matheus-rr

5 ms·

1.
by matheus-rr 6mo ago
This is the thing people who haven't run a Rails app for years don't appreciate. I went through the Next.js pages router to app router migration on a production app. That wasn't a version bump, it was a rewrite across a diffe
2.
by matheus-rr 6mo ago
The Java parallel is apt. Joda-Time dominated the ecosystem for about 8 years before JSR 310 landed in Java 8 (2014). One thing that helped there was a clear, single release target. What I keep thinking about with Temporal is the adoption t
3.
by matheus-rr 7mo ago
The practical pain with Web Streams in Node.js is that they feel like they were designed for the browser use case first and backported to the server. Any time I need to process large files or pipe data between services, I end up fighting wi
4.
by matheus-rr 7mo ago
Fair point on the contradiction. The "never use negative instructions" wisdom comes from general prompting where mentioning the unwanted thing can increase its likelihood. AGENTS.md is a different context though, the model is read
5.
by matheus-rr 7mo ago
The --mount=type=cache for package managers is genuinely transformative once you figure it out. Before that, every pip install or apt-get in a Dockerfile was either slow (no caching) or fragile (COPY requirements.txt early and pray the laye
6.
by matheus-rr 7mo ago
In my experience the problem is how people write them. Descriptive statements get ignored because the model treats them as context it can reason past. "We use PostgreSQL" reads as a soft preference. The model weighs it against wha
7.
by matheus-rr 7mo ago
The context window cost is the real story here. Every MCP tool description gets sent on every request regardless of whether the model needs it. If you have 20 tools loaded, that's potentially thousands of tokens of tool descriptions bu
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by matheus-rr 7mo ago
The jails vs containers framing is interesting but I think it misses why Docker actually won. It wasn't the isolation tech. It was the ecosystem: Dockerfiles as executable documentation, a public registry, and compose for local dev. Yo
9.
by matheus-rr 7mo ago
The protocol vs service distinction matters most where version lifecycles create lock-in. When you depend on a service, you're at the mercy of their deprecation timeline — Heroku free tier, Google Reader, Parse. When you depend on a pr
10.
by matheus-rr 7mo ago
The part about "dark flow" resonates strongly. I've seen this pattern play out with a specific downstream cost that doesn't get discussed enough: maintenance debt. When someone vibe-codes a project, they typically pin wh
11.
by matheus-rr 7mo ago
The thing that strikes me about this thread is how many people are scrambling to evaluate alternatives they've never tested in production. That's the real risk with infrastructure dependencies — it's not that they might go cl
12.
by matheus-rr 7mo ago
Fair concern, but this has been quietly production-stable on GCP and Azure since 2017 — that's 8+ years at cloud scale. The LKML debates you're referencing are mostly about edge cases in exotic VMX features (nested APIC virtualiza
13.
by matheus-rr 7mo ago
The dependency tree is where this bites hardest in practice. A typical Node.js project pulls in 800+ transitive dependencies, each with their own release cadence and breaking change policies. Nobody on your team understands how most of them
14.
by matheus-rr 7mo ago
The "junior dev" analogy is the one I keep coming back to, but the part people miss is the review surface area problem. When a human junior writes code, they leave breadcrumbs of their thinking — commit messages, PR descriptions,
15.
by matheus-rr 7mo ago
The intermediate product argument is the strongest point in this thread. When we went from assembly to C, the debugging experience changed fundamentally. When we went from C to Java, how we thought about memory changed. With LLMs, I'm
16.
by matheus-rr 7mo ago
This is one of those "obvious in hindsight" tricks. The comma prefix gives you a namespace that's guaranteed to never collide with system binaries, shell builtins, or anything from a package manager. I do something similar wi
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by matheus-rr 7mo ago
Interesting trade-off: build a minimal interpreter that's "good enough" for AI-generated code rather than trying to match CPython feature-for-feature. The security angle is probably the most compelling part. Running arbitrary
18.
by matheus-rr 7mo ago
The pendulum swing described here is real but I think the underlying issue is subtler than "AI vs. no AI." The actual problem most teams have isn't writing code — it's understanding what the code they already depend on i