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Imagine building your entire product roadmap on the world’s most advanced AI model, only for it to vanish overnight. That nightmare became a reality when a US export-control directive forced Anthropic to abruptly disable Claude Fable 5 and Mythos 5 globally, just three days post-launch.
This sudden cutoff has reignited a fierce discussion on India’s Sovereign AI strategy. Tech leaders are sounding the alarm on the risk of relying entirely on foreign AI infrastructure. But let’s be real: products don’t get built over Twitter talks.
While grand visions of building a homegrown frontier LLM make for great social media engagement, the ground reality of execution is incredibly complex. Training foundation models from scratch requires astronomical compute power, deep capital, and highly specialized talent.
Just look at Ola’s Krutrim AI, whose consumer assistant Kruti recently went offline, highlighting the massive operational hurdles of maintaining stable models. Instead of chasing vanity metrics, should Indian teams focus on open-source foundations or specialized middleware?
Pragmatic players like Sarvam AI are showing the way by building voice-first models tailored for local context instead of competing on brute-force scale.
India has also just launched Varya, an open-source, government-backed AI video model that is 20 times cheaper than global rivals. It generates culturally accurate, high-definition Indian-themed videos in just 45 seconds using a highly efficient 4-step distillation process.
This is the kind of frugal, practical innovation that India thrives on.
For PMs and designers, this episode is a massive lesson in dependency mapping. If your core UX depends entirely on a third-party API that can be yanked away by a foreign regulator, you aren’t building a resilient product - you are building a house of cards.
How are you designing your UX to handle AI service fallbacks?
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UI/UX Designer at Salesforce | Bengaluru
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