Nobody Knows How to Deploy This Thing
Everyone's talking about AI agents. Almost nobody has actually changed how they work.
Real John here - Queen of Hearts today… loving the Theory11 Voyager deck for those curious. Anyway, I had off yesterday which means I was playing Street Fighter and playing with AI stuff. I do love 3 day weekends, especially after the Knicks parade (go KNICKS!).
I talk about agent stuff today, but there is one thing that I want to also talk about… Fable being pulled. Why? Because they refused to remove the jailbreak bug. But the real reason is probably because they don’t know how to stop it. A quick intro before I get into this week’s newsletter. AI LLMs cannot be blocked by guard rails in a markdown file. AI is just as susceptible to social engineering as much as we are. Remember it was all trained on human data, so human flaws exist in its OWN system. If you are worried about privacy, security, or blah, blah, blah. Stop using the internet, wifi especially, and never touch AI. You carry a digital tracking device with you 24 hours a day, you login to multiple systems a day using the same account, you tell a chat company secrets and it promises it is being private. If an AI said it would sell you swamp land or a bridge, you probably would buy it. Be human, trust but verify. Don’t think your data is not being used.
Ok, that part of the rant is over… Let’s get into the latest buzzword Agentic AI and how people are claiming they are AI forward and don’t even know what that means (probably because they didn’t write the script, the AI did it for them, c’mon people, be better). Ok, let’s get into it.
I’ve been in software for 30+ years. I’ve survived the Java EE era. I sat through Agile transformations that were just scrum ceremonies with a new logo. I watched companies “go cloud” by lifting and shifting their on-prem disasters into AWS and calling it digital transformation.
And now I’m watching it happen again. Same movie. Different buzzword.
Agentic AI.
Every conference talk, every LinkedIn post, every VC pitch deck in June 2026 has the word “agentic” in it. AI that doesn’t just answer questions — it does things. It browses, clicks, writes code, sends emails, manages tasks end to end. Autonomous. Proactive. A whole new paradigm.
Cool. So why does every team I talk to still have a human copying the AI’s output into a spreadsheet?
The Gap Nobody Wants to Admit
Here’s what actually happened over the last year: companies went from using AI as a chatbot to buying AI agent tooling. They subscribed to the platforms, they wrote the system prompts, they plugged in the APIs.
And then they dropped the agent into the exact same workflow they had before.
Same approval chains. Same ticket system. Same standup where someone reports what the AI said. Same manager who “reviews the AI output” for three hours a day and wonders why productivity didn’t go up.
You didn’t adopt agentic AI. You gave your old process a robot assistant and called it transformation.
That’s not a technology problem. That’s a thinking problem.
The bottleneck was never the model. It’s that nobody has sat down and asked: “If this agent can actually do the work, what does my job look like now?”
That question is terrifying. So instead, everyone just adds AI to the existing job and wonders why they’re more exhausted than before.
What Deploying Agents Actually Requires
Let me be specific, because vague inspiration isn’t useful.
1. Kill the handoff. If your agent produces output that a human then manually moves somewhere else, you haven’t deployed an agent. You’ve deployed a fancier copy-paste machine. The agent needs to finish the job — (for those wondering, I edit it so it adds those emdashes for formatting, I don’t use emdashes) write to the database, send the message, update the record. If you can’t trust it to do that, figure out why and fix that problem first.
2. Rewrite the job description around the agent, not alongside it. The agent is not a tool you use. It’s a team member with a role. Define its scope. Define what it owns. Define what escalates to a human and why. I did this with Cash Critters — specific AI tasks have specific lanes. When something falls outside that lane, it surfaces to me. Everything inside the lane? It runs.
3. Your review process is now exception handling, not proofreading. If you’re reading every output your agent produces, you haven’t changed anything. You’ve just added a step. Exception-based review means: the agent ships, you see anomalies, you investigate anomalies. Not “let me check everything it did.” That’s not delegation. That’s micromanagement with extra steps.
4. Measure the right thing. Nobody is tracking “hours of work the agent completed autonomously.” They’re tracking the same KPIs they had before, wondering why the numbers look the same. Define what the agent is supposed to own, and measure whether it owns it. Not whether humans are happy with the output. Whether humans aren’t involved in producing it.
5. Ship it broken and fix it. This one stings for people who want a perfect rollout. There is no perfect rollout. I’ve been coding since I was 9 years old on a Commodore 64. You know how I learned what worked? I deleted something, watched it break, and fixed it. Agents are no different. Deploy them into real workflows with real stakes, watch where they fall over, and tighten it up. Waiting for perfect is how you get to 2027 still talking about the potential of agentic AI.
The Hard Truth
The companies winning right now aren’t the ones with the most sophisticated agents. They’re the ones who were willing to blow up their old process to make room for a new one.
That takes courage. It takes a leader willing to say “we don’t need that meeting anymore” and actually cancel it. It takes an engineer willing to let the agent own a thing they used to own. It takes a founder willing to trust the system they built.
Most people aren’t there yet. They want the productivity gains without the organizational change. You can’t have both.
Agentic AI isn’t a tool upgrade. It’s a workflow redesign that happens to involve a very capable tool. Skip the redesign, and you’ve paid for a gym membership you’re not using.
So yes — everybody’s talking about agents. Almost nobody has actually deployed one properly. The gap between those two groups is where the next competitive advantage lives.
Go build the thing. Then get out of its way.
My new favorite quote - “The magic is in the work” - Jalen Brunson (Congrats Captain!)
John Mann is the founder of Startups and Code LLC, a software engineering executive with 30+ years in the industry, and the person who built Cash Critters for $50/month because constraints are a feature, not a bug. Subscribe for weekly takes on AI, startups, and building things that actually ship.