NewTimeSpace reports that a closed-door dialogue obtained byUnique Research at CES 2026 AI Demo Day featured a core discussion between Tanka CEO Kisson Lin and Emmy-nominated producer Jesse Z, highlighting how fundamental changes in AI product marginal cost structures are forcing companies to abandon internet-era thinking and shift toward a "tiered subscription + usage limits" hybrid model. The two guests revealed the core logic transformation in AI commercialization for 2026 from the dimensions of productivity tools and entertainment creation respectively.

On market selection strategy, Kisson Lin proposed clear criteria: must target niche markets that are currently small but in high-growth phases. Citing Canva and Slack as examples, he noted both companies started from specific, analyzable niches. If a market is already large, it indicates saturated competition with no opportunities for startups. For B2B products, the best approach is to start within one's immediate network, conduct extensive interviews, identify common demand patterns, and locate gaps unaddressed by existing products.

Regarding localization strategy, Jesse Z emphasized the necessity of hiring local Go-to-Market (GTM) teams and respecting local cultural workstyles. "Don't try to hire locals but expect them to work like Chinese teams," Jesse Z warned. "Without respecting local culture and workstyles, retaining talent becomes difficult." Kisson Lin further defined localization as not merely geographical but user-tiering. "Small micro-enterprises (<20 people) and large enterprises have completely different needs," he noted. True localization means deeply adapting products to the needs of different user tiers.

On connecting product development with market feedback, Kisson Lin shared a highly operational approach: having engineers directly watch recordings of sales demos or establishing "Office Hours" for engineers to speak directly with users. Under traditional models, marketing teams bring back cold bullet points that engineers cannot empathize with. Directly observing where users get stuck or confused is more effective than meeting discussions. "Don't just listen to what users say, watch what they do," Kisson Lin emphasized. "In UI/UX, user feedback is often inaccurate; observing their confusion through recordings is more effective than meeting discussions."

On overseas fundraising strategy, both guests offered practical advice. As a non-technical founder, Jesse Z's strategy was to first secure B2B partnerships (with schools, brands, agencies), generate revenue and traction, prove the product works in the local environment, at which point investors will proactively approach. Kisson Lin stressed the importance of creating FOMO (Fear of Missing Out): "Don't let investors think you're a 'familiar face.' The best strategy is to schedule all roadshows within 2 weeks to 1 month, telling them you're in intensive fundraising mode, which can improve decision-making efficiency."

Commercialization and pricing formed the core of this discussion. Kisson Lin clearly stated that AI-era moat logic has changed. Large data volumes (TikTok model) are no longer absolute advantages; data depth per single user matters more. Moreover, AI inference costs are extremely high, requiring early validation of user payment willingness. "AI not only has high R&D costs but also extremely high inference costs," he warned. "Don't do unlimited freemium models; start charging early to validate value."

Regarding pricing models, both guests agreed the freemium model is dead. Kisson Lin explained that AI products have numerous functions (search, image generation, workflows), but overly complex pricing confuses users. Enterprise clients find pure usage-based models unpredictable in cost. The solution is a hybrid model—tiered subscriptions combined with usage limits. Future trends will shift toward "result-based pricing," particularly in sales/marketing fields, though internal workflows are difficult to measure by results.

On product direction, Jesse Z stated decisively: "Must build end-to-end systems. Users don't need scattered tools; they need complete workflows that truly eliminate technical barriers and directly output value." Kisson Lin predicted that within two years, AI will have stronger memory and context selection capabilities, solving current token limitations. AI will evolve from auxiliary suggestions to autonomous Agents capable of running complex tasks for extended periods without human monitoring.

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