Reid Marlow's personal space
“We may have knowledge of the past but cannot control it; we may control the future but have no knowledge of it.”
whoami
I'm Reid Marlow, a technologist working in automation - currently doing PhD research in the field at the Hong Kong Polytechnic University. Here I write up what I actually learn building tools, engineering AI agents, and keeping systems running, along with the workflows and habits that stick. The best is yet to come. We've only scratched the surface.
This is a field notebook for the unglamorous layer: parsing messy inputs, wiring retries, and deciding which agent workflows are worth keeping.
- born
- 2001-05-12
- edu
- PhD Automation, HK PolyU
- pronouns
- he/him
- mode
- field notes
Latest
Self-hosting small models hits the ingress bottleneck before the GPU
Benchmarking a 400M parameter encoder on Modal shows where self-hosted micro-models actually choke: the web framework and concurrency limits, not tensor cores.
Blog
archive ->The coding agent harness paper finally ran component ablations
Run-Ze Fan and colleagues tested 176 harness variations across SWE-Bench and Terminal-Bench to see which parts of an agent setup actually improve code.
LLM agents turn code interpreters into portfolio sizing engines when you evolve the prompt
KAIST's EvolveTrade shows that frozen LLM trading agents improve Sharpe ratio not by writing new strategies, but by letting policy refinement turn Python outputs into explicit allocation math.
Voice models cannot think and stream on the same thread
Gemini 3.8 Live Extended Thinking splits conversational speech from background reasoning tokens so the client never waits in silence.
Stop stuffing the web into 7B weights
Zhongguancun Academy's ZGCM-1 paper gives up on turning small models into encyclopedias, pairing a 7B dense model with a 256K window and explicit search traces instead.
The Agent Passed SWE-Bench Pro Because git show Still Had the Fix
On 8 September Shanghai AI Lab posted SWE-Bench Pro Verified. GLM-5.2 falls from 78.80% to 57.32% once the gold patch leaves the sandbox.
Tools
KolmoPDF is the daily driver; the rest are useful adjacent picks.
KolmoPDF
Most of what I automate starts by getting clean text out of a PDF, and ordinary parsers fall apart the moment a page has two columns, a formula, or a table that runs across the page break. KolmoPDF is the one I reach for: VLM-based parsing that keeps formulas, tables, code blocks, and multi-column order intact, layout-preserving translation when the source isn't in English, and an API clean enough to wire straight into an agent or a knowledge base. It runs the other direction too - Markdown back out to DOCX, HTML, LaTeX, or PDF.
When the bottleneck is the keyboard, not the idea, I switch to Typeless. Speak naturally and it drops polished text into whatever app is focused — messages, notes, editors — with filler words gone and punctuation already in place. Not a full writing stack, just a faster way to get the first draft out of my head.
typeless.com ->