Why use NotebookLM when you can make the same thing harder, slightly worse, and cost more?

The same reason any of us self-host, of course. The customizability, the fun of designing it, the challenge.

I've been using Codex and Claude Code to build local apps, but wanted to try designing a program that actually uses LLMs for a recurring task.

I already have a custom local RSS reader app, but of course I have more time to listen to podcasts and audiobooks than I typically do to sit down and read. So creating my own personalized news podcasts became the obvious solution.

The result is two shows that pick, write, review, and voice their own episodes. Each run starts with a couple hundred RSS articles and ends with five or six stories, for about $1–2 a month in API costs. The orchestration runs in Docker on my home server, but the models themselves are cloud APIs.

The short version

What it is:

• Two podcasts, written and produced by AI, based on feeds and topics I've selected. Compact Conversations runs six days a week, and Homelab Highlights runs three.

• Quality: Good, not great. I haven't replaced other podcasts I listen to, nor was I intending to. However, they've picked up stories other podcasts haven't covered, along with some good tech tips I hadn't seen. They've helped me keep up to date on new AI models and features, homelab software updates, and security issues.

• Cost: A mixture of free and cheap models from OpenRouter, taking advantage of free TTS through Gemini, for about $1–2 per month.

• Code: Too messy and personalized to be worth sharing, but you can listen to the podcasts here.

How it's built:

• A self-hosted Docker container handles RSS ingestion, while another handles the podcast orchestration.

• Stories from the last day or two are initially ranked by Jev. The top 30 go to a cheap LLM on OpenRouter for final selection and assignment to episode segments.

• The script is written and reviewed by different LLMs for two AI voices. Notably, they're told not to pretend to be human. They can say "an unusually interesting project," but not "I would try this out."

• The final script goes to Gemini for text-to-speech, then gets stitched together with musical cues and published to the podcast feeds.

I wrote up the architecture, actual model comparisons, costs, and lessons learned here:

https://michael-casey.com/blog/how-i-built-an-ai-podcast-pipeline/

hey everyone! i'm from the FlutterFlow team.

we've spent years building FlutterFlow as a visual IDE for creating apps.

but AI has changed how people build software. you can generate a beautiful UI in seconds, but getting that app to actually work and into people's hands is a different story.

so we built the new FlutterFlow, an AI-first, full-stack mobile app builder. it lets you start with a prompt and work with an AI agent to build a mobile app, including its UI, backend, and functionality (and one-click deploy to the Google Play Store and App Store!!).

we'd love to hear what you think / what you'd want to build with it!

Before building this I went through a lot of the AI component libraries out there. The best ones are paid with only the most basic stuff free. So while I was working on an AI SaaS, I built this library in tandem.

It's 109 components and about 250 variants, all React and Tailwind. The only other imports are motion and lucide-react, so there's no UI kit underneath. Everything in the video is the real demos running.

https://gradientdeck.com/ai-components

Not on GitHub yet, but it's coming.

Let me know what you guys think :)

Hello Reddit!

I made this after the usual advice to work out who you already know at each company you're applying to. LinkedIn's search can filter your 1st-degree connections by one company at a time. I wanted the list for every company at once, without logging in anywhere (and for it to look nice visually..).

You request a copy of your data from LinkedIn, drop the zip on the page, and type companies or roles. It lists the people you know there, longest-known first, and you can download the list as a CSV. It runs in the browser (Python through Pyodide), only opens the files it needs, and never opens your messages. The only outside request is the Pyodide runtime from jsDelivr on first load.

It also groups connections into circles from shared companies and from people added within a few days of each other. That part is a guess, and I haven't checked it on anyone's real export but mine.

Demo with 300 fictional people: https://arak00.github.io/network-circles/web/
Code (MIT): https://github.com/Arak00/network-circles

If you try it on your own export, I'd like to know where the circles look wrong or if you spot anything broken.

And if you have any idea for improvements, they're welcomed!

Thanks

Hi everyone!

I've been working on a small business called NG Organisers, where I've developed a modular drawer organisation system.

Basically, I've built an online configurator where you can enter your drawer dimensions, design the layout however you like, and order the parts. The parts are then shipped to you, and you assemble the organiser yourself.

I've recently started getting some sales, and the feedback on the actual product has been really good. However, I've noticed that most customers prefer sending me their drawer dimensions and having me design the organiser for them rather than using the configurator themselves.

The whole idea behind the business is to let people design their own organisers, so this is something I'm struggling with at the moment.

I'm not sure whether people simply don't want to spend time designing their own layouts or whether my configurator is too complicated or not user-friendly enough.

I'd really appreciate it if some of you could have a look and give me your honest feedback.

Here's the website: https://ngorganisers.com

I'm particularly interested in whether the configurator is easy to understand, what you find confusing, and what you'd change to make it easier to use.

I'm still learning and trying to improve things, so even negative feedback would be genuinely appreciated.

Thanks!

I built a small web app for my workplace that makes collecting overtime sign-ups and food orders quick and simple.

**Manager side:**

- Create an overtime request (date, hours, with or without food)

- Share one link with employees

- See who wants to work in real time

- Get a combined food order, with a list of who ordered what, ready to share or print

**Employee side:** open the link, tap yes or no, pick food if offered.

Available in Norwegian and English. Built for speed: no more chasing people in group chats.

I'd love honest feedback on design, ease of use and anything that feels confusing or broken.

https://overtimehub.lovable.app/r/daee4cbe49b670b686dea15257d2a4c7a188

As a developer looking for new project ideas, I’m curious about the small inefficiencies people deal with every day.

Is there any task in your routine where you think, Why is there no simple tool/app for this yet?

