u/Monolikma

I'm planning to start my med school in Belarus next year. I want to learn Russian before joining the university. They'll teach Russian in university too. But I heard it won't be enough to do clinical in 3rd year.

I'm using duolingo for now and in level 10. But I feel like it's nor enough. I want suggestions with learning language more quicker and I want to achieve a state where I can atleast hold basic conversation.

I want suggestions on apps or youtube channels or any other effective ways

Thankyou

Hey there, I've been browsing for a while and have been playing a lot with Duolingo but it doesn't seem to really help with the grammar so much. I also tested things like Anki but it was quite technical and ended up feeling like just a bunch of flashcards. Any recommendation from what worked for you would help. thanks!

We built Patricia, an AI teammate that works inside your communication channel for SMEs and agencies. You get $50 every time someone you send turns up to a demo, whether or not they ever buy. Then 20% of everything that account spends, for 12 months. We bill for work done rather than per seat, so that 20% grows as the account matures: a company that properly adopts her runs about $650 a month. The referral compounds instead of decaying. Link to the program in the chat.

Give me your feedback if any ✌🏻

Hey everyone - sharing with the builder community:

We noticed a clear gap in the market between comfyui production quality on the one side and builder struggling to monetise on the other side. So we're opening 5 paid contests for ComfyUI builders starting June 1. Two weeks each, $20K prize pool across the season, every contest solving a real customer pain we've been tracking.

Submissions open June 1, but the 5 briefs are public today at runflow.io/contests. If you want a 6 day head start to read them and decide whether to build, here you go.

How the model works:

- We talk to companies stuck on real production problems (current cohort: performance marketers losing whole days to manual ad-variant work).

- We turn that pain into a brief with a hidden test set and auto-graded acceptance criteria.

- Builders ship workflows against the brief.

- The winning workflow goes live as a public API on our marketplace. No paywall to enter the contest, no paywall to use the winning workflow once it ships.

Prize per contest: $1,650 + $500 credits to 1st, $500 + $100 to 2nd, $200 + $50 to 3rd, plus $50 credits to the next 20 valid entries.

The 5 contests in order:

1. Brand-consistent ad variants (Jun 1 -> Jun 15)

2. Static-to-video ad upgrade (Jun 15 -> Jun 29)

3. Static to social ad creative (Jun 29 -> Jul 13)

4. Catalog hero photography (Jul 13 -> Jul 27)

5. UGC-style ad creative (Jul 27 -> Aug 10)

What you can do already:

- See high level what the 5 contest will be about

- Join the builder Discord to ask brief questions, hang out with other entrants, and get pinged when contest #01 opens: discord link on the contest page itself

On top of the price we will also actively promote the workflow once live as the goal is to go to production with it. The winner of each will get exposure to the market and client since the builder name will be highlighted. If this initial program is successful we will run more of those.

Again we want to be the bridge for better quality workflows for production and helping builders monetise their amazing work.

AMA below if anything looks unclear.

Day 2 of a 30-day public hackathon. Yesterday I shared the smart-resize + quality control pipeline we built. Today: object removal benchmarks.

Quick context for anyone catching up. We were producing 100K AI images a month at our previous company (BetterPic) before the commodity hit our revenue. So now we're rebuilding from the same core skill: production AI image workflows that hold up at scale. The 30 day hackathon is me posting every day what we test, what breaks, and what we ship next.

Today's test: object removal on 3 production style images. Same mask, three different tech. Our internal pipeline: smart object removal, against Nano Banana Pro and GPT Image 2 Pro.

Test 1: a glass on a book

- Our comfyUI workflow: glass removed cleanly, the desk continues underneath where it should

- Nano Banana Pro: glass removed but the output came back slightly zoomed, different aspect ratio

- GPT Image 2 Pro: glass removed but the model invented text on the book label. It now reads "Jorlant" (nonsense)

https://preview.redd.it/34la6plfp52h1.png?width=1870&format=png&auto=webp&s=29468dd5cc544aab1327506d5c67adbd0aa6bb1c

Test 2: a person in front of a tower

- comfyUI workflow: clean, integrity of building in the background is good

- Nano Banana Pro: tighter crop, frame doesn't match input

- GPT Image 2 Pro: person removed but the model added a SECOND tower in the background that wasn't in the source

https://preview.redd.it/y5dkq5ctp52h1.png?width=1858&format=png&auto=webp&s=ab757a4e25e8d0740e50fb7f0baf4aa2186c3e6f

https://preview.redd.it/wfjstnqtp52h1.png?width=1024&format=png&auto=webp&s=9cddcc1f0306eee3e082d649a7b2ed54e26f7c62

Test 3: croissants on a plate (product photo)

- comfy workflow: croissants removed, same plate

- Nano Banana Pro: croissants removed but the plate came back bigger and slightly different style. Wrong SKU.

- GPT Image 2 Pro: less obvious plate swap, rim subtly changed

https://preview.redd.it/ui5z0ni1q52h1.png?width=1872&format=png&auto=webp&s=38935517723847b888459418c49afbcfde48405c

Three failure modes that came out consistent across every test on the generalist models:

1. Frame drift. Closed-source models don't respect input dimensions. Output is zoomed in or out, sometimes a different aspect ratio entirely. Breaks any downstream layout pipeline.

2. Hallucination. When the masked area covers content the model has to reconstruct (like the book label under the glass), generalists invent plausible but wrong details. The "Jorlant" text didn't exist in the source.

3. Object substitution. Even items not in the mask come back changed. The croissant plate became a different plate. Generalist models regenerate the whole image with the masked area replaced, so everything else gets repainted in their style too.

What this means for the business:

For one-off creative work, the generalists are fine. Sometimes their hallucinations look better than the original.

