0barney

almost retired

[0barney @0barneyx]

Easy 5 figs

[0barney @0barneyx]

Just for me
Pump coin will pump soon

[0barney @0barneyx]

@0xFar3000 Trading memecoin in is front of u damn

[0barney @0barneyx]

Ye man

[0barney @0barneyx]

Just for me
Pump coin will pump soon

[0barney @0barneyx]

Just for me
Pump coin will pump soon

[0barney @0barneyx]

Hi
Almost 7 digits
I’ll x3 my entire nw and get retired after that
Maybe open a tg or discord to build a little strong group

[0barney @0barneyx]

@Siriusdegex Lmao lets do this again dm

[0barney @0barneyx]

Create or trade I can do both
Print is so easy in this game if you dont please do something you’re fat and poor
Shame

[0barney @0barneyx]

Gud day at work

[0barney @0barneyx]

@0xFar3000 Printing on solana bru, dev and…

[0barney @0barneyx]

@0xFar3000 Dont need btc to make money bro

[0barney @0barneyx]

Yesterday’s gain is awful lmao almost hit 100 sol @Siriusdegex

[0barney @0barneyx]

@0xFar3000 @TheXeophon Man, really, we’re already

[0barney @0barneyx]

Humanity… or something like that

[0barney @0barneyx]

@Siriusdegex Idk who are you but Im ready for that shit if you speak english and have some liq to invest

[0barney @0barneyx]

I can start a 10k solcoin and bring this shit to 10M in less than 6 hours

[0barney @0barneyx]

@0xFar3000 @TheXeophon Dude this isn’t about jobs anymore, there are way bigger and more dangerous issues at play. It’s beyond us, man. I don’t think you realize.
we are totally broke in front of it, I feel comfy w my 500k nw but I'm a piece of shit

[0barney @0barneyx]

dude has my nw in shitcoins

[Hugo Martingale @HugoMartingale]

public port update

[0barney @0barneyx]

lmao

[Ansem 🐂🀄️ @blknoiz06]

dude has a BILLION dollar bitcoin long open

[shyamal @shyamalanadkat]

getting started with evals doesn't require too much. the pattern that we've seen work for small teams looks a lot like test‑driven development applied to AI engineering:

1/ anchor evals in user stories, not in abstract benchmarks: sit down with your product/design counterpart and list out the concrete things your model needs to do for users. "answer insurance claim questions accurately", "generate SQL queries from natural language". for each, write 10–20 representative inputs and the desired outputs/behaviors. this is your first eval file.

2/ automate from day one, even if it's brittle. resist the temptation to "just eyeball it". well, ok, vibes doesn't scale for too long. wrap your evals in code. you can write a simple pytest that loops over your examples, calls the model, and asserts that certain substrings appear. it's crude, but it's a start.

3/ use the model to bootstrap harder eval data. manually writing hundreds of edge cases is expensive. you can use reasoning models (o3) to generate synthetic variations ("give me 50 claim questions involving fire damage") and then hand‑filter. this speeds up coverage without sacrificing relevance.

4/ don't chase leaderboards; iterate on what fails. when something fails in production, don't just fix the prompt – add the failing case to your eval set. over time your suite will grow to reflect your real failure modes. periodically slice your evals (by input length, by locale, etc.) to see if you're regressing on particular segments.

5/ evolve your metrics as your product matures. as you scale, you'll want more nuanced scoring (semantic similarity, human ratings, cost/latency tracking). build hooks in your eval harness to log these and trend them over time. instrument your UI to collect implicit feedback (did the user click "thumbs up"?) and feed that back into your offline evals.

6/ make evals visible. put a simple dashboard in front of the team and stakeholders showing eval pass rates, cost, latency. use it in stand‑ups. this creates accountability and helps non‑ML folks participate in the trade‑off discussions.

finally, treat evals as a core engineering artifact. assign ownership, review them in code review, celebrate when you add a new tricky case. the discipline will pay compounding dividends as you scale.