Attercop

AI Threads

Explore our latest thinking on AI agents, knowledge graphs, and the future of software.

Practical insights and real‑world strategies to help you unlock AI's full potential.

Written by our team of expert data scientists and AI specialists.

AI Opportunity vs AI Liability: What Investors Need to Know
AI&DataBusiness&Finance

AI Opportunity vs AI Liability: What Investors Need to Know

Why the real value in AI isn't efficiency, but the ability to prove safety, fairness, and compliance.

Sarah Clarke | AI Governance Specialist, Attercop
Why define your AI strategy?
AI Strategy

Why define your AI strategy?

How strategy, governance, and a clear roadmap turn AI risk into opportunity.

Graeme Cox | CEO, Attercop
GPT 5: Here’s why product velocity now beats raw model gains
GPT5Generative AI

GPT 5: Here’s why product velocity now beats raw model gains

Also - is it any good?!

Graeme Cox | CEO, Attercop
Agentic Patterns for Enterprise Deployment: From Autopilot to Automated Fleet
AI AgentsAI Architecture

Agentic Patterns for Enterprise Deployment: From Autopilot to Automated Fleet

How Enterprises Can Scale from Co-Pilots to Fully Autonomous AI Agents

Graeme Cox | CEO, Attercop
AI Agents: Understanding the Next Wave
Agent InfrastructureAI Agents

AI Agents: Understanding the Next Wave

Cutting through the hype to explain what AI agents actually are—and why integration is the real game-changer.

Graeme Cox
Why Does Gartner Consider Graphs a 'Critical Enabler' Right Now?
Knowledge GraphsAI&Tech

Why Does Gartner Consider Graphs a 'Critical Enabler' Right Now?

In this issue of AI Threads, we examine how knowledge graphs complement large language models - and why combining structure with reasoning could be essential to the future of intelligent systems.

Attercop Team
The Future of AI Training: Scaling Smarter, Not Bigger
AI InfrastructureAI&Tech

The Future of AI Training: Scaling Smarter, Not Bigger

Welcome to the first issue of AI Threads, where we take a closer look at how AI is built, trained, and scaled—and whether the way we’re doing it now is really the best approach.

Attercop Team

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