The complete Blast Radius read

Implications of the AI Capability Surge

The current wave of AI impact is proving to be the most consequential shift the technology market has ever experienced. As of June 1, 2026, the current wave of AI disruption is less a normal software cycle than a change in who does the work, how fast products can be created, and where durable business value can still live. Prior platform shifts (personal computers, client-server, broadband, mobile, etc.) made people faster. This one is beginning to move work from human operators into model-driven systems, agents, and AI-native services at a speed the market has not seen before.

As throughput, reasoning, autonomy, and code generation improve, software markets are entering a new regime. Better frontier models do not merely improve products; they compress differentiation, change buyer behavior, and threaten the viability of business models built on functionality that can be recreated by the next model release or agent platform.

The practical question for founders and early-stage investors is therefore no longer just whether a product is useful, has traction or leverages AI in some way. It is whether the company can stay above the Frontier Line long enough to build trusted deployment, proprietary context, workflow control, distribution leverage, and real economic defensibility.

The AI blast radius is the widening zone of disruption, innovation and business-model exposure created as frontier AI capability and deployment evolve faster than organizations can absorb them.

Fundamental startup viability criteria for founders and investors have expanded to consider AI product architecture, inference economics, harness strategy and if the company can stay above the Frontier Line long enough to build awareness, trusted deployment, proprietary context, workflow control, distribution leverage, and real economic defensibility.

The concept in an image:

The red Frontier Line represents the increase in best-in-class frontier-model capabilities over time. Below that line are dead or soon-to-be-dead companies and the line is moving up. Words are important here: the functionality that exists below the line will persist in a variety of ways going forward; it’s the existing business models associated with the companies below the line that will cease to exist. This is already happening as startups pick off subscription-based tools to internally reproduce, tailored to their specific business requirements.

Any software company operating near the Frontier line (or even perceived as operating near that line) is subject to a turbulence cloud of doubt and suspicion associated with the devaluation or commoditization of easy to replace software. Restated: the zone around the Frontier Line represents perceived durability risk, the customer/investor/market’s belief that a company’s current value proposition, pricing power, or growth may not survive the next wave of AI capability improvement, even if the business looks relatively healthy now. It is the doubt that buyers, investors, and acquirers place on whether the company will remain meaningfully differentiated as the Frontier Line rises. In practice, that perception alone can slow sales, compress valuations, and tighten financing well before actual disruption fully arrives. Companies affected by perceived durability risk will almost certainly not overcome the noise in the market and their GTMs will dramatically slow or completely stall.

The green Typical Enterprise Readiness curve (different y-axis, for the record) is the dotted answer to the question the Frontier Line implicitly asks: who is actually positioned to absorb this capability? Where the red line tracks what Frontier AI can do, the green line tracks if the average enterprise can organizationally consume it. The shape tells the story: readiness sits essentially on the floor through the front half of 2026, begins to bend as enterprises self-transform or are facilitated by ServiceCOs (see below) engagements. The Frontier Line gap never closes because capability advances on a research and compute cadence are measured in months while organizational readiness advances on a change-management cadence, traditionally measured in years.

• Below green: Enterprise ready and open to purchase and can absorb AI on their own; often crowded, lower-friction, AI experimental budgets flow freely; however, software here is more likely to become internal tooling or next-Frontier model inherent capability. Importantly: a startup in this zone may be currently successful but operating on borrowed time regardless of how much demand the green line implies.
• Between green & red: contested adoption market. The enterprise needs help deploying it, but the core functionality is under commoditization pressure. This is the services, integration, workflow packaging, trust, governance, and implementation market. Noisy and comes with commoditization risk.
• Above red: The durability zone. Not yet reproducible by frontier AI alone, especially if paired with proprietary data, workflow control, trust, distribution, regulatory moats or outcome ownership.

If a business can overcome the turbulence, growth can happen quickly when exploratory budgets for learning and experimentation with AI are being thrown around. In major tornados (the Geoffrey Moore type), many companies will lean in and try a handful of new tools and solutions as they figure out what’s what and where to start; early-stage companies that participate in those budgets can be fooled that the revenue is more predictable and repeatable than it really is and can be surprised as experimentation budgets morph or go away.

This phenomenon exists because Effective AI Frontier Capability (reasoning, autonomy, coding) grows at ~5x every 18months. The graph below (Anthropic’s Frontier models shown) shows actual capability growth through March 2026 (Blast Radius 1.0) and an 18-month capability growth forecast. Historic benchmarks are actuals.

Factoring in three compounding forces - smarter models × better harnesses × recursive improvement – results in an estimated 5–6× capability gain over the next 18 months.