i'm a software engineer based in the philippines, driven by curiosity and whatever i find interesting. i learn fast with the caveat of goldfish memory (which i call my context lol) and i'm usually self-motivated that i forget to eat.
this is not like other portfolios. feel free to have a look around and explore what makes me, me.
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@schmayterling
open githubrecruiter?
(follow the red line) →the same circle, over and over.
for those who want something simpler
enter simple mode
i enjoy writing code.
if ai solves every problem,
what's left?892 commits. the personal AI agent i've been trying to build since 2023 is finally becoming something i'm proud of.
one question usually turns into three projects and too many open tabs.
typescript, python, rust, go, infrastructure, and agents.
in roughly five weeks
an earlier role handled 2,000+ requests a day at 99.3% uptime.
i update this board whenever my attention changes, so it never settles into a final form.
how WFDs work, when to write one, the states a document can be in, frontmatter format, and the markdown features available.
my desktop is scattered screenshots, dozens of windows, half-finished checklists, and constant switching.
whatever feels urgent or interesting gets the whole pile.
right now, only this website and my ai work count as current.
did i mention this board evolves over time? you might find new stuff here next time. suggestions? email me.
hey@ryanaque.com
i turned weeks of neuroscience papers into her memory system.
weave gives long-running agents memory, state tracking, and retrieval that can be inspected.
i watched a kdrama about a girl who forgets everything every morning and realized my AI agent has the same condition. so i built it a brain.
someone else is
on the other end.
28 tasks × 5 trials · +0.125 det · −34% tokens/task
i'm less interested in whether it's good.
ideally when something is coming up, whether it's work related or it's just a personal project of mine i usually let it run at the end because i need pressure to perform things.
diffusion models
i built an AI agent with persistent memory. now i need to figure out if it's remembering the truth or just what i wanted to hear.
AI makes me faster. It also might be making me dumber. I'm figuring out where the line is.
atlas maps symbols, calls, tests, and history so developers and agents can ask structural questions about a repository.
2,239-trial benchmark across 8 OSS repos: Atlas beats a text-search baseline by +0.223 deterministic, +0.127 LLM-judge, at 42% fewer tokens.
orchestrator lets a local model read and control a live chromium page through the devtools protocol.
apr 18–19, 2026 · atlas
28 tasks × 5 trials · +0.125 det · −34% tokens/task
at 18:03 on apr 18, 58 seconds after the benchmark commit, the score was +0.125 deterministic and +0.035 llm while tokens per task fell 34% and cost fell 25%.
i mapped symbols, calls, and tests, then compared the agent against plain text tools before trusting the graph.
the first result looked too good, so i gave the judge code tools and added unseen corpora before trusting it.
i turn an idea into a tool, measure it, look for the embarrassing counterexample, and keep whatever survives.