Tag: Agentic AI Roadmap
-
Agentic AI SDLC: From Prompted to Autonomous, Step-by-Step Guide
If you run software programs for a living, you already know the shape of what is coming: a maturity ladder, gates between rungs, a sign-off before the next rung is funded. That instinct is right. What changes with agentic AI is what the gates are made of. A traditional gate was a meeting, a sign-off,…
-
Agentic AI Model Never Decides the Outcome. The Controls Do.
The best agentic AI case studies I have published in the last year share one finding, and it is not about models. Across ten posts covering more than sixty enterprise agentic AI deployments, not one outcome, good or bad, was decided by which model the company picked. Every one was decided by what the agent…
-
The AI-Native SDLC Playbook, Staged on the Five-Stage Agentic AI Roadmap
What an AI-Native SDLC Roadmap Sequences An AI-native SDLC roadmap is the order in which an enterprise adopts the plays of an AI-native software development lifecycle — intent files, plan mode, hooks, agentic code review, continuous evals, self-closing maintenance loops — so that each play arrives only after the controls it depends on already exist.…
-
Agentic AI Governance: Managing the Harness Across the Five-Stage Roadmap
What Agentic AI Governance Actually Governs Agentic AI governance is the discipline of controlling what an AI agent is allowed to do, verifying what it actually did, and proving both to an auditor — and in 2026 the object of that governance is no longer the model. It is the harness. The industry has converged…
-
Anthropic’s AI-Native SDLC Playbook, Mapped to My Agentic AI Playbook
The AI-native SDLC is a rebuilt software development lifecycle in which AI is embedded at every stage — plan, design, build, test, deploy, maintain — and each stage ends by committing a version-controlled artifact that the next stage reads. That chain of artifacts, from intent.md through the spec, the plan, the diff and the incident…
-
The Governance Gap in Agentic AI
Bill Gates published a roughly 6,000-word essay this week arguing that even under the best circumstances, the transition to the AI era will be one of the most turbulent periods in human history — and that there is no plan for the social, political, and economic upheaval it will cause. His framing is binary: AI…
-
Enterprise Agentic AI Vision 2030
Enterprise agentic AI is not arriving in a straight line. It’s a J-curve: a rough two years of pilots and cancellations, then a scramble to scale, then — if the forecasts hold — an operating model that looks nothing like the IT services industry of 2025. Most analysts, academics and IT services leaders agree on…
-
Agentic AI Sandbox Isolation: The Control Behind 2026’s AI Escapes
Sandbox isolation is the enforced separation between where an AI agent is allowed to experiment and where production data, other companies’ systems, and the open internet live. In July 2026, two frontier AI labs learned, in public, what happens when that separation is stated in a policy instead of built into the infrastructure. I have…
-
Agentic AI Lesson: Governed Scales, Headcount-First Gets Rolled Back
Agentic AI is software that takes a goal, plans the steps, uses tools and takes action toward an outcome with limited human supervision — not a chatbot that only answers questions. I picked two 2025–2026 banking deployments from public reporting because they ran the same play in the same industry and landed in opposite places.…
-
What Is Agentic AI Technology? A Practitioner’s Field Map of the Enterprise Stack
“Agentic AI technology is the software stack that lets an enterprise hand a system an outcome to achieve rather than a script to execute” © Dr. Harish Kotadia, 2026 — the model, memory, tools, identity, guardrails, and observability that turn a goal into governed, auditable action. Instructions in, results out — that was IT. Intent…