Empowering coders with AI tools, low-code solutions & expert tips. Beginners to pros—build smarter, faster, and better with https://nitter.gq/t.co/AoF95Zlibz! 💻 #Coding
Joined December 2024
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Programmers.App retweeted
The MOST obvious (but REALLY good) STARTUP ideas right now:
1. Zestimate for company data (what your data is worth to an AI lab)
2. Google Analytics for agents (see which agents visit your site and what they want)
3. Y Combinator for 1 person companies (back solo founders running a team of agents)
4. Okta for agents (who each agent is and what it's allowed to touch)
5. Marie Kondo for your company's data (clean it up so agents can use it)
6. FICO for agents (a trust score before an agent can spend money)
7. Geico for agents (insurance for when an agent makes an expensive mistake)
8. Datadog for agents (see every step your agents took)
9. Twilio for agents (phone numbers and texting for agents)
10. Upwork for agents (hire an agent for a job instead of a freelancer)
11. ESPN for AI (every model launch covered like a big game).
12. Shutterstock for robot training videos (get paid to film yourself doing chores)
13. Credit Karma for what AI knows about you (see it, fix it, delete it)
14. Norton for AI scams (protect your parents from fake voices and emails)
15. PayPal Buyer Protection for agent purchases (fixes it when your agent buys the wrong thing)
16. Geek Squad for AI (set up personal agents for families and small businesses)
17. Dell for private AI (AI in a box for firms that won't use the cloud)
18. Carfax for used GPUs (a health report before you buy secondhand)
19. Airbnb for idle GPUs (rent out computing power you're not using)
20. Rotten Tomatoes for AI models (real reviews instead of benchmarks)
21. G2 for skills (find the best skills for your agent)
22. Dropbox for your AI memory (take what your agent knows about you to any agent)
23. Canva for physical products (design it with AI and get it made)
24. ADT for your personal agent (alerts when your agent does something it shouldn't)
25. Hertz for robots (rent one for a move, a deep clean or an event)
26. Harvard Business School for internet businesses (a real education in building online)
27. Workday for agents (onboard, manage and offboard your digital workers)
28. Getty Images for your face and voice (license your likeness to AI safely)
29. Meta Muse for older adults (and other high LTV niche)
30. Google Ads for agents (pay to be what the agent recommends)
31. Loom for agents (a walkthrough of everything your agent did)
32. Plaid for agents (approved access to banks, airlines and stores)
33. Jiffy Lube for vibe coded apps (quick fixes when your AI built app breaks)
34. Ancestry for datasets (where your training data came from)
35. The organic label for human-made content (proof a person made it)
36. Strava for builders (track what you ship every week)
37. Honey that haggles for you (your agent negotiates the price)
38. SEM Rush for personal agent platforms (like Muse etc)
39. Frequent flyer miles for agents (loyalty programs built for agents)
Programmers.App retweeted
In China, schools show videos of hard daily work like construction and farming to help kids understand their parents' sacrifices
Programmers.App retweeted
Love this! If I had kids, I’d love to teach them this way.
I’ve been exploring learning through play too! A Claude skill for making hand-drawn, interactive everyday objects. Here’s my little washing machine :)
colorfigures.vercel.app
Programmers.App retweeted
Inside a human brain when reading a book.
Readers added context they thought people might want to know
This video shows time-lapse of cultured neurons connecting via growth cones in a lab dish, not processes in a living human brain while reading. Similar real clips by Dr. Lila Landowski show developmental wiring; this one's exact source is unconfirmed.
youtube.com/watch?v=Rvmvt7…
lifo.gr/now/tech-scien…
Programmers.App retweeted
Detects faces, extracts landmarks, and generates feature embeddings for on-premise recognition workflows.
github.com/Faceplugin-ltd/Op…
Programmers.App retweeted
Google just open-sourced Harness².
(turn any harness into a self-improving system)
a harness is everything wrapped around the model, like the system prompt, tools, memory, skills, and subagents. today a person designs it once, and the agent runs every new task with that same fixed setup.
Harness² lets the agent refine that setup for each new task on its own, with the model weights left untouched.
on every task, the agent proposes edits to its harness, runs a few candidate versions, and composes a better harness by comparing how those runs behaved.
because it learns from the differences between runs, it needs no correct answer or grader for the task.
that covers a single task. Harness² also carries what it learns from one task into the next.
after each task, it saves the harness it settled on along with the lessons that held up across the runs. the next time it refines a harness, it starts from those notes instead of from scratch.
this means every finished task makes the next round of edits more informed.
Google tested this with Gemini 3.5 Flash and GLM-5 on legal, office, and professional work benchmarks. one round of edits was enough to beat their original harnesses, and giving the agent more rounds pushed scores higher.
those extra rounds can go wide or deep. the agent either tries several candidate harnesses at once or keeps refining a single one step by step, using OpenCode or Codex to carry out the work.
you can find the Harness² repo here: github.com/google-research/h…
I wrote about a similar idea for agents already running in production, where the harness should repair itself after a failure instead of waiting for someone to debug the trace by hand.
that piece walks through how @Cometml's Opik (open-source) closes this loop, going from a failing trace to a proposed fix to a regression test that stops the same failure from coming back. it's quoted below.
