The Most Important Conversation I Had This Week
How one uncomfortable question forced me to define what we actually build—and why clarity beats hype in the age of AI “everything apps.”
This week, we’re talking:
Why the business question you’ve been avoiding answering is probably the most pressing 💼❓
The power of a NO to cut through AI hype ❌🔪
The magic of Model Context Protocol (MCP) 🪄
Why Agentic AI is still just software 🤖💻
How the White House is attempting to federalize surveillance under the auspices of innovation 🏛️🕵🏼
Why “infinite exponential growth” isn’t a business model 📈💥
How “ghost listings” are haunting jobs data 👻👔
My Take:
The Question I Didn’t Want to Answer
My Co-Founder and Head of Revenue at Kana.ai, Nick, has been hounding me the last few weeks: “What exactly do we offer? Are we selling an agent? An agentic application? What’s the thing?”
I could feel myself getting persnickety. While I appreciate precision and discipline always, Nick’s pestering was starting to feel like an exercise in false precision. Let’s close deals, and stop playing with the dictionary!
Then I had to ask myself: why was I getting so persnickety? When I interrogated my own frustration, I realized the ugly truth: I couldn’t answer the question. And if I couldn’t give Nick a straight answer, how were we supposed to explain it to customers?
The discipline of defining your exact offering tightly is the only way that you survive the bullshit cycle.
Worse, I realized we were becoming part of the problem. We’re at that part of the hype cycle that feels like walking through Central Park and getting approached by the creepy guy in a trench coat trying to sell you the shit he stole from somebody else: “Pssst... you want an agent? A workflow? An application? A portal? A synthetic-data funnel? The same 2000-and-late product we’ve been selling you for the last 15 years, now with a chat interface?”
When everyone claims to do everything, everybody starts to sound like everybody else. And without a clear answer to Nick’s question, I was headed straight into that same muddy pool.
When customers can’t tell you apart from the hundred other vendors claiming to revolutionize everything with AI, they tune out.
The discipline of defining your exact offering tightly is the only way that you survive the bullshit cycle.
The Strategic Power of No
So we tried something different. Instead of claiming we do everything, we started proudly declaring what we DON’T do:
“We do not do AI for creative content generation, and we never will.” “We don’t do AI for marketing copy.” “We don’t optimize your ads—just use Google for that.”
A customer told me: “God, it’s so nice to hear you say that. Everyone says they have everything.”
That’s when I knew we were onto something.
So What DO We Actually Build?
Which brings us back to Nick’s question: agents or agentic applications?
Here’s what I’ve landed on. Agents give us a tidy way to draw a circle around a problem. Don’t boil the ocean. Just give me a loyalty agent. Just give me a segmentation agent. Just give me an analytics agent.
Decomposing big, messy problems into smaller, solvable pieces—that’s what every good systems engineers have done for 40 years, long before AI. But agents are a new twist on this age-old problem. They get us off the rocks of bloated enterprise applications where customers license a gigantic pile of shit from Salesforce, SAP, and Oracle. “I don’t use all of that. I don’t want all of that. I just want this little piece.”
An agentic application? That’s two or more agents that are:
Highly aligned around a shared objective
Loosely coupled – they can talk to each other
This is where things get interesting. New protocols like MCP (Model Context Protocol) let agents basically introduce themselves to each other. An agent can show up and say, “Hello World, here’s what I do, I’m ready to party.” You send it data or instructions, and it reports its results back through the MCP connection. It gives each agent the ability to specialize and talk to other agents in a structured way – no free-form, agent-to-agent chats. It speeds up software deployment by tamping down the over-specification that has plagued conventional software for decades.
Why This Changes Everything (And Why It Doesn’t)
This isn’t 10% better—it’s 10x better. A business process that historically took three weeks of consulting and development now goes live in 48 hours.
Why? Because you don’t have to write it all down. You can gesture, point, grunt, and the system gets it. A little like conversing with ChatGPT: “I think I know what you mean. Let me clarify—more of this or less of that? Oh, okay, good. I got it. Let’s go.”
MCP is just this really tidy way of getting agents to share their toys.
But here’s the thing: everybody needs to breathe in, breathe out. Stop mythologizing agents. I’m grateful Dario Amodei is taking the existential and cybercrime risks of superintelligence seriously, and I’ve written about the pressing need for AI regulation in other posts. But in an enterprise context, workers terrified about their pending enslavement by robot overlords need to settle the fuck down.
At the end of the day, it’s still just software on a screen.
If you’re in the enterprise world, you don’t need superintelligence. You just want software to work quicker, better, faster, stronger. Agents get us there—not through oracular magic, but by being really good at decomposition, really good at context, and really good at solving specific problems (but only if they’ve been thoughtfully specified).
The Bottom Line
The companies that win won’t be the ones claiming to do everything with AI. They’ll be the ones brave enough to say what they don’t or won’t do, smart enough to break problems into manageable pieces, and honest enough to admit it’s still just software.
Really, really good software.
My Stack:
White House prepares executive order to block state AI laws 🏛️🕵🏼
My quick read: this is the federal government and Big Tech trying to preempt 50 states from protecting their own citizens’ data... basically federalizing surveillance under the auspices of innovation. While everyone else debates “innovation vs safety,” let’s see this for what it is:
Big Tech weaponizing federal power to kill state-level privacy protections before they spread
The Trump administration doing Silicon Valley’s dirty work and using DOJ as their enforcement arm against states
The race to the bottom RE: regulatory framework
Nvidia CEO quells Wall Street fears of AI bubble amid market selloff 📈💥
Nvidia crushed earnings again, and demand for their chips is still roaring. But the market is finally realizing that “infinite exponential growth” isn’t a business model.
The demand story is real, but the pace of that demand can’t defy gravity forever
Investors aren’t questioning GPUs, they’re questioning the second derivative: can growth keep accelerating at the same breakneck speed?
Watch Out for ‘Ghost Listings’ in the Jobs Forecast 👻👔
You only get good outputs when you put in good data. Turns out, the monthly jobs report is built on some pretty lousy data… thanks in no small part to a phenomenon that economists are calling “ghost jobs.”
Ghost jobs are roles companies post but never actually hire for. And we’re not talking about rounding errors. A new analysis shows that roughly 30% of all job postings in recent months — and even years — never resulted in an actual hire.
That means:
Employers have been signaling demand that doesn’t exist
JOLTS numbers are overcounting “opportunity” by millions
Policymakers are flying blind on inflated signals