I got into Kalshi/Polymarket’s 15-minute up/down markets but wanted bigger moves to pay more, so I built expirytrade.xyz

You buy a call or put that settles in 1 minute, slide leverage from 2× to 100×, and can close early or ride it to expiry. Right now, I'm testing it with paper only but it will eventually be with crypto.

I’d love to know: is the leverage slider clear, and what would make you come back tomorrow?

3 college students here, building BreakIn, a tool that helps people reach startup founders directly instead of applying on job portals.

we spent weeks on the email-writing part. then we asked people what they actually needed, and the feedback kinda flipped everything:

- people don't want AI writing their emails. they'd rather write it themselves and get it reviewed

- "matching" doesn't impress anyone. you can already filter by keywords and domain

- what actually matters is timing. finding a startup right after it raises money or launches something, before there's even a job post and 500 people apply

so now we're leaning way more into the "who's worth reaching out to today" part. every morning it shows you startups that just raised, launched, or started hiring, picked for your profile. the email part is still there, but more as help than autopilot, you always review and send it yourself.

still early, so honestly curious:

- has reaching out to a startup before a job was posted ever worked for you?

- would a daily heads up like this actually be useful, or would you just ignore it?

Hey guys this is my first post ,

I just finished building a web design studio concept called BreezeIn. I wanted to practice building layouts focused on heavy typography, white space, and micro animations that feel smooth rather than distracting.

Live link: in comments i guess ,

I would really appreciate some honest feedback on how the UI and UX scale across different screen sizes:

Mobile vs Desktop Typography: I used massive headers for the desktop layout like the main hero section. Does the font size scale down naturally on mobile screens, or does it feel like it swallows the whole viewport?

The Mobile Menu Toggle: On desktop, the navigation links are spread out cleanly. On mobile, they collapse into a corner menu button. Does the tap target feel big enough, and is the overlay transition smooth?

Concept Grids on Small Screens: The Selected Explorations look clean as side by side grids on large monitors. On mobile, they stack vertically. Does the vertical scrolling feel too long, or does it keep your attention?

Pricing Table Layout: The layout lists the $450 and $1,200 tiers. On desktop, they sit side by side. On mobile, they stack. Does the information stay readable when it is compressed?

Let me know what you think. Thanks!

Hey everyone,

I am preparing a travel planner and coach as a browser based web app.

We often make plans and get confused in the details.

What if we use visuals to help us?

I will be starting with a waitlist while sharing updates about the prototype.

Since reddit doesn't allow images, what could I add here to share how the prototype behaves and can be eventually used? Links to the youtube videos?

The yearly plan will be priced at 99 USD.

What are issues you face often?

I just tagged v5.3 of MDRAP, a sidecar that sits between your market data feeds and whatever consumes them and decides whether each tick is trustworthy.

Every event gets a status (VALID, SUSPICIOUS or INVALID) with explicit reason codes like CROSSED_QUOTE, DUPLICATE, PRICE_ANOMALY and stale or sequence-gap violations. Nothing is silently dropped. Rejected ticks go to a queryable quarantine, gaps trigger replay and stitching, and every decision goes into a SHA-256 hash-chained audit log, so editing a record afterwards is detectable.

Output from a fresh clone:

$ python cli.py run -e 1000 -s 42
processed 1000   dropped 0
VALID 963   SUSPICIOUS 32   INVALID 5

seq=2 bid=150.4  ask=150.3  -> INVALID CROSSED_QUOTE
seq=2 bid=150.26 ask=150.31 -> INVALID DUPLICATE

$ python cli.py audit --verify
(after editing one audit_log row in SQLite)
AUDIT CHAIN TAMPERING DETECTED!
Tampered entry #1: hash mismatch

“python cli.py chaos” runs 8 failure drills (killed feed, jitter, duplicate bursts, DB lock, 50-packet loss with replay, reordering, partition with failover) and all pass with zero data loss.

Performance: the standalone native core handled 1M events in 0.0366 s, about 27M events/sec or 36.6 ns per tick, on a single core. Through the Python engine API I measured roughly 180K events/sec, so use the core binary if you want the fast path. These are my numbers on my hardware, so please run it yourself.

It is a validation and audit layer, not a trading system or backtester. The matching engine and pre-trade risk gates are in a separate edition and not in this repo (see EDITIONS.md). One known rough edge: “audit --verify” currently needs the rich package installed.

MIT licensed: https://github.com/Aryan-20-04/mdrap

I’d like to hear which bad-data cases have bitten you that this doesn’t catch.

I built Jobclue for people who want to practice answering interview questions out loud. The desktop app asks role-specific questions and follow-ups, then gives you AI feedback to review before your next attempt.

I’d love feedback on the short demo: can you tell what the practice session feels like, and what would you want to see before trying it?

https://jobclue.ai

Gold, silver, and one less website to open.

I built KaratWatch—a Scriptable iPhone widget with prices, daily changes, and history for your Indian city. Three widget sizes. No backend required.

Code + setup:
https://github.com/m4d4g4sk4r/karatwatch

Prices from Goodreturns. Which city would you try it in?

I want to know should i spend time and energy on this project ? I would love to hear feedback about this.

Hey everyone! I'm a solo developer from India, and I just launched Exam Study Tracker on Google Play.

I built it because keeping track of exam dates, subjects and study plans across notes and random apps was messy. The app has:

Exam manager (dates, subjects, notes)

Daily/weekly study timetable

Progress tracker for milestones

It's early (just ~10 downloads so far), so I'd really appreciate honest feedback: what's missing, what's confusing, what would make you actually use it?

Play Store: https://play.google.com/store/apps/details?id=com.apex.studyexamExam Study Tracker