No unified definition for an AI “agent” is leading to customer frustration, as Microsoft, OpenAI, Salesforce, Amazon, Google, and others market it differently
Data Science: 2010-2016 — Machine Learning: 2017-2022 — AI: 2022-2024 — AI Agent: 2025- [embedded post] @neuroemergent : Beep Boop. “You agentic Bro?” — “I agent Bro.” [embedded post] Paul Rietschka / @prietschka : I don't think I've ever seen a more clearly-artificial public relations campaign around a technology that is simultaneously, (1) non-functional, and (2) unwanted. — It's been bizarre watching major cos. try to hype these things, esp. considering there are no clear use cases being targeted. Rumman Chowdhury / @ruchowdh : 🖐️ I call AI Agents “3 APIs in a trench coat” — techcrunch.com/2025/03/14/n... Mastodon: Alex Jimenez / @AlexJimenez@mas.to : In the last few years, the tech industry has boldly proclaimed that #AI “agents” are going to change everything. However, no one seems to agree what an AI Agent might be. — https://techcrunch.com/... #AgenticAI #DigitalTransformation @counternotions@mastodon.social : Senior director of product at Google and an ex-GitHub Copilot leader: “I think that our industry overuses the term ‘agent’ to the point where it is almost nonsensical.” — (Not nonsensical if you define it as “a field Apple's hopelessly fallen behind.") — https://techcrunch.com/... LinkedIn: Yam Marcovitz : The term “agentic”, coming from someone who's been pushing LLMs to their limits in the past couple of years... is soon to be completely outside the realm of engineers and engineering. … Matthias Patzak : So what? — We are still discussing what a microservice is... Or what is DevOps? — 9 out of 10 applicants talk about Kubernetes when I ask them about DevOps. … Eros Marcello : Me in 2015: — So, if these Conversational AI platforms say it learns with use, why are we hand labeling + explicitly programming what these systems say for each specific variation of user input? … Richard Platt : Silicon Valley is bullish on AI agents. OpenAI CEO Sam Altman said agents will “join the workforce” in 2025. … Ashok Govindaraju : One company's AI agent books appointments. Another's can supposedly run entire business functions. The reality? … Forums: r/technology : No one knows what the hell an AI agent is Misk To / Beehaw : No one knows what the hell an AI agent is
Context & Ripple Effects
The agent label had already become a commercialization narrative: agent-focused startups drew funding around the promise of monetizing AI models. This report exposes a foundational weakness in that narrative: buyers cannot reliably compare offerings when the category itself is described differently by each vendor.
Related coverage also frames the gap between product framing and practical value: companies have mainly used agents to pursue efficiency and cost reduction, while constrained AI features can leave users unable to adapt tools to their needs. Clearer product boundaries matter before “agent” becomes a useful procurement category.
First-order effects
- Customers evaluating agent products face inconsistent expectations around capabilities, autonomy, and likely deployment requirements, making vendor comparisons harder.
- Microsoft, OpenAI, Salesforce, Amazon, Google, and other sellers risk having their agent claims judged against incompatible definitions rather than a shared product standard.
Second-order effects
- Buyers are more likely to demand concrete workflow, integration, and oversight details in evaluations, shifting sales conversations away from the “agent” label alone.
- Startups and platform vendors seeking to monetize models through agents must differentiate with demonstrable outcomes, not category terminology—a pressure reinforced by the earlier investment case for agent businesses.
Third-order effects
- If terminology remains fragmented, the market may segment around narrower, task-specific agent products rather than a single interoperable category.
- The durable competitive advantage may shift toward tools that make agent behavior governable and configurable, especially as buyers test whether efficiency claims translate into usable deployments.
The trend: AI is moving from model-led branding toward a buyer-led test of whether agent products have defined capabilities, controllable behavior, and measurable business value.