Mike @internalises

Software developer @browserbase mikem.codes Joined April 2016

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Mike @internalises

a day ago

@beach_grapes @heinenbros Zillow, Redfin, apartment listing sites, etc scraping + cataloging. Probably using a model like DINOv2 to create embeddings from these images, then find most similar to your reference image… just guessing

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Mike @internalises

3 weeks ago

@InGameHQ How many sigmas

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Mike @internalises

4 weeks ago

@hiiinternet So clean 🧼

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Mike @internalises

2 months ago

@peytoncasper Ominous...

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Mike @internalises

2 months ago

@derekmeegan Loading up the system

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Mike @internalises

2 months ago

@peytoncasper @derekmeegan

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Mike @internalises

3 months ago

@peytoncasper

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Mike @internalises

3 months ago

@Jaxenormus @__Tkat__ 🤢

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Mike @internalises

6 months ago

@wyatt_sg V2 in my gym

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Mike @internalises

7 months ago

@GeckoSquadron No crying in the casino

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Mike @internalises

7 months ago

Want to join the team that works on this? We’re hiring a Platform Services Engineer at Browserbase. Sneaker bot / anti-bot experience is a major plus. jobs.ashbyhq.com/browserbase/14…

harsehaj ⋆˙⟡ @harsehaj

7 months ago

We forked Chromium and broke it until it worked exactly the way we wanted it to. Chromium wasn’t designed for long-running server workloads, CDP consistency under automation, or removing identity leaks. So to build real browser infra for AI, we had to reshape it from the inside

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Mike @internalises

7 months ago

@JureSotosek Big moves from big Jure

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Mike @internalises

9 months ago

@Delmo_dev Mysterious

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Mike @internalises

9 months ago

@__Tkat__ Need to be income maxing at every opportunity

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Mike @internalises

10 months ago

@__Tkat__ You can just build things

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Mike @internalises

10 months ago

@hiiinternet

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seb @hiiinternet

a year ago

Yapping in the video below but if you're hiring engineers or interested in engineering roles / who's hiring here's the tl;dr: This software solves 1/ Problem for employers: Too few applicants = not enough to hire Too many = no time to review Either way, great candidates get missed. Inbound becomes noise. Via semantic search + boolean screening at scale you can surface candidates that are a good fit at scale. Results are 10x better than alternatives that are just keyword matching, we consider context. 2/ Problem for candidates: Even if you're great, your application is one of thousands. Recruiters skim resumes in seconds. No signal = no response. Because we make search + surfacing best talent extremely easy for employers you get better access to the roles that make sense. 3/ What we’re building: Structured flows for every inbound applicant Signal detection across resumes, portfolios, social links, GitHub, etc Auto-prioritization based on quality, not keywords 4/ Why it works for hiring teams: It turns unstructured inbound into ranked, high-signal leads. Founders or recruiters only review the best. More signal, less noise, no wasted time = more interviews. 5/ Why it works for candidates: You're not lost in a pile Your work gets parsed, scored, and shown based on quality Distributed to high quality teams Using it now to hire engineers in NYC and SF. Will expand to more roles + teams soon. DM if you want early access for hiring. If you're interested in who's hiring check out the job postings below: