akrylov

7 ms·

1.
Finally, found a good use-case for OCaml(ingresslabs.github.io)
11 points by akrylov 3mo ago|2 comments
2.
by akrylov 3mo ago
lpf is GitOps for Linux networking: PF-style firewall, NAT, QoS, and routing policy with live diff, guarded apply, and automatic rollback for remote changes.
3.
by akrylov 4mo ago
I have not tried deerflow 2.0 but the community showcase is not particularly impressive to be honest. Single agent system can do just as good. Any multi-Agent framework must constantly outperform single-agent on a different tasks.
4.
by akrylov 4mo ago
The name of the thread is provocative, but the premise is valid - I have yet to see anything produced by multi-agent frameworks (langchain or bespoke works) that produced value. Anthropic pushes vibeCAD, vibeVFX, vibePowerPoint but the resu
5.
Multi-Agent is a snake oil(avkcode.github.io)
6 points by akrylov 4mo ago|5 comments
6.
Hormuz Shock(avkcode.github.io)
1 points by akrylov 4mo ago|0 comments
7.
by akrylov 4mo ago
No US has been "winning" or rather leading thus far, but there is no guarantees that it will ever "win". I do not subscribe to idea of omnipotent omnipresent AGI. China plays a long game, I think DeepSeek does not engage
8.
by akrylov 4mo ago
It's not "AI bubble" - at this point it's a software bubble. It's Antropic or OpenAI that should justify their valuations, they have close to billion customers at this point. It's non-AI software companies with
9.
by akrylov 4mo ago
>> And, yet, the US AI companies are not actually making a profit, right? I think they already, actually making profits especially Antropic. But think how important it's from a business standpoint - the entire software stack from
10.
by akrylov 4mo ago
No, Alibaba is excellent top-5 easily.
11.
by akrylov 4mo ago
The trade war and tariffs are bringing inflation, consumer prices will soar, but from a geoeconomical standpoint this will hurt China (And EU) more than US. US consumer on average has the deepest pockets in the World and people the top will
12.
by akrylov 4mo ago
True, I would have preferred benevolent dictator scenario, like with the Internet. But this time around it's different - AI data centers will be protected like embassies.
13.
by akrylov 4mo ago
Jobs, Wozniak, Gates - it's a myth that you need poor migrants pulling themselves by their bootstraps to innovate. Sometimes a nazi scientist like Wernher von Braun is what it takes.
14.
by akrylov 4mo ago
It's a myth. IBM, Xerox, HP, DEC was innovating long before H1B's.
15.
by akrylov 4mo ago
The goal is global domination as always, unfortunately. DARPA and the Pentagon helped create the Internet, and Silicon Valley later turned it into a major commercial success.
16.
The US is winning the AI race where it matters most: commercialization(avkcode.github.io)
241 points by akrylov 4mo ago|677 comments
17.
Loops and Routines Without Claude(ingresslabs.net)
1 points by akrylov 4mo ago|0 comments
18.
The IDE Should Become an Operating System for AI(avkcode.github.io)
8 points by akrylov 4mo ago|3 comments
19.
Ask your agent to do Docker and K8s(ingresslabs.github.io)
2 points by akrylov 4mo ago|0 comments
20.
Armenia at the Crossroads(nopolitik.substack.com)
5 points by akrylov 1y ago|0 comments
21.
Building Kubernetes with Kubernetes(github.com)
2 points by akrylov 1y ago|0 comments
22.
Terraform and Ansible is not enough(github.com)
4 points by akrylov 1y ago|1 comments
23.
by akrylov 1y ago
Terraform and Ansible are powerful tools for infrastructure automation, but they fall short in handling complex, long-running workflows, state management, and fault tolerance. Modern DevOps tooling often struggles with scalability, error re
24.
Helm and YAML templating was a mistake: A Makefile Manifesto(github.com)
4 points by akrylov 1y ago|1 comments
25.
by akrylov 1y ago
Modern Kubernetes deployment methodologies have grown increasingly complex, layering abstraction upon abstraction in pursuit of flexibility. This article challenges that trajectory by examining how fundamental Unix tools combined with Makef
26.
Fine-Tuning Models with Your Own Data, Effortlessly(github.com)
2 points by akrylov 1y ago|1 comments
27.
by akrylov 1y ago
Most blog posts focus on using top-tier LLMs or setting up complex AI pipelines for large corporations. But what if your data is private, and you don’t have access to top-tier ML talent or massive infrastructure? In this article, we show ho
28.
Leaquor.jl: Secret Scanning with Julia(github.com)
2 points by akrylov 1y ago|1 comments
29.
by akrylov 1y ago
Most secret-scanning tools for Git repos have a big problem: their JSON output is often broken or hard to parse, making automation a pain. They find secrets just fine, but trying to use their output in a CI pipeline or backend service usual
30.
Scaling Verilator Simulations with Kubernetes and Julia [pdf](github.com)
3 points by akrylov 1y ago|1 comments

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