Generation Gets the Demo
The most valuable use of AI isn't generating new code. It's understanding the legacy systems your business already runs on. Why comprehension beats generation.
Tag: AI Adoption
11 articles tagged with "AI Adoption"
Your Agent Pipeline Isn't a Pipeline
Platforms made it easy to build a first agent. Nobody has solved how to run one in production with the same discipline we apply to software.
Your AI Strategy Is Only as Strong as Your Inventory
You can't govern, defend, or prove value from AI systems you can't account for. Why inventory is the first place enterprise AI governance gets real.
Who Owns the Outcome? Governing the Age of AI Sprawl
AI agent sprawl is outpacing enterprise governance. Here's why that's a leadership problem — and what the governance stack actually needs to look like.
AI Questions Every Leader Should Be Asking
Most AI initiatives fail not because the technology is immature, but because leaders never asked the right questions. Ten worth asking now.
From Prototype to Platform: The Reality of Scaling Agentic AI
Agentic AI demos are impressive. But turning them into reliable, sustainable enterprise systems takes more than a prompt and agent builder
Part 3 — Edge AI in the Developer’s Workflow
Edge AI is moving from IoT devices to developer laptops. Running models locally eliminates latency, outage risk, and cloud costs in day-to-day coding.
A Second Set of Eyes: How AI Is Quietly Crowdsourcing Our Workflows
AI’s biggest near-term value isn’t automation — it’s acting as a second set of eyes. How personal crowdsourcing is quietly reshaping how we work.
Who’s Actually Building AI Agents?
Building AI agents for production takes far more than good prompts. Real agent systems need tools, memory, error handling, and organizational trust.
Why Enterprise Survival Depends on a Context Driven Approach to Data
Enterprises invest heavily in big data and AI but struggle with ROI because most data is inaccessible. A context-driven approach unlocks the value of dark data.
Progressing the Digital Worker with Context
Most organizational data is dark and inaccessible. Enriching captured data with business context is the key to enabling digital workers and automation.