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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i turned weeks of neuroscience papers into her memory system.
W
weave
weave gives long-running agents memory, state tracking, and retrieval that can be inspected.
current benchtypescriptagentsmemory
giving an ai agent a hippocampus
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.
wfd · 2026-02-28T02:01:00 · 14 min
what keeps me going
someone else is on the other end.
x.com
follow me on X
from avery v3github.com
Mem0
from giving an ai agent a hippocampusarxiv.org
Zep: A Temporal Knowledge Graph Architecture for Agent Memory
from giving an ai agent a hippocampus
i'm less interested in whether it's good.
how does it work?
my focus has improved and i'm not sure why.
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.
maywritten · 2026-06-10 · 3 min
a handdrawn chart titled day in a life showing focus changing through the daymy focus has improved and i'm not sure why.my.clevelandclinic.org
lamotrigine
from my focus has improved and i'm not sure why.aligned.substack.com
Jan Leike
from do you want me to do that?
noiseshape
diffusion models
watching a photo develop.
do you want me to do that?
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.
wfd · 2026-03-02T09:42:00 · 4 min
the usage of ai in daily work
AI makes me faster. It also might be making me dumber. I'm figuring out where the line is.
wfd · 2026-02-28T02:01:00 · 3 min
nytimes.com
AIinduced psychosis
from do you want me to do that?
A
atlas
atlas maps symbols, calls, tests, and history so developers and agents can ask structural questions about a repository.
current benchtypescriptsqlitemcp
Atlas: structural code-intelligence for LLM agents (an empirical evaluation)
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.
wfd · 2026-04-19T18:00:00 · 17 min
O
orchestrator
orchestrator lets a local model read and control a live chromium page through the devtools protocol.
current benchtypescriptcdpagents
llm-judge-bias.github.io
judgebiasbench
from Atlas: structural code-intelligence for LLM agents (an empirical evaluation)
Stub
i haven't finished writing this yet. i publish drafts early as part of WFD 17.
I use AI when writing code. Objectively it's better at writing code than doing it by hand, provided you prompt it right. Garbage in, garbage out. The quality of the output is a direct function of how well you frame the problem, the constraints, and the context. If you feed it vague instructions you get vague code.
Oxide's RFD 576 frames it well. The responsibility lies with the person in the chair. The AI is a tool. The output is yours. If the code is wrong, that's on you, because you accepted it. If the architecture is bad, that's on you, because you approved it. The moment you stop understanding what's being generated is the moment the tool becomes a liability.
the problem
Ever since WFD 15 I've been starting to wean off heavy AI usage. The reason is simple: I feel dumber.
I had a moment where I kicked off an AI task to solve something and it sat there thinking for thirty minutes. While it was thinking I already finished the task myself. I cancelled the run. Wasted tokens, wasted time, and I could've just done it from the start.
The same thing happens with explaining code I wrote. I know the codebase. I built it. But I hit mental blocks trying to articulate how something works because I've been letting AI do the tracing for me. The muscle for retracing logic and holding context in my head is atrophying.
AI is good. AI is a 10x multiplier. I've heard it all. But it's making me worse at the things I used to be good at because it's doing them for me.
the real issue
I enjoy writing code. I enjoy writing this document. Delegating everything to AI takes the fun out of the thing I actually love doing. Programming got me started because I liked solving problems. If the AI solves every problem, what's left?
arguments against reducing AI usage
It's genuinely faster for boilerplate, tests, and repetitive work
It catches patterns and bugs I'd miss on the first pass
The time savings on large refactors are real
Fighting against better tooling is a losing position long-term
arguments for reducing AI usage
I'm losing the ability to hold complex systems in my head
Muscle memory for debugging and tracing is degrading
I enjoy the craft and outsourcing it defeats the point
Over-reliance creates a dependency I don't want
The thirty-minute-thinking incident was a wake-up call
where i currently stand
Starting to wean it off. I'm not going cold turkey, but I'm being more intentional about what I delegate and what I do myself. The boring stuff (boilerplate, repetitive refactors, test scaffolding) is fine. The interesting stuff (architecture, debugging, problem-solving) I want back.