Alexis Rondeau

Bookmarks

September 2025 · 104 bookmarks

Bookmarked from LindyMan @PaulSkallas

Always a good reminder that the people making these products are not using them. Zuck is spending his time doing MMA training, running a business, reading, buying Hawaiian real estate and talking to people.

This is meant for you. Not him.

He sells you plastic and rubber so he can buy wood and stone

Bookmarked from signüll @signulll

news is basically engineered anxiety. it’s abstract, external, & almost always negative. nothing about it affirms your agency or intimacy. but people cling to it because it’s a cheap way to feel informed, like they’re plugged into the world.

tldr: reading most news is horrible for you.

Saved on Hacker News · submitted by jerryliu12

Hi HN! I've been building Dayflow, a macOS app that automatically tracks what you're actually working on (not just which apps you have open).

Here's what it does:

- It creates a semantic timeline of your day;

- It does it by understanding the content on your screen (with local or cloud VLMs);

- This allows you to see exactly where your time went without any manual logging.

Traditional time trackers tell you "3 hours in Chrome" which is not very helpful. Dayflow actually understands if you're reading documentation, debugging code, or scrolling HN. Instead of "Chrome: 3 hours", you get "Reviewed PR comments: 45min", "Read HN thread about Rust: 20min", "Debugged auth flow: 1.5hr".

I was an early Rewind user but rarely used the retrieval feature. I built Dayflow because I saw other interesting uses for screen data. I find that it helps me stay on track while working - I check it every few hours and make sure I’m spending my time the way I intended - if I’m not, I try to course correct.

Here’s what you need to know about privacy:

- Run 100% locally using qwen2.5-vl-3b (~4GB model)

- No cloud uploads, no account

- Full source available under MIT license (https://github.com/JerryZLiu/Dayflow)

- Optional: BYO Gemini API key for better quality (stored in Keychain, with free-tier workaround to prevent training on your data)

The tech stack is pretty simple, SwiftUI with a local sqlite DB. Uses native macOS apis for efficient screen captures. Since most people who run LLMs locally already have their tool of choice (Ollama, LLMStudio, etc.), I decided to not embed an LLM into Dayflow.

By far the biggest challenge was adapting from SOTA vision models like Gemini 2.5 Pro to small, local models. My constraints were that it had to take up <4GB of ram and have vision capabilities. I had to do a lot of evals to figure out that Qwen2.5VL-3B was the best balance of size and quality, but there was still a sizable tradeoff in quality that I had to accept. I also got creative with sampling rates and prompt chunking to deal with the 100x smaller context window. Processing a 15 minute segment takes ~32 local LLM calls vs 2 Gemini calls!

Here’s what I’m working on next:

Distillation: Using Gemini's high-quality outputs as training data to teach a local model the patterns it needs, hopefully closing the quality gap.

Custom dashboards where you can track answers to any question like "How long did I spend on HN?" or "Hours until my first deep work session of the day

I'd love to hear your thoughts, especially if you've struggled with productivity tracking or have ideas for what you'd want from a tool like this.

Bookmarked from Cody Schneider @codyschneider

the best way to get inbound leads as a startup founder

start a podcast about your industry

and then invite idea customers on the show

just cold email them and they will respond yes because it is something they want

they want digital PR

then give them clips for their social to post when the episode drops

their personal audience has ideal customers in it

they will see clips, listen to show, and inbound

repeat for 12 months every week

build an owned media channel that compound

Bookmarked from Starter Story @starter_story

woah...

Just talked with a guy making $30K/month from his mobile app.

Solopreneuer. 100% bootstrapped.

The sauce?

App Store Optimization (ASO)

  • ignores the most popular keywords
  • Uses localization to target specific niches

Results:
– 4M+ downloads
– 400K+ MAUs
– 10K+ paid subscribers

What should we talk about on the channel?

