About us
Exploring the real-world applications of Artificial Intelligence on O'ahu — from Pi rigs to quantized LLM agents — and trade hard-won lessons from the field.
🌺 🤖 🌺
Demos like:
* A.I. Greenhouse
* Automated A.I. Agents
* Chat Bots
* Generative Art engines and workflows
* misc things like prompt patterns, LLM configuration findings, observability, cost controls, big data + A.I, devops + A.I.
Workshops like:
* 5-minute chat bot
* [ Ideas? Let us know : Kevin@oahu.ai ]
Featured event
Open Source Legends on data-driven A.I. agents and LLM-assisted PCBs
Two open-source legends (Nathan Marz & Jonas Schnelli) will be presenting at our February O‘ahu A.I. meetup:
- From PCB to Production: Developing Embedded Systems with LLMs
- A Data-Driven Approach to Balancing Quality, Latency, and Cost in AI Agents
If you care about:
- Bridging AI software and real-world hardware
- Building agents that don’t silently regress
- Understanding what your AI systems are actually doing
- Closing feedback loops between production and evaluation
This meetup is for you.
🎙️ Talk 1
From PCB to Production: Developing Embedded Systems with LLMs
by Jonas Schnelli
Estimated time: 20 minutes
LLMs aren’t just changing software — they’re reshaping hardware and embedded development.
Jonas will walk through how modern AI tools are influencing the entire embedded workflow, from circuit boards to firmware to production devices.
What is a PCB?
PCB stands for Printed Circuit Board. It’s the physical board that holds and connects electronic components (chips, resistors, capacitors, microcontrollers) using etched copper traces — the backbone of almost all modern electronics, from laptops and phones to ESP32 and IoT devices.
***
🎙️ Talk 2
A Data-Driven Approach to Balancing Quality, Latency, and Cost in AI Agents
by Nathan Marz
Estimated time: 60 minutes
LLMs are inherently unpredictable. A prompt change that fixes one case often breaks another you didn’t test. When the input space is effectively all of human language, ad-hoc testing leads to fragile agents that fail under real-world usage.
Nathan will show how to build reliable AI agents through systematic, data-driven, iterative development. You’ll see how to optimize across the quality-latency-cost tradeoff using production data, controlled experiments, and deep observability.
This talk covers:
- Structured datasets with real inputs and “golden truth” outputs
- Avoiding circular logic when using LLMs to evaluate LLM output
- Why evaluating individual steps of agent workflows matters
- Tracing and telemetry requirements for AI agents
- Automatically collecting datasets from production traffic
- Online evaluation, alerting, and continuous feedback loops
***
About Jonas Schnelli
Jonas has been writing code for 30 years, spanning web apps, native iOS and Android, and Mac applications. He spent 8 years deep in Bitcoin Core’s C++ internals before focusing on hardware engineering and embedded firmware.
Now based in Hawai‘i, Jonas designs ESP32 devices and explores how AI tools are transforming embedded systems development.
GitHub: https://github.com/jonasschnelli
***
About Nathan Marz
Nathan lives on O‘ahu and runs Red Planet Labs, a distributed company building Rama, a developer platform for scalable backends with far less code and infrastructure.
He created several influential open-source projects, most notably Apache Storm, one of the first systems to enable reliable large-scale real-time data processing. Nathan previously worked at Twitter, where he helped start core infrastructure teams, and he is the author of Big Data: Principles and Best Practices of Scalable Realtime Data Systems.
Outside of work, Nathan enjoys hiking, stand-up comedy, and old movies.
GitHub: https://github.com/nathanmarz
***
🌺 This event is sponsored by Hawaii Coworking (https://hawaiicoworking.co) , Darshaun Nadeau (https://flowingblue.com) and Kevin Riggen (https://oahu.ai) .
Upcoming events
2
The (First Ever) Honolulu OpenClaw Meetup
Hawaii Coworking, 444 Hobron Ln. Penthouse 1 , Honolulu HI 96815, Honolulu, HI, USAloha Tech Enthusiasts,
Oahu AI is excited to host the first ever Honolulu OpenClaw meetup.
https://openclaw.ai/
Share your OpenClaw setup, check out what other people are doing, or just stop by to see what the hype is all about.
