Product manager and builder with years in product management and developer tools. DC roots, grad school @ the University of Texas at Austin, now building from the San Francisco Bay Area. Currently focused on AI agents — designing and shipping agent platforms, agent frameworks, and multi-agent systems, plus the cloud platform services behind them.
Previously
Broadcom
Technical Product Manager – VMware Cloud
Nov 2023 – Aug 2024
Continued leading the VMware Cloud subscription roadmap after Broadcom acquisition of VMware
Aligned new executive stakeholders while maintaining self-service UI and API experiences
Guided integration efforts with Broadcom IT plaform
VMware
Product Manager – VMware Cloud
Apr 2021 – Nov 2023
Owned end-to-end product lifecylce & roadmap for VMware Cloud subscription services across UI and API channels
Launched a $300M ARR SaaS expansion on AWS with engineering, UX, finance, and GTM partners
Implemented an automated subscription model for on-prem customers, opening a new sales channel
Amazon Web Services
Sr. Product Mangager Intern - Technical
Jun 2019 – Aug 2019
Prototyped a cost management and allocation tool for container services with engineering partners
Analyzed the container cost market to surface competitive gaps for the AWS roadmap
Ran customer feedback sessions on prototypes to align workflows with enterprise needs
Fannie Mae
Technology Engineer & Analyst
Aug 2012 – Apr 2018
Led developer tooling for 220+ applications to improve productivity, quality and compliance
Deployed a component management system integrating security, legal, and architecture controls
Built evaluation frameworks that assessed 100+ software products for enterprise adoption
UT Austin McCombs School of Business
MBA, Technology & Innovation
Class of 2020
Consortium for Graduate Study in Management fellow, Graduate Business Technology Group, Black Graduate Business Association
Board Fellow with Texas Folklife, advising on digital strategy
All-in-one group coordination app for trip planning—chat, proposals, payments, and live locations.
Coffee Scroll - Morning News Podcast
Private - In use in portfolio
Automated podcast generator that converts curated news into daily audio episodes with AI-powered summarization and natural voice narration. Aggregates multiple news sources and produces professional-quality episodes on autopilot.
Windy
In Development
Web-first SaaS learning platform for teens and adults with AI-assisted tutoring, project-based courses, and meaningful gamification.
Ring
Private Use · Run Bi-Hourly
Automated job discovery system that monitors PM openings across multiple ATS platforms.
AI agent security risks stem from authority confusion—untrusted content issuing commands to software that already has user permissions—rather than model alignment failures.
Vercel released durable-harness, an open-source package that logs every model and tool call so Pi, OpenCode, Claude Code and Codex sessions resume after crashes, timeouts and redeploys on Vercel, Postgres or a laptop.
Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve the agent harness, the software that governs tool use, memory management, and task execution, while keeping the underlying language model fixed. Recent methods automate this process by using a meta coding agent to modify the harness based on execution feedback. However, relying on that agent's existing knowledge and observed failures can
How OpenAI works with distribution partners to uphold consistent safeguards, support responsible access, and clarify expectations in our Usage Policies.
CTGT replaced the identifiers with stable labels, sorted the list and isolated each test in a fresh organizational environment. Five subsequent runs each produced the same 34 obligations.
We ran one synthetic banking manual through our pipeline four times and got four different sets of obligations, from a model that returned identical text for identical requests.
The article examines the transition from microservices to agentic AI architecture in distributed systems. Microservices allow for functional decomposition, while agentic systems focus on decision decomposition. This shift introduces new complexities in observability, reliability, and system design, highlighting the need for updated architectural patterns and practices.
Founded in 2025 by Red Hat, IBM (NYSE: IBM), Google Cloud, CoreWeave and NVIDIA, and now governed by the Cloud Native Computing Foundation (CNCF), llm-d plays a key role in the open foundation for enterprises deploying AI at scale in production.
Search: TavilyScript: GPT-5.4 miniVoice: Fish Audio S2.1 Pro
Mercury 3 is the most capable diffusion LLM released to date. It outperforms GPT-6 Luna and Claude Haiku 5.5 while running 4–8x faster at 1,000+ tokens per second.
Decision models like Jev return typed labels with confidence scores instead of text, positioning them as a cost-effective middle layer between SQL rules and full LLM calls for high-volume classification tasks in data pipelines.
NVIDIA's smallest Dory 1.0 4B build is a 3.673 GB Q5_K_M GGUF, so memory is settled on every current Mac. The blocker is software: no llama.cpp release reads the Dory architecture, so you build a pinned contributor fork.
DeepSeek has just released DeepSeek-V4.1-Flash-1017, a new checkpoint of its V4.1-Flash model. It is live on the DeepSeek website, app and API. DeepSeek claims stronger scores, faster task completion and shorter outputs than the September V4.1-Flash release. The company calls it a Pareto improvement in performance and cost. Alongside it, DeepSeek opened its Search and […]
LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a promising approach to automatically evolve these harnesses. However, deploying RSI in open-world settings still faces two critical challenges. First, open-world tasks are typically unseen during the harness design phase and novel at test time, leaving no ground-truth verifiers to reliably guide online harness edits. Second, the RSI process remains
We’re committing a portion of Anthropic’s shares to the Anthropic Public Benefit Fund, a new entity with a structure that increases the stake as the company grows.
How will AI reshape the economy in the years ahead? What is the core source of disagreement about AI's future impact on the economy? This note presents new survey evidence on these questions.
Gartner forecasts agentic AI inference costs will rise fivefold by 2028 despite falling token prices, driven by agents consuming 5-30x more tokens per task than chatbots and labs reinvesting efficiency gains into costlier frontier models.