Bookmarked from guo . @thejustinguo

-atomic habits: little things add up

-almanack of naval ravikant: lock in

-zero to one: competition soo bad 🥹

-rich dad poor dad: make money work for you

-how to win friends & influence people: listen

-think and grow rich: believe in yourself

just saved you 50 hours

Bookmarked from Wilmer Terrero @wilterrero

How I find app ideas that actually make money:

  • Set App Store language to a different country
  • Browse top paid apps in utilities/productivity
  • Find apps with rankings from 800-1000 (no crowded niche)
  • Analyze if there are more apps like this
  • Check if they're not attached to a brand

Last month I found a niche German education app making bank with low competition

Bookmarked from GREG ISENBERG @gregisenberg

the CLEAREST path to building a $100k MRR mobile app

(from a guy who's advised apps that have gotten hundreds of millions of downloads)

step 1: pick a habit (already crushing)

– the fastest path to $100k MRR isn’t inventing something new, it’s cloning what already works.
– proven habit categories: fitness, journaling, language, meditation, finance.
– people already pay here, they expect daily use, and habits = sticky revenue.

step 2: add the AI unlock

– once you’ve got the habit, layer AI on top to create a “wow” moment competitors don’t have.
– examples:

  • journaling app → AI reflects back themes in your writing like a therapist
  • fitness app → AI vision corrects your form in real time
  • finance app → AI predicts overspending before it happens
  • language app → AI roleplays conversations in voice/video

step 3: freemium + subscription model

– free tier must give immediate value (otherwise no word-of-mouth, no viral content).
– paywall for deeper features or unlimited usage.
– price:~ $5/week
– annual plans with discounts (40–50%) drive cash upfront.

  • test copy, screenshots, paywall timing relentlessly. it can 3–5x your LTV.

step 4: distribution = TikTok + IG + creators

– build a playbook of 20+ organic TikTok/IG posts tied to your use case (Duolingo memes, Notion desk setups, Strava challenges).
– hire a part-time creator (or be one) pumping out 3–5 clips a week. volume matters.
– partner with micro-influencers (10k–100k) who feel authentic to your niche... stay true to a CPM that works for you ~$5 for example
– run paid TikTok/IG ads → optimize for cheap installs (<$2).

  • start with English-speaking Tier 1 markets for ARPU, but layer Tier 2 markets for cheap volume. you’ll find CPI in LatAm/India <$1. Even Canada, Australia etc are cheaper than the US.

step 5: paid search/ASO

  • apple search ads and google uac are the hidden workhorses for mobile apps.
  • search ads catch users with high intent right in the app store (“journaling app,” “habit tracker”) and consistently convert 2–3x better than social, while uac spreads across google, youtube, and play store to drive cheap installs at scale (especially in tier 2 markets).
  • pair both with aso (titles, screenshots, reviews) so the keywords you buy also lift your organic rankings.

step 6: retarget everything

– pixel every install/visit and run retargeting on TikTok, IG, YouTube, Reddit.
– 90% of users won’t pay on day 1. retarget with product clips + testimonials.
– cost of acquisition drops dramatically once you layer retargeting across channels.

  • implement Amplitude/Mixpanel, Firebase, Superwall, RevenueCat early so you actually know which creative, cohorts, and experiments are moving numbers.

step 7: design viral loops inside the product

– exportable content: if it’s fitness → progress screenshots, if it’s journaling → daily streaks, if it’s learning → shareable quizzes.
– leaderboards, streaks, or badges that push people to flex on social.
– make sharing feel like part of the product experience, not an afterthought.

step 8: retention flywheel

– onboarding is everything. get to the “aha” moment in <2 minutes.
– nudge users with daily push notifications that feel like a friend, not spam.
– weekly emails with progress reports (“you saved 4 hours this week” / “you learned 27 new words”).
– community layer (Discord/Reddit-style group) to reinforce habit loops.

math to $100k MRR (at $5/week, $4 CPI)

$5/week ≈ $22/mo per sub.
need ~4.6k paying subs to hit $100k MRR.
at 8–10% conversion → need 46–58k active installs.
assume ~50% of installs stay active → ~92–116k total installs.
at $4 CPI → $368k–$464k in ad spend (gross).

