Are You Retraining for the Agentic Shift or Just Using Tools?
The professional landscape is bifurcating. On one side, enterprise-grade tools like OpenAI’s "Dots" and Google’s September 2026 updates are pushing us toward an agentic future, where software manages multi-step workflows and complex orchestration. On the other, the broader market remains skeptical; consumer adoption is stalled at two percent, and public figures like Pope Francis are questioning whether algorithmic output—often prone to hallucinations that complicate service industry safety—can ever replace human-led intent.
We are seeing a clear divide between those treating AI as a glorified autocomplete and those building systems that act as autonomous agents. While labor activism in tech, as documented by researchers like JS Tan, highlights the friction of these shifts, the technical hurdle is no longer just "prompting." With the release of technical guides for the GPT-6 ecosystem and open-source models like AstaBrief, the barrier to entry for building agentic architectures is dropping. The question is whether you are evolving your skillset to build these autonomous systems or simply layering AI tools over legacy processes.
What we're arguing about
- Are you actively redesigning your professional workflows to delegate multi-step tasks to agents, or are you merely using AI as a faster search engine for your existing tasks?
- Does the shift toward "super intelligence" branding by the White House change how you pitch your AI-integrated projects to stakeholders, or does it feel like disconnected safety theater?
- In your industry, which specific "human-in-the-loop" tasks are now being undermined by AI-driven misinformation, and how are you retraining your team to mitigate these risks?
Share a specific example of a workflow you have successfully delegated to an agent versus one where you refuse to let AI take the wheel.