Is every product suddenly becoming an “AI agent”?
I was reading this recent @OpenAI article about Gartner naming OpenAI a Leader in enterprise AI coding agents: https://openai.com/index/gartner-2026-agentic-coding-leader/.
"Software development is becoming more agentic." This is a good summary of what is happening right now. We are moving from AI that helps you write faster, to AI that can take over tasks (actions, use tools, make changes, run tests, and bring the work back for human review). That is a very different behavior.
The article gives Cisco as an example. They used Codex for a big part of their AI Defense platform and reduced delivery time from several quarters to a few weeks.
The AI agent trend is real. But I also think this is where many products will get it wrong. Not every workflow needs an agent. Some tasks need a simple assistant. Some need automation. Some need a dashboard. And some actually need an agent that can act, check, and ask for approval.
The real question is not “How do we add agents everywhere?” It’s:
Where does an agent actually make sense?
Have you already turned part of your product into an AI agent?
Are you still figuring out if you need one?
Replies
I think the real disruption isn’t agents replacing apps. It’s agents replacing interfaces. For decades humans adapted to software. Agentic systems are the first serious attempt at software adapting to humans. Which sounds amazing until you realise humans are inconsistent, emotional, ambiguous, and constantly changing their minds 😄
So the real competitive advantage may not be intelligence. It may be reliability under messy human behaviour.
Yeah, this is my frustration too. I've been testing a ton of new stuff lately and the pattern is always the same: take an existing workflow, slap "AI agent" on it, rewrite the landing page. Nothing actually changed underneath.
The ones that actually work are the ones where the agent removes a decision or a step. If it just adds a chatbot to something that worked fine as a button, it's not an agent—it's a marketing rebrand.
Has anyone here found a product that genuinely got better after going from regular tool to AI agent? Curious what that looks like.
A lot of the rebranding is pricing-driven, not architecture-driven. "Agent" commands a higher price point and a better investor narrative than "automation" or "assistant." Until you’re measured on the outcome — not just the activity — it’s still just a chatbot with ambition.
I am so glad you're starting this discussion. I asked myself that when I started building my app. I love the concept of AI helping us do things we otherwise can't, but we should spend more time thinking about when and how to use AI, especially since the full scope of the job and environmental impacts are unknown.
I think a lot of companies are calling things "agents" that are really just workflows with better marketing. An actual agent should be able to make decisions, use tools, handle exceptions, and complete a task with minimal guidance. Otherwise it's probably just automation with a new label.
The distinction I find useful: is the AI actually making decisions with downstream consequences, or is it just a better search bar with a chat interface?
Most things launched as "agents" right now are the latter — which isn't bad, it's often genuinely useful. But calling it an agent sets expectations that lead to disappointed users when it can't chain tasks without hand-holding.
This is a strong space. The speed improvement from AI coding agents is obvious now. The harder question is what happens after the code works.
Can the team understand it?
Can another developer maintain it?
Are the security assumptions clear?
Are access controls and data flows visible?
Can the founder explain the technical decisions later?
For me, the next step in AI coding is not just faster generation. It is better proof around what was built, why it was built that way, and where human review still matters.
The useful distinction for me is whether the agent owns a real workflow or just gives the product a more fashionable interface.
“Agent” makes sense when it can observe context, decide the next step, ask for missing info, and route or act. Otherwise a button, form, search box, or automation is probably better.
I’m applying that lens to AnveVoice now. Voice only seems defensible when the visitor has intent and the alternative is friction: form, chat queue, missed call, or bounce.
For me it's fewer agents, better placed. The simple test:
Needs a faster draft → that's an assistant, not an agent.
Deterministic, same steps every time → that's automation.
Just needs to surface data → that's a dashboard.
Needs to act, check its own work, and ask a human when it's unsure → that's the one that actually earns being an agent.
Slap an agent on all four and you get something impressive in a demo that nobody trusts in production. Pick the one workflow that genuinely needs to act under oversight, ship that, and leave the rest as assistants or automation.
It's funny but true that for companies with complex systems or workflows you might actually need an agent or fleet of agents to constantly analyse your workflows to identify great candidates for agentic workflows.
Whatever the case, you'd rather err on the side of automating processes with agents and then remove them if redundant to not doing it at all in a world agents are completing tasks that needed an army of top engineers working for 3 months straight in 20minutes.