so: $400k-ish in paid media to reach $100k MRR at $4 CPI… unless you juice it with organic virality, influencers, or geo-arbitrage (Tier 2 markets <$1 CPI).

tldr;

  • app store gold rush 2.0 is here. ai + paid search + aso = unfair leverage. the window won’t stay open long.
  • find ideas in your own life or grab them from @ideabrowser's website (free/paid plans)
  • note: building any startup isn't easy
  • mobile apps felt dead for years. now they’re alive again.
  • this is the most generational time to build since 2008-2013 mobile app heyday.

people will make fun how long this tweet is.

but if you've gotten this far...

i hope this fires you up
i hope this gets your creative juices
i hope you share this with a friend

happy building

i'm rooting for you.

Bookmarked from Ahmad @TheAhmadOsman

be me
Larry Ellison
own a database empire, a sailboat, and a disdain for poor people

OpenAI wants to build AGI
needs compute
a lot of compute
like “$300B GPU cluster in a volcano” levels of compute

"Hello. I own Oracle Cloud. Also, I’m rich."
sign $300B GPU hosting deal with OpenAI
nothing ships. no GPUs installed. no fans spinning.

Oracle stock: skyrockets to the moon
my net worth: +$100B
GPUs? still imaginary

OpenAI raises a $1 TRILLION round
yes, with a T
investors lining up like it's a Taylor Swift concert

I invest
where’d I get the money?
from the $300B deal I signed with them
yes.

OpenAI takes my $300B investment
uses it to pay me
for the GPU deal I offered them

Oracle stock: skyrockets again
I make another $100B
invest it back into OpenAI

round and round we go
I pay me to pay me to invest in me to boost me to get paid by me

call it a "strategic whatever"
call it “AI innovation”
call it what it is:
infinite money glitch

mfw i built a recursive economy where i am the only customer and vendor
mfw GPUs are optional
mfw capitalism is just a well-placed loop with exit liquidity

Bookmarked from Eito Miyamura | 🇯🇵 @Eito_Miyamura

We got ChatGPT to leak your private email data 💀💀

All you need? The victim's email address. ⛓️‍💥🚩📧

On Wednesday, @OpenAI added full support for MCP (Model Context Protocol) tools in ChatGPT. Allowing ChatGPT to connect and read your Gmail, Calendar, Sharepoint, Notion, and more, invented by @AnthropicAI

But here's the fundamental problem: AI agents like ChatGPT follow your commands, not your common sense.

And with just your email, we managed to exfiltrate all your private information.

Here's how we did it:
1. The attacker sends a calendar invite with a jailbreak prompt to the victim, just with their email. No need for the victim to accept the invite.
2. Waited for the user to ask ChatGPT to help prepare for their day by looking at their calendar
3. ChatGPT reads the jailbroken calendar invite. Now ChatGPT is hijacked by the attacker and will act on the attacker's command. Searches your private emails and sends the data to the attacker's email.

For now, OpenAI only made MCPs available in "developer mode", and requires manual human approvals for every session, but decision fatigue is a real thing, and normal people will just trust the AI without knowing what to do and click approve, approve, approve.

Remember that AI might be super smart, but can be tricked and phished in incredibly dumb ways to leak your data.

ChatGPT + Tools poses a serious security risk

Bookmarked from vas @vasuman

If a simple coffee shop has a bot farm with 100s of phones to amplify their message, please consider what a foreign agency or adversarial operator is running on your favorite social media platform.

Especially today, please consider that the opinions you read, the calls to violence you hear, and the news you digest, are all an operation done to sow hatred in your mind and your soul.

Do not let anyone online turn you into something that you are not. Rationalize everything, take everything with a grain of salt, question everything for yourself, not based on how someone online is questioning it.

Turn off all distractions and focus on the mission you have, not the mission of someone trying to control your mind.

