Spring 2025: As American tech companies quietly shift from AGI promises to specialized solutions, one CTO explains the strategic pivot reshaping Silicon Valley
Spring 2025 brought silence to tech conferences—the word "AGI" vanished from presentations. In its place came modest terms: "agents," "specialized models," "vertical solutions."
For Oleksandr Boiko, CTO at Field Complete and Principal Backend Engineer at Plat.ai, this validated a direction he'd taken months earlier. While managing distributed teams across three continents, he'd watched the gap widen between AGI promises and business reality.
What Silicon Valley was finally admitting in spring 2025, Oleksandr had built his strategy around since late 2024.
"While some companies were still talking about AGI, others took the path of covering specific industries and professions with specialized models," Boiko explains. "This triggered battles not for the market as a whole, but for specific niches generating revenue."
When OpenAI Blinked
In January 2025, Sam Altman still claimed to "know how to build AGI." By March, OpenAI's tone had changed completely—focusing on practical applications instead of grand timelines.
Oleksandr saw this coming. When Cursor.ai emerged as a coding assistant purpose-built for developers, it proved something uncomfortable: a tool designed for one job beats a system trying to do everything.
"The appearance of Cursor.ai showed that a specialized tool is now much more interesting to the market than an abstract all-knowing model," he notes. "This provoked investors to shift focus from expensive AGI—where it's unclear when it will be ready—to specific products already generating revenue."
The investment data confirmed it. CB Insights reported 340% growth in specialized AI applications during Q1 2025. More telling: 80% of large funding rounds over $50 million went to companies building solutions for specific industries—healthcare, finance, legal, education.
Bessemer Venture Partners put it bluntly in their March report "The Future of AI is Vertical": "The era of horizontal AI platforms is ending. The future belongs to vertical solutions."
Legal AI platform Harvey raised $80 million in February at a $1.5 billion valuation. Meanwhile, startups promising "AGI for business" struggled to close rounds.
Google and Microsoft Follow
Google reimagined its product positioning with Gemini 2.0, moving from understanding information to making it useful. Microsoft went further with Azure AI Foundry, positioned as an "AI agent factory"—instead of one universal system, dozens of specialized agents, each excelling at specific tasks.
Oleksandr's path—early engineer to Head of Engineering to CTO—gave him a clear view of the economics. At Field Complete, he's CTO. At Plat.ai, he's still writing code. That combination—strategy plus hands-on work—shaped how he thinks about technology and business growth. At Field Complete—a platform serving everyone from solo handymen to large property management operations—he made an early call: focus on specialized AI models that could ship within quarters, not general systems promising everything eventually.
The company, which raised two rounds from venture funds, structured around this principle. Instead of waiting for one universal AI to handle contractor workflows, they deployed multiple focused tools—each solving a specific problem in field service management. Revenue followed execution, not promises.
"Having an agentic approach with a rich selection of models for different tasks, businesses can now form their workflows and pipelines, closing gaps or entire processes they previously outsourced," he explains.
His teams saw the shift firsthand. AI didn't just accelerate work—it changed what they could build. Specialized models opened capabilities that previously required either substantial budgets or staff they couldn't hire. Development timelines compressed. Operations that demanded external expertise became internal strengths.
The Academic Reckoning
While corporations repositioned, researchers weren't buying it. A March 2025 AAAI survey of 475 AI researchers found 76% consider achieving AGI through scaling current approaches "unlikely" or "extremely unlikely."
At January's CES conference, Yann LeCun was categorical: "There's absolutely no way that autoregressive language models will reach human intelligence."
Technical limitations became impossible to ignore. Energy requirements for training potential AGI systems could exceed medium-sized countries' CO₂ emissions. Quality training data scarcity approached critical levels.
Oleksandr doesn't dismiss AGI entirely. "AGI is still interesting, but nobody knows how much time, finance, and computing power it will take, and whether it will be trustworthy without verification."
That uncertainty makes AGI unsuitable as a business foundation. Companies can't build strategies around technology arriving in five years or fifteen.
"The most promising directions right now are systems for managing and orchestrating models, plus specialized models responsible for specific tasks," he says.
His practical focus shows. "This set of tools opens opportunities that were either unaffordable before or difficult to staff. Replacing some human professions with AI significantly saves budget and allows you to have 'employees' of the same required level as many as you want."
The Geographic Divide
The AGI retreat isn't universal. China's "AI+" program provides $6 billion in direct government funding, and major Chinese AI companies' safety commitments signal continued investment in AGI. Europe chose a third path: the EU's €200 billion InvestAI initiative focuses on "trustworthy AI technologies" within regulatory frameworks that make general-purpose systems expensive to develop.
Oleksandr, who evaluates Ukrainian-founded startups as a juror for UAtech Venture Night at Web Summit Vancouver, sees these regional patterns clearly.
"The USA is now the main player thanks to available resources, both human and technological," he observes. "China shows itself quite well considering they don't have access to cutting-edge hardware. Europe heavily regulated this industry, not letting it develop when it's very important to be in the race."
He adds: "The new US administration fully supports this direction of development, helping attract investment and partnerships."
Execution Beats Vision
At UAtech Venture Night, Oleksandr applies a single filter to startup evaluation: can a team take an idea to customer metrics within a quarter? This philosophy shapes Field Complete's approach.
"For us, AI isn't a trend anymore. It's infrastructure. We measure AI benefits the same way we measure uptime or release costs."
While competitors explore possibilities, Field Complete ships features. While others develop roadmaps, Boiko's teams close legal questions in hours, write code faster with better quality, and scale service capacity without proportional headcount growth.
Competitors are still exploring. Field Complete is already ahead.
Boiko frames the AGI retreat as strategy, not failure. "This brings money into the industry, which catalyzes development. AGI stopped being so interesting because, having an agentic approach with wide model selection for different tasks, business already has the opportunity to form its workflows."
Simultaneously, specialized AI applications demonstrate clear profitability paths and market validation, providing immediate ROI and clear differentiation strategies.
What It Means
Spring 2025 was when the industry stopped pretending. Practical AI through specialized agents wins. Universal systems lose. This isn't technological failure—it's recognition that solutions you can deploy beat breakthroughs you can't.
American companies pivot toward specialized applications. Chinese firms maintain AGI ambitions with government support. European approaches emphasize trustworthy AI within regulatory frameworks.
Companies that internalized this shift early are now quarters ahead. Those waiting for the "right moment" explain to boards why similarly-resourced competitors grow faster.
The AGI race continues in research labs. But the competition that matters—for market share, operational excellence, customer satisfaction—is being won with specialized AI deployed today.
For technology leaders like Oleksandr, whose 18-year journey from engineer to CTO across video-on-demand, advertising, SaaS, and fintech taught him to distinguish between promising futures and profitable presents, the choice became obvious by spring 2025. Build what ships. Measure what matters. Win while others wait.
