The last two years in AI have been disorienting.
Every week brought a new model, a new product launch announced on X, and a new reason to reconsider assumptions that felt settled only months before. For startups trying to keep up, the experience has been less like riding a wave and more like trying to read a map while the terrain keeps shifting beneath you.
It was something I discussed on another episode of The Spiro Circle only a few weeks ago. But this time, according to Tom Findling, Co-founder and CEO of Conifers, the disorientation was merely a prologue for what’s to come.
“The last two years were a promo to what’s going on,” he said. “I think starting in 2026, you really see the maturity, both on the model side and the agent side, to come and really disrupt the enterprise.”
If the explosion of GPT-4, autonomous agents, Claude’s product launches, and multimodal models were just the opening act, what exactly is coming next?
The Convergence Moment
Findling claims the answer is in a convergence that is only now becoming visible. For most of the AI boom so far, the two core components of enterprise deployment (the models themselves and the agent frameworks built around them) were developing on separate tracks. Models were getting smarter, and agents were getting more capable - but the combination wasn’t yet reliable enough to deploy seriously inside a large organization. “I think we got to the point that agents got to a certain level of maturity when you can deploy them in the enterprise, you can monitor them, you can scale them, and the models themselves have become extremely smart.”
SOC teams face alert volumes that no human workforce can realistically process. Analyst shortages are chronic, and Findling estimates that fewer than one percent of applicants for analyst roles can actually do the job. Previous attempts to close the gap were built on rule-based logic that couldn’t adapt to the context-dependent, environment-specific nature of real incident investigation. “We tried for the last decade to solve that problem,” Findling said. “Unfortunately, it didn’t go that well. That’s why we still have business.”
CognitiveSOC, Conifers’ flagship platform, ingests thousands of daily security alerts, uses AI reasoning to investigate incidents autonomously, and delivers measurable outcomes. The company reports up to an 87% reduction in investigation time compared to human analysts working manually.
To date, the company has raised $25 million from SYN Ventures, Picus Capital, and Washington Harbour Partners, whose investment is aimed at expanding into government and critical infrastructure markets. The momentum reflects a growing conviction that agentic AI (systems that can act, not just respond) is the architecture that finally makes the math work.
“If you don’t fix it, it will break.”
Which brings the sharpest business lesson of the moment into focus: The philosophy of adoption. The adage that “if it ain’t broke, don’t fix it” is no longer relevant in a sector that is moving and evolving in weeks, not years. “If you don’t stay current, you become obsolete. Even for two quarters, you haven’t looked at the latest and greatest, the new models, your product is already far behind.”
In our conversation, I highlight this inversion: It isn’t that change is “good” and stability is “bad”, but rather that the calculus of risk has entirely flipped. Waiting used to protect you from premature commitment, but now it exposes you to competitive irrelevance. The companies treating AI adoption as something to revisit once the dust settles are already making a strategic error that they may not be able to unwind.
A lot of our conversation focused on how these two years have seen such incredible transformations. He admitted he could not have predicted back then what he would be building today. Finally, Findling expects to look back on 2026 in two years’ time with the same sense of uncertainty.
The prologue is complete - but no one knows exactly what they’re about to watch.
