maherbeg

5 ms·

31.
by maherbeg 3mo ago
I wouldn't care where my data went if it was to help my children.
32.
by maherbeg 3mo ago
I would say one thing I've enjoyed about the latest frontier models from US labs is that you just work at a higher level of abstraction. You can talk about the end goal and it'll just rip. You'll add scaffolding to constrain
33.
by maherbeg 3mo ago
I wouldn't call this minor. The 2 big features seem to be integrated memory + ambient proactiveness. This requires pretty intense tuning to not be annoying.
34.
by maherbeg 3mo ago
I've found the prompting needs are drastically different from the latest frontier models to the latest open weight models. I can be much more vague and talk about an end goal with the frontier models vs needing to be more prescriptive
35.
by maherbeg 4mo ago
Cursor had a specific licensing agreement that allowed them to brand it how they want.
36.
by maherbeg 4mo ago
I wonder if new models will be trained with speculative decoding as a core feature allowing fewer experts to be needed for a pass.
37.
by maherbeg 4mo ago
I'm a big PGDog fan! It really helped us scale our connection proxy needs pretty substantially and it has great features like auto mode to support Aurora failovers neatly. It's infra that just works.
38.
by maherbeg 4mo ago
Happy to chat about this, but we use the AWS secrets manager flowing into External Secrets Operator to generate a pgdog_users.toml. We then kick off a workflow to refresh things, but our rate of change here is much smaller than a super dyna
39.
by maherbeg 4mo ago
iOS 27 supports devices all the way down to the iPhone 11, so I think they're doing pretty well here.
40.
by maherbeg 4mo ago
Great post! There are some neat tricks around completion initing that I'll have to grab. I use fish shell and have done a bunch of optimization around async git statuses too.
41.
by maherbeg 4mo ago
for sure! but there are lots of incremental shareable primitives that could help. I think about go's built in testing tools that can get extended as an example
42.
by maherbeg 4mo ago
Very happy for them, they made excellent tools and I hope they can continue their work! I do believe though that these tools (formatting, linting etc.) should be built into the language like Go, and I really hope the Node team can just abso
43.
by maherbeg 5mo ago
In addition to this, the labs are all building managed cloud agents, where they can tune better models and better harnesses. If you want the best performance, you'll eventually have to use their platform with their secret alpha baked i
44.
by maherbeg 5mo ago
There will always be a gap, but what's interesting is that because new models are constantly coming out, we as an industry never spend any time extracting the maximal value out of an existing model. What if there are techniques, and ha
45.
by maherbeg 5mo ago
This is so sick. I'm really curious to see what focused effort on optimizing a single open source model can look like over many months. Not only on the inference serving side, but also on the harness optimization side and building cust
46.
by maherbeg 5mo ago
I also don't think a lot of people know some of the more advanced context management tricks like /rewind /fork /tree to take advantage of prefix caching
47.
by maherbeg 5mo ago
Zed has a "turn off all AI features" checkbox if you want to use that
48.
by maherbeg 5mo ago
It works well but there are a lot of missing features * skill auto complete * custom agents * sub agents * background process management
49.
by maherbeg 5mo ago
pgbackrest is awesome, truly. Thank you so much for the work you've put into this project over the years, and I'm sad the crunchy data acquisition couldn't keep the project alive.
50.
by maherbeg 6mo ago
We actually have one of these between our group of friends and their kids and it's awesome. The kids call each other to chat and setup play dates or to go run around in the street. Our kids will call back home to let us know they made
51.
by maherbeg 7mo ago
Honestly, they can keep waiting for another year or two for on-device models at the size they're looking for to be powerful enough.
52.
by maherbeg 7mo ago
The way we solved it is by checking the lsn on the primary, and then waiting for the replica to catch up to that lsn before doing reads on the replica in various scenarios.
53.
by maherbeg 8mo ago
This is really tough in a large organization with features that cross across product domains.
54.
by maherbeg 8mo ago
Yeah, you'll definitely want to set things like `max_standby_streaming_delay` and friends to ensure things are bound correctly.
55.
by maherbeg 8mo ago
Gotta say, I love using PGDog. It has some fantastic built in features, and I'm looking forward to testing out the improved query parser. Lev and the team are heroes. At the scale we were using PGDog, enabling the previous form of the
56.
by maherbeg 9mo ago
I totally agree. I love watching a small set of animated films over the holidays in time order to really see the technical progress. It's especially fun to go from something nostalgic I loved as a kid, to something I can really see the
57.
by maherbeg 9mo ago
Both accessibility, and application security are easier to build rules + improved models for because they have pretty solid constraints and outcomes. UX on the other hand is definitely more challenging given how much of it isn't quite
58.
by maherbeg 9mo ago
That may be true now, but think about how far we've come in a year alone! This is really impressive, and even if the models don't improve, someone will build skills to attack these specific scenarios. Over time, I imagine even clo
59.
by maherbeg 9mo ago
I wouldn't be surprised if this paves the way for differing insurance rates on health markers given how magical glp-1s seem to be, and how much of modern disease is based on lifestyle factors.
60.
by maherbeg 10mo ago
a lot of the gen1 users will likely swap over to it though. They basically have dropped improvements for gen1 autonomy which is rug-pullish :(

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