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TechCrunch Disrupt 2025 Puts AI Builders Center Stage

TechCrunch Disrupt 2025 brings AI to the forefront with two headline sessions: Greenfield Partners will reveal the AI Disruptors 60 list of startups shaping AI infrastructure and applications, while JetBrains will argue that developer-focused AI must prioritize code quality over raw velocity. Expect investor insights, product strategy, and practical takes for builders and buyers.

Published August 29, 2025 at 06:09 PM EDT in Artificial Intelligence (AI)

TechCrunch Disrupt 2025 centers on the builders remaking AI

TechCrunch Disrupt returns to San Francisco October 27–29 with a clear message: AI is no longer an experiment — it’s the platform layer. Two sponsored sessions from Greenfield Partners and JetBrains will highlight different parts of that shift, from the startups building AI’s backbone to the developer tools that determine whether intelligent software scales with quality.

On Monday Greenfield will unveil the AI Disruptors 60, a curated list of early- and growth-stage companies focused on AI infrastructure, applications, and GTM innovation. Expect investors and founders to debate which architectures, business models, and scaling patterns will actually hold up as demand explodes.

Speakers include leading investors and founders such as Shay Grinfeld and Renen Hallak of VAST Data, who will unpack how these startups are solving real constraints — storage, latency, cost, and developer workflows — that stand between promising models and production-grade products.

Tuesday’s JetBrains session flips the lens to the developer experience. Kirill Skrygan will argue that AI for devs must prioritize code quality, reliability, and maintainability — not just faster output. The takeaway: velocity without safety or testability means technical debt at scale.

Those two angles — infrastructure and developer tooling — are complementary. Powerful models need efficient, dependable plumbing. Developer-facing AI needs observability, testing, and governance to avoid cascading failures when deployed across teams and systems.

  • Greenfield’s AI Disruptors 60: early signals to watch in infra, apps, and GTM.
  • JetBrains on developer-first AI: code quality, testing, and reliability as competitive edges.
  • Investor and founder panels offering practical playbooks for scaling AI safely.

Why this matters beyond the conference: companies and public institutions face a choice. Do you bet on flashy demos or on the vendors and practices that will survive audits, audits, regulatory scrutiny, and real user load? The sessions at Disrupt are designed to help answer that question with lived experience from builders and funders.

Real-world analogies help. Think of AI infrastructure as highways and developer AI as vehicles. You can have a fleet of fast cars, but without well-maintained roads, clear signage, and traffic controls, you get pileups. Disrupt’s lineup is tracing where new roads are being paved and which carmakers are prioritizing safety features.

For investors, founders, and engineering leaders attending Disrupt, these sessions are a chance to align product roadmaps with operational realities: observability, cost engineering, model evaluation, and developer workflows that limit regressions.

QuarkyByte watches these signals to translate them into actionable guidance. We track vendor quality, integration risk, and scaling patterns so organizations can prioritize proof points over product rhetoric. Whether you are a VC sizing convertible note risk or a CTO planning production rollouts, the Disrupt agenda gives you a sharper lens.

If you’re planning to be in Moscone West, make time for both sessions. One reveals who the market thinks will build the new AI foundation, the other explains how builders should use that foundation without creating brittle, costly systems. Together they frame where smart investment and cautious engineering must meet.

Bottom line: Disrupt 2025 is less about hype and more about the plumbing, discipline, and talent that will determine which AI efforts become durable platforms and which become footnotes. Expect concrete examples, tough questions, and a useful map for next steps.

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