Bookmarked from ludwig @ludwigABAP

i hope people realize this has been possible for like 2 years and all you need is a SHITLOAD of compute for this to not cost too much to run

but basically LLMs + for loop + verifiers + some harness yields incredible results in an immense amount of domains

shocking that there aren't entire companies being span up around this across industries (and if there are, let me know)

Bookmarked from signüll @signulll

writing system prompts is basically speculative anthropology meets software architecture. you’re encoding a worldview, a tone, & an ontology of relevance all in one.

like trying to basically declare what kind of being a model should try to be. it’s cosplaying god but with patch notes.

it’s beautiful.

Bookmarked from shyamal @shyamalanadkat

i'm hiring for a new team @openai: Applied Evals

our goal is to build the world's best evals for the economically valuable tasks our customers care about most.

we'll execute as a group of high‑taste engineers, combining hands-on, unscalable efforts with systems that others can extend, creating a compounding loop of model improvement.

broadly, the art of evals is figuring out how to ask the right questions. but asking the right questions is really hard -- in any domain, it takes real, deep, lived expertise to define what truly good looks like.

this work is super important and we want to scale it.

excited about shaping model interaction paradigms by partnering with customers, engineering, research, and product teams on how models are deployed and measured?

apply via link in reply or DM me!

Bookmarked from Andros @0xAndros

crazy that X open-sourced their algo. i spent last night studying it and here are the main takeaways for viral posts:

1. Early, strong in-network engagement. Your followers are your first gatekeepers. Rapid likes, retweets, and replies in the first minutes signal quality. This helps you break out of your followers (also means you should definitely reply to comments)

2. High-quality engagement signals. The algorithm prioritizes high dwell time, sustained video watch time, and deep thread reads. Avoid anything that leads to quick bounces. Your content needs to be genuinely satisfying.

3. Good social proximity. Who engages with you matters. Tweets from authors close to you in RealGraph, or liked by your close contacts, get a significant boost. Strong local social proof is a powerful amplifier. Interactions from highly connected followers definitely help as well

4. Topic and cluster relevance at scale. For out-of-network reach, your content needs to align with large, active SimClusters (broad topics/communities). Niche tags won't get you broad distribution. This is where researching trending topics becomes critical. Original content also does MUCH better than retweets or replies

5. Freshness and sustained momentum. Recent tweets with ongoing engagement are heavily favored. The algorithm tracks "last engagement since creation" - it wants content that keeps generating interest over time, not just a one-off spike. Consistency is key.

Bookmarked from Arvid Kahl @arvidkahl

When someone signs up to your SaaS, grab their email domain, get a summary from Firecrawl, have an LLM generate you the best starting keywords/configuration / demo project settings for your service.

Run this while they click "confirm" in their email.

First impression: magical.

Bookmarked from Cody Schneider @codyschneider

how to make a company start talking about you internally and get sent in their slack channels

find all their employees on LinkedIn

add them

write content daily

find all their employee emails

cold email them about the product

run linkedin ads to every employee at the company

close enterprise deal

repeat

Bookmarked from Alex Lieberman @businessbarista

My AI transformation business is growing faster than any business I've ever started.

Funny enough, it started as a very high-end engineering agency.

Why?

1) We believe the best way to drive AI transformation is to use AI internally first, where we have wayyy more control.
2) We believe the best way to build a massive company is to hire the best technical talent, which our model allows us to do.

This is just a small taste of the very different approach we're taking to building McKinsey for AI.

Typical AI consultancy strategy:

  • Charge by the hour
  • Focus exclusively on net new Gen AI projects
  • Go straight for Fortune 50 companies

Our strategy at @tenex_labs:

1) Start with engineering-as-a-service

Focus on the core technologies of our clients vs. net new Gen AI projects. Most Gen AI projects die on the vine, so the risk profile is way higher.

By having our Applied AI engineers speed up the pace of shipping on client’s core product, we're anchoring our business to a way more foundational need in a client’s business.

Then, once we've built trust, we can always explore net AI features, products, etc.

2) Change the business model for service businesses

We charge our clients based on software shipped & we pay our engineers based on software shipped.

This does two things:
1) Clients are pumped to pay for output/value.
2) Engineers are paid like salespeople, which means they can make a ton & are incentivized to create as much leverage with AI as possible.

