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Aishwarya Riganti — Sonic AI
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Aishwarya Riganti
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Aishwarya Riganti
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In 2025, skepticism among business leaders about AI's longevity has significantly reduced compared to 2024, when many viewed it as another crypto-like wave.
Expert perspective
Aishwarya Riganti
Apr 3
The CEO of Rackspace, Gajen, dedicates time from 4 a.m. to 6 a.m. daily to stay current on AI developments.
Expert perspective
Aishwarya Riganti
Apr 3
Building AI products is fundamentally different from building traditional software due to the non-deterministic nature of both user inputs via natural language and the probabilistic outputs from LLMs.
Expert perspective
Aishwarya Riganti
Apr 3
In some companies, subject matter experts are reluctant to collaborate on AI projects because they fear their jobs are being replaced.
Expert perspective
Aishwarya Riganti
Apr 3
The cost of implementing AI products will become 'ridiculously cheap' in the next few years, making design, judgment, and taste more valuable skills than pure execution.
Speculative
Aishwarya Riganti
Apr 3
A paper from researchers at UC Berkeley and Databricks, including Matei Zaharia and Ion Stoica, found that approximately 75% of surveyed enterprises cited reliability as their biggest problem with AI.
Expert perspective
Aishwarya Riganti
Apr 3
Major model updates, such as the deprecation of one API version for another, can break existing AI systems and require a full recalibration due to the new model's different properties.
Expert perspective
Aishwarya Riganti
Apr 3
Security issues like prompt injection will become a huge problem once AI systems go mainstream, but currently most teams are too focused on building to worry about it.
Expert perspective
Aishwarya Riganti
Apr 3
Developing agentic AI systems requires managing a trade-off between granting the system more agency to make decisions and relinquishing human control.
Expert perspective
Aishwarya Riganti
Apr 3
The claim of 'one-click agents' that work out-of-the-box for enterprise use cases is pure marketing and should be met with skepticism.
Expert perspective
Aishwarya Riganti
Apr 3
The term 'evals' in the AI industry is suffering from 'semantic diffusion', where it is used to describe many different activities, leading to a loss of its original, specific meaning.
Expert perspective
Aishwarya Riganti
Apr 3
Approximately 80% of the work for AI engineers and product managers involves understanding customer workflows, behavior, and data, rather than building advanced models.
Expert perspective
Aishwarya Riganti
Apr 3
An Air Canada chatbot hallucinated a refund policy that was not part of the company's official playbook, and the company was legally required to honor it.
Expert perspective
Aishwarya Riganti
Apr 3
Multi-modal AI experiences will be a major trend in 2026, moving beyond text-only LLMs to incorporate richer, more human-like conversational signals.
Speculative
Aishwarya Riganti
Apr 3
The AI product development lifecycle is very different from traditional software, which has broken established handoffs and collaboration models between PMs, engineers, and data scientists.
Expert perspective
Aishwarya Riganti
Apr 3
Replacing a critical enterprise workflow with an AI system typically takes four to six months of work, even for companies with optimal data and infrastructure layers.
Expert perspective
Aishwarya Riganti
Apr 3
The key to success in the current AI market is not being the first to launch an agent, but building the right data and feedback flywheels to enable continuous improvement.
Expert perspective
Aishwarya Riganti
Apr 3
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