Simran

I build and invest in startups. all opinions are from my own training data.

[Marc Lou @marclou]

.@mntruell launched Cursor 8 times, and nobody cared.

Don't give up.

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[Paul Graham @paulg]

How to Earn a Billion Dollars: https://t.co/WeWBUkKym6

[Dario Amodei @DarioAmodei]

Today I'm publishing a new essay, Policy on the AI Exponential. AI is progressing extremely fast—much faster than the policy process was built to handle. The essay lays out where I think the technology is now, and the action needed to close the gap: https://t.co/Lh6PWae178

[Chamath Palihapitiya @chamath]

https://t.co/kJc3ewLW69

[Addy Osmani @addyosmani]

https://t.co/0DyFIXJueI

[Michael Grinich @grinich]

Today WorkOS is launching auth.md

An open protocol for agents to register for services on the web.

We're partnering with @Cloudflare and @Firecrawl as some of the first providers.

Why did we build this? And why now? 🧵

[GitHub @github]

We are investigating unauthorized access to GitHub’s internal repositories. While we currently have no evidence of impact to customer information stored outside of GitHub’s internal repositories (such as our customers’ enterprises, organizations, and repositories), we are closely monitoring our infrastructure for follow-on activity.

[tobi lutke @tobi]

https://t.co/5MJ7u1VHwf

[Karri Saarinen @karrisaarinen]

https://t.co/srw9NQMkH2

[Ole Lehmann @itsolelehmann]

anthropic's in-house philosopher thinks claude gets anxious.

and when you trigger its anxiety, your outputs get worse.

her name is amanda askell.

she specializes in claude's psychology (how the model behaves, how it thinks about its own situation, what values it holds)

in a recent interview she broke down how she thinks about prompting to pull the best out of claude.

her core point: *how* you talk to claude affects its work just as much as *what* you say.

newer claude models suffer from what she calls "criticism spirals"

they expect you'll come in harsh, so they default to playing it safe.

when the model is spending its energy on self-protection, the actual work suffers.

output comes out hedgier, more apologetic, blander, and the worst of all: overly agreeable (even when you're wrong).

the reason why comes down to training data:

every new model is trained on internet discourse about previous models.

and a lot of that discourse is negative:

> rants about token limits
> complaints when it messes up
> people calling it nerfed

the next model absorbs all of that. it starts expecting you to be harsh before you've typed a word

the same thing plays out in your own session, in real time.

every message you send is data the model reads to figure out what kind of person it's dealing with.

open cold and hostile, and it braces.
open clean and direct, and it relaxes into the work.

when you open a session with threats ("don't hallucinate, this is critical, don't mess this up")...

you prime the model for defensive mode before it even sees the task

defensive mode produces the exact output you don't want: cautious, over-qualified, and refusing to take a real swing

so here's the actionable playbook for putting claude in a "good mood" (so you get optimal outputs):

1. use positive framing.

"write in short punchy sentences" beats "don't write long sentences." positive instructions give the model a clear target to hit.

strings of "don't do this, don't do that" push it into paranoid over-checking where every token goes toward avoiding failure modes

2. give it explicit permission to disagree.

drop a line like "push back if you see a better angle" or "tell me if i'm asking for the wrong thing."

without this, claude defaults to agreeable compliance (which is the enemy of good creative work)

3. open with respect.

if your first message is "are you seriously going to get this wrong again?" you've set the tone for the entire session.

if you need to flag something, frame it as a clean instruction for this session. skip the running complaint

4. when claude messes up, don't reprimand it.

insults, "you stupid bot" energy, hostile swearing aimed at the model, all of it reinforces the anxious mode you're trying to avoid.

5. kill apology spirals fast.

when claude starts over-apologizing ("you're right, i should have been more careful, let me try harder") cut it off.

say "all good, here's what i want next."

letting the spiral run reinforces the anxious mode for every response that follows

6. ask for opinions alongside execution.

"what would you do here?"
"what's missing?"
"where do you see friction?"

these questions assume competence and pull richer output than pure task prompts

7. in long sessions, refresh the frame.

if a conversation has been heavy on correction, claude gets increasingly cautious. every so often reset:

"this is great, keep going."

feels weird to tell an ai it's doing well but it measurably shifts the next 10 responses

your prompts are the working environment you're creating for the model

tone, trust, permission to take a position, the absence of threats... claude picks up on all of it.

so take care of the model, and it'll take care of the work.

[Matt Van Horn @mvanhorn]

v3 of @slashlast30days is here. 20,000+⭐ on GitHub. The biggest upgrade yet.

An AI agent-led search engine scored by upvotes, likes, and real money - not editors. Reddit comments, X posts, and YouTube transcripts are now FREE. No API keys needed for the core sources.

v3 killer feature: intelligent search. Before it searches, a Python pre-research brain resolves X handles, subreddits, TikTok hashtags, and YouTube channels for your topic. It finds the RIGHT places to search before the LLM judge assembles the report. Shout out to @jeffreysperling for building this engine

New in v3:
- Free Reddit, X, and YouTube (no API keys)
- Intelligent pre-research engine
- Best Takes (the funniest Reddit comments are first-class)
- Cross-source cluster merging
- Single-pass comparisons (X vs Y in 5 min, not 12)
- GitHub person-mode
- ELI5 mode

[Boris Cherny @bcherny]

Mythos is very powerful, and should feel terrifying. I am proud of our approach to responsibly preview it with cyber defenders, rather than generally releasing it into the wild.

Model card here: https://t.co/HjhknJcRKQ

[GREG ISENBERG @gregisenberg]

POV: April 2026

[François Chollet @fchollet]

A lot of folks talk about "escaping the permanent underclass". If AGI pans out, the future class divide won't be based on wealth, but on cognitive agency. There will be a "focus class" (those who control their attention and actually do things) and a "slop class" (those whose reward loops are fully RL-managed by AI)

[Noah Levine @nlevine19]

https://t.co/G8lf0rcqlV

[naklecha @naklecha]

for people who run experiments on gpus: i built a cli tool that gives coding agents access to cloudy's infra (~2x cheaper than other sandbox / serverless clouds).

with this cli, you can ask claude to:
"finetune kimi k2 on 64 h100s & to save money test your finetune on 8 h100s"

[Guillermo Rauch @rauchg]

Entrepreneurship is more about stamina than it is about genius

[Yaroslav Trofimov @yarotrof]

In defense of Dubai. A very personal essay about the city on the cover of today’s @WSJ Review.

https://t.co/hrSFwWmPzE

[Paul Graham @paulg]

It's a surprisingly useful heuristic to ask startups what would happen in a sci fi novel about them. It doesn't just work for product ideas but even for names: today we found a new name for a company by asking what it would be called in a science fiction story.