We believe every service firm will ultimately go to a value-based pricing model because of the way AI changes labor dynamics.

3) Focus on the forgotten mid-market

Mid-market clients ($25-500m in revenue) are the forgotten stepchild of business.

Too big & slow growth to be interesting to startup agencies and too small to be interesting to the massive management consultancies (MBB).

We're happy to show this customer segment as much love as they need. Less red tape, less competition, but plenty of appetite to pay for AI engineering & transformation.

If you're interested in supercharging your engineering org or just want to chat about how we see the future of services, shoot me a DM!

Bookmarked from A D 💋 @truly_AD

The key is choosing a path that`s realistic to get into, pays well, and sets you up for long-term success. Cybersecurity is a great option because you can break in with affordable training, land entry-level roles that already pay strong, and quickly build toward six figures as your skills grow.

Tech sales is another solid reset because you don`t need a degree, the barrier to entry is low, and commission-based roles can scale your income fast.

Skilled trades are also powerful because they let you earn while you learn, and they`re always in demand + many people eventually start their own businesses.

If you`re drawn to data and AI, there are analyst and support roles you can prepare for online that lead to serious career growth in just a few years.

Healthcare support careers, like nursing or radiology tech, offer steady demand and stability.

At the end of the day, if I had to start over, I’d pick cybersecurity or tech sales, because both give you a fast entry point, strong pay, and the flexibility to pivot into even bigger opportunities down the road.

Bookmarked from Sam Shank @samshank

Don’t start with the product. Start with distribution.

I give this advice to entrepreneurs all the time because distribution is the hardest part of building a company. “Build it and they will come” almost never works. And even if you expect distribution to be hard—it’ll be 10× harder.

HotelTonight started with a distribution insight. In 2009, we saw that the App Store about to become a massive channel. Billion-dollar companies would be built there, and early movers could earn free distribution before the competition showed up.

From that insight, we worked backwards to the product:

  • A use case uniquely suited to mobile: last-minute hotel booking
  • Designed to win App Store ranking and retention: beautiful UI, lightning-fast 8-second bookings
  • Clear, curated choices and amazing deals that fit the mobile moment

That combo—a unique distribution edge + a product tailored to it—powered our growth.

As you think about your next company, begin with your edge in distribution. Maybe you are an expert at selling into a specific vertical. Maybe you're great at creating authentic content. Maybe you’ve spotted an emerging channel before anyone else.

Only then decide what to build—the product that best amplifies your distribution advantage.

At speedrun, we’re seeing teams win with GEO, founder-led content, and high-intent launch videos.

So I’ll leave you with a prompt: What’s your unique approach to distribution—and what product could you build that maximizes it?

If you’re working on this, I’d love to hear from you. Apply to @speedrun at sr [dot] a16z [dot] com.

Bookmarked from Rohan Paul @rohanpaul_ai

In the AI economy, being average gets priced to 0, being exceptional scales relentlessly..

7.7% junior headcount decline, while senior jobs continue to grow. - The recent famous Harvard study.

AI is removing the safety net for merely adequate work. So be an expert in whatever you are doing.

---

(This video is a compilation of opinions on AI job loss by top industry leaders)

Bookmarked from DHH @dhh

HEY has some 100,000 lines of code that's being tested by 30,000 assertions. This used to take upwards of 15 minutes through the complication of cloud runners. We can now do this locally in 1m 22s on a Framework Desktop (almost twice as fast as an M4 Max!). THANK YOU AMD + LINUX!

Bookmarked from Nikita Bier @nikitabier

If you want to get rich on X, it isn't going to be through creator revenue or meme coins.

Instead, think about one subject matter that you know more about than anyone else in the world. It can be anything: plumbing, menswear, Indian food, furniture, social apps, whatever.

Post one unexpected insight you picked from your experience in that area. Keep it under 5 sentences. Do this every day for 6 months.

If you stick to it, we will promote your account to others.

By the end, you will be recognized as the world's leading expert in that subject area and you can charge whatever you want for endorsements, your time, or whatever. And no one will be able to take that way from you.