This event is mostly just for meeting others, but we have scheduled a short amount of time at the beginning for presentations and live demos. If you would like to show us what you've been working on, we would love to see it (both live demos or slides are fine, 5-10 minutes max). Send me a message.When: Friday February 13th, 6PM-8PM
Where: Hawaii Coworking
444 Hobron Ln, Penthouse 1 | Honolulu, HI 96815
Hosts: Darshaun Nadeau & Kevin Riggin
The Details:- Cost: The event is free to attend.
- Food & Drink: Please note that food and drinks are not provided, so feel free to grab a bite nearby before heading up to the penthouse.
Whether you're looking to troubleshoot your own build or just want to see what the buzz is about, come one, come all!
We look forward to seeing you there and talking all things OpenClaw.Best regards,
Darshaun Nadeau & Kevin Riggin20 attendeesOpen Source Legends on data-driven A.I. agents and LLM-assisted PCBs
Hawaii Coworking, 438 Hobron Lane PH1, Honolulu, HI, USTwo open-source legends (Nathan Marz & Jonas Schnelli) will be presenting at our February O‘ahu A.I. meetup:
- From PCB to Production: Developing Embedded Systems with LLMs
- A Data-Driven Approach to Balancing Quality, Latency, and Cost in AI Agents
If you care about:
- Bridging AI software and real-world hardware
- Building agents that don’t silently regress
- Understanding what your AI systems are actually doing
- Closing feedback loops between production and evaluation
This meetup is for you.
🎙️ Talk 1
From PCB to Production: Developing Embedded Systems with LLMs
by Jonas SchnelliEstimated time: 20 minutes
LLMs aren’t just changing software — they’re reshaping hardware and embedded development.
Jonas will walk through how modern AI tools are influencing the entire embedded workflow, from circuit boards to firmware to production devices.What is a PCB?
PCB stands for Printed Circuit Board. It’s the physical board that holds and connects electronic components (chips, resistors, capacitors, microcontrollers) using etched copper traces — the backbone of almost all modern electronics, from laptops and phones to ESP32 and IoT devices.***
🎙️ Talk 2
A Data-Driven Approach to Balancing Quality, Latency, and Cost in AI Agents
by Nathan MarzEstimated time: 60 minutes
LLMs are inherently unpredictable. A prompt change that fixes one case often breaks another you didn’t test. When the input space is effectively all of human language, ad-hoc testing leads to fragile agents that fail under real-world usage.
Nathan will show how to build reliable AI agents through systematic, data-driven, iterative development. You’ll see how to optimize across the quality-latency-cost tradeoff using production data, controlled experiments, and deep observability.
This talk covers:- Structured datasets with real inputs and “golden truth” outputs
- Avoiding circular logic when using LLMs to evaluate LLM output
- Why evaluating individual steps of agent workflows matters
- Tracing and telemetry requirements for AI agents
- Automatically collecting datasets from production traffic
- Online evaluation, alerting, and continuous feedback loops
***
About Jonas Schnelli
Jonas has been writing code for 30 years, spanning web apps, native iOS and Android, and Mac applications. He spent 8 years deep in Bitcoin Core’s C++ internals before focusing on hardware engineering and embedded firmware.
Now based in Hawai‘i, Jonas designs ESP32 devices and explores how AI tools are transforming embedded systems development.
GitHub: https://github.com/jonasschnelli***
About Nathan Marz
Nathan lives on O‘ahu and runs Red Planet Labs, a distributed company building Rama, a developer platform for scalable backends with far less code and infrastructure.
He created several influential open-source projects, most notably Apache Storm, one of the first systems to enable reliable large-scale real-time data processing. Nathan previously worked at Twitter, where he helped start core infrastructure teams, and he is the author of Big Data: Principles and Best Practices of Scalable Realtime Data Systems.
Outside of work, Nathan enjoys hiking, stand-up comedy, and old movies.
GitHub: https://github.com/nathanmarz***
🌺 This event is sponsored by Hawaii Coworking (https://hawaiicoworking.co) , Darshaun Nadeau (https://flowingblue.com) and Kevin Riggen (https://oahu.ai) .
33 attendees
Past events
13
