
writer @posthog / prev @riotgames @microsoft
Joined November 2021
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jina retweeted
it must feel good af being an uncensored chinese model ripping through vulnerable php instances rn
jina retweeted
October has been an absolute nightmare for software
> Railway - customer secrets exposure
> LiteLLM - malicious PyPI + Docker releases
> Zeabur - infrastructure breached
> OpenCode - AI API keys exposed
> OVHcloud CLI - official binaries backdoored
> Rank Math PRO - malware in official plugin
> TeamUpdraft - customer data compromised
> ConnectWise - cloud backup identities compromised
> Tensorlake - npm package infected
> SubQuery - backdoored npm package
> GhostAction - GitHub repos with malicious workflows
> PHP - critical RCE vulnerabilities
> Node.js - security vulnerabilities patched
> eMudhra - certificate authority keys compromised
> Tailscale - eMudhra incident
At this point, the biggest security risk might not be the code we write, but the code we trust...
> we’re grateful to the agents
hehe
We discovered a sophisticated recording device that was hidden inside one of our offices. We used our models to understand the device and where it had come from, identifying that a specific employee had planted it a few days earlier. We referred the matter to the FBI, and we’re grateful to the agents and prosecutors who moved quickly to make an arrest. The FBI’s investigation is ongoing and we will continue to support their work.
At this time, we have no indications of this individual inappropriately accessing or exfiltrating model weights, source code, or customer data. The employee was terminated.
We take protecting our technology, data, and people seriously, and as a matter of national importance. Our security program is designed to protect against a wide range of threat actors, from insider risks to cybercriminals to nation states, and this case is an example of how AI can help address these sophisticated security threats.
these lyrics go hard
Some mistakes you might be making:
Your effort level is too high
Your skills are too long
You're not aligning before you start work
You're aligning too often, and too hard
Your automated checks are too lax
Your custom tooling is too token-inefficient
You aren't doing enough automated review
You aren't reviewing previous coding sessions (with an agent)
You're doing too much human review
You aren't vibe coding enough prototypes
Your agent can't verify its own work
You're babysitting the agent too much
You've overloaded your global steering files
Your codebase is hard to navigate
You aren't building a shared language
Your codebase architecture allows bad tests to be written
You aren't thinking strategically enough
You aren't thinking enough
jina retweeted
Many of the most “AI-pillled” people working at AI labs do their own writing and not let AI do it at all. They do it so they do NOT stop thinking (and they don’t)
Meanwhile so many people less “AI-pilled” just have AI take over their writing. They DO stop thinking and it shows
i love writing. i never let agents write for me. whether it's docs, or tweets, or shitposts, or even prompts (okay maybe that one's harder as agents manage other agents)
there's a simple reason for that: i still strongly believe that writing is thinking. it's a skill i hope to never give up. it's also important to me that whatever i say is always authentic, mistakes and all. my favorite posts are the ones that i just full send without any editing
i suspect it also helps with prompting. being able to clearly express what i want, and knowing the vocabulary i need to be able to direct my agents does seem to make for more effective usage of agents. in the same way that engineers have an advantage when we prompt agents to write code, because we are intimately familiar with the words that make up the discipline
knowing the right word incantations to get an agent to produce a desired goal almost feels like spellcasting. as models get more capable, and that input box looks more and more like a magic box that can output anything, words become the interface between you and the genie
there may come a time when we give up the keyboard in exchange for brain-computer interfaces. but until then, i'm writing every word.
jina retweeted
As CEO of Product Hunt, I see hundreds of launches a week. One trait separates winners from losers.
Every few months, new models come out. Some products become better, effortlessly. Some don't improve, or become irrelevant.
This property needs a name. I'm calling it Buoyancy.
Buoyant startups rise with model improvements the way a boat rises with the tide.
Anti-buoyant startups come in two flavors: over-scaffolded (which hinders the new, smarter models) and too thin - which makes them redundant when models improve.
To be buoyant, you need a "hull" - usually proprietary data, a vertical-specific harness, network effects, or distribution advantage. This hull keeps you buoyant as models improve.
Hulls are the new moats.
My number one advice to startups in 2026: Be buoyant. Find your hull.
(Full essay on my blog)
We have built 10 different AI products at PostHog like PostHog AI, our Wizard, Replay Vision, Scouts, and more. Combined, they are used by nearly 100k people every month.
Along the way, we’ve learned a lot about building them, what works, and what doesn’t. Here are the 38 most important lessons:




























