Token Engineering

From MIT Decoding Research to Today’s Inference Tradeoffs

Token Engineering

Show Notes

Check out the latest episode of Inference Time Tactics. Our guest is Pawan Deshpande, founder, product leader, and angel investor in companies like Anthropic and Toast, with roles at Google, Scale AI and Domino Data Lab.

Hosts Rob May & Calvin Cooper sit down with Pawan to cover:

Early MIT NLP research applied to today’s inference-time tradeoffs How to evaluate enterprise agents in practice Training data plus inference filtering in real deployments Open source adoption realities in the enterprise Where durable value lives in the stack

Connect with Pawan Deshpande Website: https://pawandeshpande.com/Academic / Research Works & ThesisDecoding Algorithms for Complex Natural Language Tasks (MIT thesis, 2007)Randomized Decoding for Selection-and-Ordering Problems Connect with Neurometric:Website: https://www.neurometric.ai/ Substack: https://neurometric.substack.com/ X: https://x.com/neurometricai/ Bluesky: https://bsky.app/profile/neurometric.bsky.social

Hosts: Rob May https://x.com/robmay https://www.linkedin.com/in/robmay

Calvin Cooper https://x.com/cooper_nyc_ https://www.linkedin.com/in/coopernyc

More from Token Engineering

Aug 5, 2026

In this episode of Token Engineering, Cooper sits down with Yash, Head of AI Research at Neurometric AI, to break down TMax from AI2 (Allen Institute for AI)—a fully open dataset and training recipe that pushes small open-weight models like Qwen to near-frontier performance on terminal agent tasks. The paper argues that diversity and difficulty matter more than where the data comes from—even when that data is entirely invented by Gemini rather than pulled from real-world code.

Jul 10, 2026

In this episode, Cooper sits down with Neurometric CEO, Rob May, to talk through a big-news month: the show's rebrand from Inference Time Tactics to Token Engineering, the launch of tokenminning.com as a response to the "tokenmaxxing" trend, Neurometric's new token engineering platform and fundraising announcement. But the bigger conversation is about why Rob thinks "token engineering" is about to become a discipline every AI company needs—the same way DevOps or UX became non-negotiable roles—and why he's betting the company on getting there first.

Jun 16, 2026

In this episode of Inference Time Tactics, Cooper sits down with Yash Sharma, Head of AI Research at Neurometric AI, to break down the Pioneer Agent paper from Fastino Labs—a system that uses Claude Sonnet as an ML engineer in a box to build and improve small language models end-to-end. From cold start data curation to production failure diagnosis, the paper argues the real bottleneck in SLM creation isn't training—it's everything around it.

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In this episode of Inference Time Tactics, Cooper sits down with Fletcher Wimbush, CEO of Discovered AI, to get into what’s actually broken about hiring—and how 13 years of bootstrapped recruiting, 10,000 interviews, and four peer-reviewed journal articles became the foundation for a platform now outperforming its biggest competitors. With hundreds of applicants flooding every open role and general AI tools hitting the ceiling at 70-80% resume screening accuracy, Discovered is combining behavioral science with fine-tuned small language models to get hiring right the first time.

Mar 9, 2026

Every day billions of voice conversations happen across games, customer service calls, and financial transactions. Almost none of them are understood by machines. In this episode of Inference Time Tactics, Calvin Cooper and Yash Sharma sit down with Carter Huffman, CTO and co founder of Modulate, to explore the AI systems that can finally understand voice conversations in real time.

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