Atomic Gravity CEO Tolga Tarhan was recently featured in ZDNet, sharing what it actually takes to get AI agents into production.
You can read the full article here:
👉 Deploying AI agents is not your typical software launch – 7 lessons from the trenches
The Shift That’s Happening
As enterprises move from AI experimentation to real deployment, one thing is becoming clear:
AI agents don’t behave like traditional software.
They introduce new challenges around control, autonomy, and ROI. But more importantly, they expose something deeper — most teams aren’t set up to actually ship.
That’s where things break.
What We See in Practice
At Atomic Gravity, we focus on getting AI into production — fast. Not pilots. Not demos. Real systems.
That perspective shaped Tolga’s contribution in the piece.
“Most of the agents we deploy are scoped to a single domain with clear guardrails and measurable outcomes.”
It’s a simple idea, but it runs counter to how most teams approach AI, trying to do too much, too early.
The result is predictable: complexity goes up, clarity goes down, and nothing ships.
Where Teams Get Stuck
Another theme from the article: teams often start in the wrong place.
“Define success upfront. Instrument everything. Keep humans in the loop longer than feels necessary.”
AI projects don’t fail because the models aren’t good enough. They fail because they’re treated like experiments instead of systems.
“When done right, AI agents can be transformational. When rushed, they become expensive demos. The difference is discipline.”
The Takeaway
AI agents aren’t just another feature to deploy.
They require a different way of building, operating, and scaling software.
The teams that succeed will be the ones that move early, but with focus, structure, and a bias toward shipping.
Read the Full Story
ZDNet breaks down seven lessons from teams actively deploying AI agents in the real world, including insights from Atomic Gravity.