For production pipelines (think: an ecommerce brand running 10K product photos a month), these failure modes are dealbreakers. You can't ship a catalog where 5% of images have slightly-wrong plates or invented text. The cost of QC at that scale is more than the cost of the generation itself.

That's the wedge we're building on. Closed-source models are built for plausibility. Production pipelines need exactness at scale, without drift. Pipeline 1 is Runflow, the internal stack we're working toward open access for builders.

My next test will be for outpainting tech. Curious where the failure modes show up there.

For anyone running production AI pipelines at volume: what's your tolerance for these failure modes? And what's been your workaround?

(I also recorded a Loom video to showcase the test but not sure if that's allowed to share here in the post)

Was at a small founder dinner last week. 2 hours, 13 people, one of them runs a company that went from $120M to $400M ARR in 18 months.

The whole night turned into one argument: who's actually going to eat your lunch in the next 3 years.

Most people in tech have a pet answer to this. The 18-year-old kid on Lovable. He's gonna leave, build the next thing, ship it before you can react.

The CEO running $400M ARR cut that take in half in about 30 seconds. He said the real threat is the top 5% of your own employees. The ops lead who already understands the customer. The senior engineer tired of the roadmap. The PM who knows exactly where the broken parts are.

Multiply them across the economy and you have a million people who can build instead of buy. The guy who decides he doesn't need a financial advisor and writes one for himself. The team at your competitor that finally got tired of the backlog and shipped the feature on a Friday using claude code.

A million threats walking around with the same tools you have.

Regulation buys you a few years if you're in healthcare or finance. Then Anthropic spins up a vertical team and the moat expires anyway.

Speed is the only thing that compounds

Same CEO said his team runs 22-23 experiments every single week. B2B websites live in 2 hours. Photo shoots replaced with AI. Stock video gone. Agencies gone.

He just invested in a 5-person company called Schematic (Lovable for hardware). They don't have Slack. They WhatsApp and they build.

Most companies cannot match that pace because the old product loop is broken. Quarterly planning, requirements meetings, PMs guarding the roadmap, ops sitting at the bottom of the backlog with 120 unblocked requests. That loop was always inefficient. With AI in the mix it's malpractice.

The new shape: ops person yells at a customer, opens claude code, ships the patch. Engineering reviews for safety, design reviews for fit, ship same day.

You can't transition. You shock or you don't.

Spiciest take of the night >> AI adoption is binary.

Another founder pushed back. He said his company is trying. They identified 30 power users. Rolling claude code to engineering. Soft transition.

The $400M CEO said no, you're going to lose. The real shift looks like this: from Monday, the whole company operates on weekly roadmaps. No quarterly anything. Experimentation meeting Monday morning. Marketing runs through AI too. Some people will quit. That's the point.

He's already done it. Some people did quit. The ones who stayed run those 22 experiments a week.

The reason a soft transition fails is that the old definition of a "good week" pulls the average back down. Half the company shipping fast and half the company writing PRDs averages to "still slow." A shock resets the baseline.

What you hire for now

90 minutes with every hire, junior or senior, no exceptions. With a bunch of filter questions:

one of the favorite interview question: "If we needed to take this company's revenue to zero in 10 minutes, how would you do it?"

99% of people fail. They reach for "shut down the servers" and immediately get cut off because invoices already went out, payments still flow. The best answer he ever got was a junior dev who said "I'd push the opacity of the enrollment button to 100%." One-line code change that kills the funnel instantly.

The point of the question is watching how someone thinks with no template to copy.

The other filter: taste. Defined narrowly. The ability to pick the best output out of 10 that AI just generated for you. Pure judgment.

He once hired someone after a 10-minute monologue about handmade Japanese fishing baits. Anyone who can speak with that kind of obsession about anything has taste.

What this confirmed for me

We run something small and fast, not a $400M company. The dinner didn't trigger a pivot. It clarified bets we were already half-making.

>> Honest reflection on each piece from that evening

Weekly cadence already exists: Our CTO killed quarterly planning the day we shifted in March. Weekly roadmap, weekly experimentation review, ship every Friday. The credit isn't mine. The dinner just made me realize how rare that operating shape still is, even at much larger companies.

Hiring filter is the real upgrade. Adapting the "take it to zero" question for our loop. The bigger thing we'll be filtering for now is the system thinker who ships end-to-end. A generalist who treats the whole product surface as their canvas because AI tools collapsed the cost of crossing disciplines. Taking marketing as an example, nowadays once the design system, copy style and, strategy files are well made in a central place, the deployment end-to-end becomes extremely fast. The output expectation has 10X'd

Now combine that with the taste filter (the ability to pick the best output out of 10 AI generations) and you get the rarest profile on the market right now. If you have one of those people on your team, protect them. If you have two, you can outpace companies 50x your size. If you have zero, that's your only open hire.

AI tools daily was already in place. Been operating this way since day one (our pivot in March). What I'm building on top is a centralized skills repo: every team member commits prompts, marketing skills, replicable systems back into one shared codebase. SEO audits, ad creative, copy edits, churn, all version-controlled. The early commits are rough. Whole thing is still wonky right now. But the compounding shape is starting to show. In 1-2 months I expect this repo to be what lets us punch 10x our weight.

The platform-shift bet is the one I'd make again from scratch. The companies winning this cycle will be the ones putting building tools directly into the hands of the people who already understand the customer.

Same pattern is going to play out in every vertical. The person who already touches the customer is the one who gets the building tools. The "you brief us, we build" services layer collapses. The platforms that win are the ones giving those people a one-click way to ship their work to a market.

Curious if anyone here is running this kind of binary shift inside their company. What's working, what's breaking, what you wish you'd done sooner.