Paul Murphy

I reflect on entering successive waves early – distributed systems, telecoms, AI, and crypto – and explain how curiosity, conviction, and timing shape which frontier problems I choose to work on. The conversation also covers how founders can use AI as an embedded capability rather than a buzzword, navigate US/UK/India fundraising and enterprise sales, and decide when to persist, pivot, or hand off a company.

The Pivot Point with Usha · April 2026

I explain how we build and operate full-stack blockchain data infrastructure at Ormi – nodes, transformations, storage, and APIs – so developers can access reliable multi-chain data without becoming data engineers themselves. I also argue that low-latency, high-throughput crypto data is one of the hardest engineering problems and a core requirement for financial institutions, high-throughput chains, and AI agents that consume on-chain data aggressively.

Ormi · 2025

I lay out TrueTribe's view of airdrops as the next evolution of digital marketing, where tokens transmit value rather than only messages and enable fine-grained segmentation and analytics across many chains. I also explain how we serve projects rather than farmers, address trust and reputation in airdrops, support quests and air-drips, and connect those capabilities to the forthcoming TRIBE token model.

Unleashing DePIN · 2025

Opinion piece on bot dynamics in web3 communities, separating spam behavior from productive automation and proposing a more nuanced policy stance.

TrueTribe (Medium) · December 2024

QuickNode feature interview on TrueTribe's product direction, technical choices, and roadmap priorities for token/project operators.

QuickNode Blog · 2024

In this discussion, we examine collateralization in crypto lending, contrast over- and under-collateralized credit with real-world lending, and ask why basic risk management and data-driven scoring failed so badly in recent crypto lender collapses. The episode establishes risk discipline and common-sense controls as core themes for rebuilding healthier crypto credit markets.

With Darshan Vaidya and John Salomon

Crypto Credit Association · February 2023

Continuing their prior conversation, the hosts dissect what went wrong in crypto lending failures and explore how technology, regulation, and better business processes can remediate risk for all parties. They emphasize that sustainable crypto credit depends on rebuilding trust through stronger controls, transparency, and risk-aware behavior rather than chasing short-term yield.

With Darshan Vaidya and John Salomon

Crypto Credit Association · February 2023

This episode introduces why the Crypto Credit Association was formed and invites listeners to join its efforts to improve standards and practices in crypto credit. It frames the show as the first in a recurring series of online events for people interested in the emerging crypto credit ecosystem.

Host — Crypto Credit Association

Crypto Credit Association · November 2022

In this episode, we explain what crypto credit is and connect it to familiar traditional-finance concepts such as lending, collateral, and risk. The conversation is designed as an on-ramp for listeners moving from conventional banking models toward on-chain credit structures.

With Darshan Vaidya (Credora)

Crypto Credit Association · November 2022

Tubetorial · June 2022

Leadership interview on managing distributed teams, with practical communication habits, decision cadence, and operating principles for remote execution.

Authority Magazine · March 2021

Customer story describing Credmark's operating model, legal/commercial workflows, and how the team structured contracts while scaling in web3.

Zegal · December 2019

I explain Graychain's thesis that credit can be extended to pseudonymous blockchain addresses when you have enough behavioral data, enabling true peer-to-peer lending in crypto. I also outline how Graychain's API exposes on-chain credit data and why regions such as Africa, Southeast Asia, and Latin America are early markets for these lending models.

E-LABZ · June 2019

APIStrat · November 2015

Finovate · 2015

I trace how early neural network work in speech stalled due to compute and adaptation limits, then show how renewed deep learning progress transformed error rates after 2009. I argue that the next breakthroughs require robust adaptation to speakers, noise, acoustics, and context, including unresolved issues such as non-native accents, corpus bias, environmental noise, and domain-specific language models.

RE•WORK · September 2015

I explain how Clarify's API platform uses speech technologies to unlock audio and video content, then place that work in the broader history of neural networks versus HMM-based speech systems. I focus on online adaptation – handling accents, gender, noise, and domain-specific language – and review research that combines deep neural networks with older techniques to move speech recognition closer to human-level reliability.

RE•WORK · June 2015

Conference talk framing audio and video as queryable data assets, with practical guidance for turning media streams into searchable, structured information.

APIDays · May 2015

Event record for a RE-WORK session on the evolution of deep learning in speech, including historical context and implications for production systems.

Re-Work · May 2015

In this fireside chat, I discuss my path from large financial systems on Wall Street to building Clarify around emerging speech and voice processing, and how deep learning is changing how companies work with unstructured audio. We focus on lessons from applying voice technologies in regulated domains and the practical realities of commercializing deep learning in industry.

RE•WORK · February 2015

I discuss why opinionated helper libraries can simplify APIs and make application code more maintainable by enforcing strong defaults and patterns. The talk encourages Python developers to encode best practices into libraries instead of leaving every decision to end-users.

PyTexas · October 2014

I show how developers can move beyond playback by using transcription, emotion, identity, and video-analysis APIs to turn audio and video into searchable, structured data. I compare human and machine transcription services, survey API capabilities across modalities, and argue for coherent abstractions – like Clarify's API – to unify heterogeneous signals into something teams can actually build on.

PyTexas · October 2014

Launch piece on Clarify's audio/video search platform, positioning media intelligence as an API-first workflow for developers and product teams.

SiliconHills · September 2014

Seton MedTech Symposium · July 2014

SiliconHills author/tag archive aggregating multiple company milestones, interviews, and launch coverage across different periods.

SiliconHills · Archive

Relocation and growth coverage of OP3Nvoice after Techstars London, focused on scaling go-to-market from Austin.

SiliconHills · December 2013

TechCrunch feature naming OP3Nvoice as a standout from Techstars London, with focus on product differentiation and market timing.

TechCrunch · September 2013

TechCrunch recap of Techstars London Demo Day with OP3Nvoice in cohort context, summarizing positioning alongside peer startups.

TechCrunch · September 2013

Forbes feature on applying intelligence-style analysis to financial communications, with emphasis on compliance, risk detection, and signal extraction.

Forbes · June 2013

Founder profile on building Calltrunk, covering early-stage execution, regulatory context, and lessons from scaling a communications product.

The Guardian · December 2012

Product coverage of ARGOsearch, focused on making recorded conversations discoverable and operationally useful rather than passive compliance storage.

Telecom Reseller · November 2012

Coverage of Call Trunk's Skype+Dropbox integration, highlighting a practical workflow for recording and archiving business calls in the cloud.

VentureBeat · December 2011

Launch coverage of CallTrunk's Skype recording capability, emphasizing compliant call capture and secure cloud retention for business use cases.

TechCrunch · November 2011

Bloomberg · March 2001

Essay on how modern software practice can reuse durable lessons from earlier engineering eras, with a focus on practical interoperability and system design trade-offs.

Linux Journal · September 1999

Object Magazine · July 1996

Co-authored with Rock Howard and Jason Schroeder

Eiffel Outlook · July 1994

NeXTWORLD Expo · Winter 1992

Closing the Gap · Spring 1989