Agentic AI for Supply Chain Intelligence. LinkedIn- A2go
Sarasota, FL
Joined March 2018
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The Harness Behind Agentic Learning a2go.substack.com/p/the-harn…
#decisionintelligence #supplychain #agenticai @governedai
Why AI Agents Fail to Deliver Supply Chain Results supplychainbrain.com/blogs/1…
The Ontology of Execution
The next advantage in enterprise operations will not come from more dashboards, more models, or more data. It will come from building systems that turn business intent into coordinated action. Modern enterprises already see more than ever. The harder challenge is acting on what they see with speed, consistency, and control.
That is why the next chapter of enterprise AI is not really about intelligence alone. It is about execution. And execution depends on structure. More specifically, it depends on ontology: the living map of how people, decisions, ownership, workflows, systems, and outcomes connect across the business.
Without that ontology, even sophisticated AI remains disconnected from the operating model. It can generate answers, summarize trends, and surface recommendations, but it cannot reliably determine who should act, which workflow should start, what policies apply, or how success should be measured. The result is familiar across industries: strong visibility, fragmented action, and a widening gap between insight and outcome.
Enterprise agents matter because they can help close that gap. But only when they are built on top of a clear ontology of execution.
Mike Romeri, CEO, A2go.ai
Full text at link below. #supplychainai #decisionintelligence #manufacturing #agenticai
a2go.ai/the-ontology-of-exec…
Non-disruptive Agentic AI for supply chain decision intelligence. ien.com/home/video/22966154/…
The Ontology of Execution
The next advantage in enterprise operations will not come from more dashboards, more models, or more data. It will come from building systems that turn business intent into coordinated action. Modern enterprises already see more than ever. The harder challenge is acting on what they see with speed, consistency, and control.
That is why the next chapter of enterprise AI is not really about intelligence alone. It is about execution. And execution depends on structure. More specifically, it depends on ontology: the living map of how people, decisions, ownership, workflows, systems, and outcomes connect across the business.
Without that ontology, even sophisticated AI remains disconnected from the operating model. It can generate answers, summarize trends, and surface recommendations, but it cannot reliably determine who should act, which workflow should start, what policies apply, or how success should be measured. The result is familiar across industries: strong visibility, fragmented action, and a widening gap between insight and outcome.
Enterprise agents matter because they can help close that gap. But only when they are built on top of a clear ontology of execution. Read the full article here:
a2go.ai/the-ontology-of-exec…
What 250 Years of American Reinvention Ask of the Supply Chain
open.substack.com/pub/a2go/p…
Check out my latest article: When the Recommendation Is Right but the Clock Keeps Running linkedin.com/pulse/when-reco… via @LinkedIn
Supply chains generate thousands of insights a day. Most of those decisions still come down to manual review and one person's judgment.
That gap — not the models — is where operational AI earns its place. Mike Romeri on what's emerging:
ibtimes.com/how-operational-…
Webinar with @Samguptausa and the CEO of A2go.ai, Mike Romeri. Sam showcasing for his audience how agentic AI can work with any ERP and planning systems to deliver decision intelligence to any supply chain. No rip out and replacing of systems and long implementation cycles. Mark Bates from Taco Comfort brought his A2go use case to light during the webinar.
linkedin.com/posts/betsy-mcc…
A2go retweeted
This is EVERYTHING you need to know about building a Company Brain in 28min.
From connecting all your tools into one intelligence layer to the new org chart around it.
This is the new way to work in the AI era.
Here's the full breakdown:
00:00 Introduction & AI Adoption
01:45 The Four Levels of AI Maturity
02:30 The Single Brain Concept
05:30 Building an AI-Powered Org
07:20 Specialist Agents & Agent Fleets
11:20 Workflows & Closed Loops
14:30 Real Agent Examples in Slack
18:00 AI ROI & Token Economics
20:45 Business-to-Agent Commerce
24:10 Action Steps & Future of Work
A2go retweeted
🚨 Jensen Huang, CEO of Nvidia:
"Every engineer is going to have and manage hundreds of agents."
The most valuable engineering skill of 2026 is not taught in any university.
No CS program teaches harness engineering.
No bootcamp teaches agent memory architecture.
No degree prepares you to build systems that survive production.
One builder mapped the entire thing out — free, step by step, no degree required.
This is the roadmap ↓
Bookmark this for the weekend.
A2go retweeted
Creator of Claude Code:
"At Anthropic, almost 100% of our engineers are running 100+ agents with self-improving loops
self-improving loops help agents become better with each run."
in a 1-hour podcast, Boris explains how they build agents loops from sratch.
Claude + loops + routines + dynamic workflows - that’s the secret.
Watch the talk, then read how to apply the same playbook to quant trading below.
Sundar may be referring to LLMs, GenAI type agents but perhaps he is speaking to industry specific agents such as in supply chain and others. He is correct in both cases but it is being done LIVE at manufacturers now pulling together their disperate systems and data into one agentic AI layer to give them decision intelligence. Give them action. No more dashboards with all the insights you can buy. Now with connected, orchestrated agents, you get real time decision intelligence that allows either automated actions or human approved action. It is here. See A2go.ai
Google CEO, Sundar Pichai:
"If you don't learn to how to orchestrate agents now, you'll spend 2027 catching up to people who started today"
In 30 minutes he explains why the best engineers stopped writing code and started building agents.
Most people think building an agent requires an engineering degree.
It doesn't. It requires one guide and one afternoon.
Watch the interview, then save the exact setup below 👇
Agentic AI Isn’t Replacing the Digital Twin — But It Doesn’t Need One linkedin.com/pulse/agentic-a… via @LinkedIn
Where Agentic AI Actually Earns Its Keep: Closing the Supply Chain Execution Gap aijourn.com/where-agentic-ai…
Every ERP modernization conversation right now ends in the same question: where do AI agents actually fit? Bolted onto the ERP roadmap? A separate platform? An overlay? And how do you get value in quarters, not years?
This webinar cuts through the noise for executives evaluating AI on top of Epicor and other supply chain ERPs. We'll unpack the "decision execution gap" — why even strong ERPs leave hours and days between insight and action — and walk through how agentic AI closes it without rip-and-replace. You'll leave with a clearer framework for what to build, what to buy, and what to expect from your team and your stack over the next 12 months.
Reserve Your Spot: elevatiq.com/events-and-webi…
#Databricks #OTIF #DemandForecasting #InventoryOptimization #CIO #COO #CSCO #CDO #SupplyChainLeaders
