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Monday, January 26, 2026
Google's plan to fix why AI actually fails
We're seeing a major shift in how AI actually works: Google DeepMind is proving that structured agentic reasoning beats reactive LLMs for reliability (yikes, all those raw prompts we've been shipping), while Anthropic just dropped Claude directly into Excel for workbook-level reasoning (wild move into productivity tools). Meanwhile, the hardware folks on arXiv are sounding the alarm that inference is no longer compute-bound but memory-bandwidth-bound, OpenAI's adding shopping carts to ChatGPT for direct commerce (bold), and financial services builders are dropping a crucial lesson: infrastructure around the LLM beats better models. Here's what's gnawing at us: if agents need structure and infrastructure to succeed, are we still building products or just fancy wrappers?
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Top Stories
Google DeepMind
Google DeepMind proposes structured agentic reasoning to overcome reactive LLM failures, reframing models as autonomous agents that plan, act, and learn through continual interaction across single-agent, self-evolving, and multi-agent settings.
arXiv
LLM inference is fundamentally memory and interconnect-bound rather than compute-limited, requiring novel hardware architectures like high-bandwidth flash memory and processing-near-memory designs to achieve practical deployment at scale.
Anthropic
Anthropic's Claude integration into Excel enables AI-assisted financial modeling with full formula tracing and transparency, allowing users to test scenarios, debug errors, and build complex models while maintaining spreadsheet structure and integrity.
OpenAI is embedding shopping and commerce features into ChatGPT, including a shopping cart and merchant tools, to transform the chatbot into a transactional platform that directly competes with traditional e-commerce and Microsoft's Copilot shopping capabilities.
Building reliable AI agents for financial services requires moving beyond prompt engineering to focus on data normalization, skill systems, sandboxed execution, and rigorous evaluation—the model is a commodity, but the infrastructure and domain expertise around it create competitive advantage.
Keep Reading
Industry Voices
Thang Luong
Google DeepMind
Co-creator of Gemma and pioneering researcher behind attention mechanisms that power modern transformer architectures.
David Silver
Founder at Ineffable Intelligence
Led DeepMind's AlphaGo and AlphaZero breakthroughs in reinforcement learning, now building his next-gen AI venture.
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