had to say. 1. Multimedia Creation Will Flawlessly Mimic Real Artists and People Video, music, and image generation will take another massive leap forward in 2026.
The conversation around AI agents has reached a fever pitch. Every enterprise leader we talk to wants to know: How do we actually do this? How do we move from proof-of-concept demos to agents that get real work done? We recently sat down with our AI Business Transformation team: Nicole Kosky, who leads the practice,
What It Really Takes to Get an AI Agent Up and Running Read More »
OpenAI’s recent Dev Day made waves with the announcement of Apps SDK and AgentKit, tools designed to make building AI agents more accessible than ever. But beyond the flashy demos and 800 million daily users milestone, what does this really mean for enterprise leaders navigating the AI landscape? Our team weighed in on the latest
Beyond the Hype: 5 Key Insights from OpenAI’s Dev Day Read More »
Co-authored by Stew Chisam, Operating Partner, StellarIQ After extensive hands-on testing with Replit Agent 3, we can tell you it represents a meaningful step forward in AI-assisted development. But not for the reasons you might expect, and not without significant limitations you need to understand before adopting it. What Is Replit Agent 3? Replit Agent
Welcome to Episode 5 of AI, Actually. This week features Pete Reilly as our moderator, joined by Alon Goren (CEO and co-founder), Shanti Greene (Head of Data Science and AI Innovation at AnswerRocket), and Stew Chisam (Operating Partner at StellarIQ). This episode tackles three major themes shaping enterprise AI today. First, we dive into Sequoia’s
The Evolution of AI Interaction As artificial intelligence continues to revolutionize enterprise operations, three key protocols have emerged to standardize how AI systems communicate and collaborate: Model Context Protocol (MCP), Agent-to-Agent Protocol (A2A), and Agent Communication Protocol (ACP). These protocols represent a significant evolution beyond earlier approaches and offer new possibilities for enterprise AI integration.
Understanding AI Agent Protocols: MCP, A2A, and ACP Explained Read More »
The AI landscape is changing faster than most businesses can keep up. You’ve probably heard three terms used almost interchangeably: Generative AI (GenAI), Agentic AI, and Artificial General Intelligence (AGI). They represent fundamentally different approaches with vastly different capabilities. So what sets them apart, and why does the agentic AI vs. AGI distinction matter for
Generative AI vs. Agentic AI vs. Artificial General Intelligence: What’s the Difference? Read More »
Our leadership team shares their collective vision for how autonomous agents and enterprise AI will reshape business in 2025. The Dawn of True Agentic AI A transformative shift in enterprise AI agents is underway. While many companies currently label their solutions as “agentic,” 2025 marks the emergence of truly autonomous AI agents with genuine agency.
How Agentic AI Will Transform Enterprises in 2025 Read More »
Strategic acquisition adds deep data science capabilities to AnswerRocket’s AI consulting services ATLANTA, GA – April 22, 2025 – AnswerRocket, a pioneer in enterprise AI solutions since 2013, today announced the acquisition of Cognitive Spark, a management consulting firm that specializes in developing advanced data science and machine learning algorithms for enterprises. Cognitive Spark’s team
Max AI is your enterprise AI agent platform, allowing users to build agents that deliver business results. Max AI supports the complete agent development lifecycle: …And More! Ready to Transform Your Enterprise AI Agents?
