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
minimalist phone: reduce your screentime
I even think that "agentic" or having "agent" is already standard, almost gone, and people will be seeking new ways to come up with any other "breakthrough" we do not know about yet.
ProdShort
@busmark_w_nika We will see where it goes.. we will probably need to adapt really fast and try to be early on the next « AI wave » 🏄♂️
minimalist phone: reduce your screentime
@amraniyasser I am pretty curious how things fold out, e.g. with energy supplies or that thing with data centres and development projects because of them. Our Earth's resources (not all of them) are renewable. We mostly think only about the short-term profit.
What matters is whether the agent owns an outcome or just adds a chat box. Most 'AI agent' relaunches are still assistive: they suggest, you execute. It gets real when an agent takes a defined job, does it end-to-end, and gets judged on the result. Once you hand a task and pay for finished work, 'agent' stops being a label and becomes a worker. Most products are not there yet.
I agree. Agents are useful only when there's a pressing need. I think most people still confuse an agent with automation and a simple chatbot with generative AI. They're used interchangeably and some agents seem unnecessary. Although only time can tell if all SaaS development will go 100% agentic.
I really like the distinction here between assistant, automation, and true agents. A lot of companies are rushing to “add AI agents” because it’s the trend, but the real value comes from understanding where autonomy actually improves the workflow instead of adding complexity.
The Cisco example is impressive, but I think the bigger shift is the change in responsibility: AI is moving from generating code to owning parts of execution and validation. That changes how teams design products, review processes, and even engineering roles.
The test I like is: what happens when the agent is wrong? If the product has a clear source of truth, a narrow action boundary, and an approval/reversal path, agent behavior can be useful. If not, “agent” usually just means a chatbot with more ways to make a mess.
For writing and GTM workflows, I’d be especially careful. An assistant can help shape drafts, summarize calls, or suggest next steps. But the moment it starts publishing, changing positioning, or updating customer records, it needs provenance and review built in from the start.
autonomous coding agents is the right direction of the future but we are far from that. anyone spending thousands a month in codex API knows that task drift, context bloat, blind retries, infinite looping, sub agent wastage, etc. is all real and it still needs human in the loop. We've experienced this first hand. Maybe if you have unlimited token budgets, you can get away with it, but eventually your CFOs gonna start asking for ROI on token spend.
Firing engineers you pay $150K for and then spending $200K in tokens to do the same work in a way that is reliable, consistent, and PRD ready is the problem at an enterprise level.
Gartner is way behind.....anytime these major companies finally release a report, at the speed AI moves, they're already behind where the market is and where its heading.
any one building real agents and agentic workflows, knows you can't just call any tool you create an agent, doesn't work like that.
its not full agent until it can do autonomous work, self improve, self heal, consistent memory, and act like a managed worker, until then its a just a tool or assistant imo and i say this as someone who ships product and built 5 startups.
What matters is whether the agent owns an outcome or just adds a chat box. Most 'AI agent' relaunches are still assistive: they suggest, you execute. It gets real when an agent takes a defined job, does it end to end, and gets judged on the result. Once you hand it a task and pay for finished work, 'agent' stops being a label and becomes a worker. Most products are not there yet.
Mailwarm
There's a lot of agent hype as if the agent is going to bring you coffee and croissants in the morning, too. But it's very useful to either have an agent-assistant who knows how to write and edit text and decks with you, or a proper agent checking stats, managing bids on ads, calling out sites that are down, or taking notes for you.