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Joined 7 years ago
Joined 7 years ago
While that's completely true, I do think it misses a key underlying point: VCs (and many breeds of investor) are not ultimately selecting for value creating ideas, or for their friends: they're selecting for investments they believe _other people_ will pay more for later.
In the case of startups, those people are most likely other VCs (at later rounds), private equity (at private sale) or retail investors (at IPO).
Very rarely is the actual company profitable at any of those stages, demonstrably and famously.
So the whole process is selecting for hype-potential, which itself is somewhat correlated to the usual things people get annoyed about with startup cliches: founders who went to MIT; founders who are charismatic; founders who are friends with VCs; etc...
So yeah, they invest in their friends, but not because they're their friends. Because they know they can more reliably exit those investments at a higher value.
We use a mix of agentic and conversational tools, just pick your own and go with it.
For Unity development (our main codebase and source of value) I give current gen tools a C- for effectiveness. For solving confined, well modularisable problems (eg refactor this texture loader; implement support for this material extension) it’s good. For most real day to day problems it’s hopelessly confused by the large codebase full of state, external dependency on chunks of Unity, implicit hardware-dependent behaviours, etc. It has no idea how to work meaningfully with Unity’s scene graph or component model. I tried using MCP to empower it here: on a trivial test project it was fine. In a real project it got completely lost and broke everything after eating 30k tokens and 40 minutes of my time, mostly because it couldn’t understand the various (documented) patterns that straddled code files and scene structure.
For web and API development I give it an A, with just a little room for improvement. In this domain it’s really effective all the way down the logical stack from architectural and deployment decisions all the way down to implementation details and debugging including digging really deep in to package version incompatibilities and figuring out problems in seconds that would take me hours. My one criticism would be the - now familiar - “junior developer” effect where it’ll often run ahead with an over engineered lump of machinery without spotting a simpler more coherent pattern. As long as you keep an eye on it it’s fine.
So in summary: if what you’re doing is all in text, nothing in binary, doesn’t involve geometric or numerical reasoning, and has billions of lines of stack overflow solutions: you’ll be golden. Otherwise it’s still very hit and miss.
The idea that a Labour Secretary of State would be phoning up the Cabinet Office screaming down the phone at them about interaction design on the website while a Tory one would just have their feet up is ludicrous and you know it.
Pages are snappy, terse, consistent, clear and unsurprising. I agree this specific example feels a bit dark-patterny and occasionally stuff like self-assesment can have more steps than necessary, but overall it's really high quality.
In comparison the process for getting a DUNS number felt like going through some kind of a psychological experiment.
Finally, this:
> a party in power famous for paternalism
is just enclowning yourself with a partisan and non-sequitous point.
Those + some SD cards and a spare evening for setup makes this a really tempting £400 project.
If you're interested in where they're currently focusing their spending and the timelines for return on investment, the recently leaked memo isn't a bad place to start https://www.uploadvr.com/meta-cto-to-staff-leaked-memo-2025-...
It's not a new headset or a protoype for one.
"Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception. These future devices will need to be all-day wearable in a socially acceptable form-factor to support always available, context-aware and personalized AI applications. Our team at Meta Reality Labs Research built the Aria device, an egocentric, multi-modal data recording and streaming device with the goal to foster and accelerate research in this area. In this paper, we describe the Aria device hardware including its sensor configuration and the corresponding software tools that enable recording and processing of such data."
[1] https://zap.works/studio [2] https://zap.works/designer [3] https://zap.works/mattercraft