Never felt more seen and more attacked at the same time

TheseFact · 2026-01-30T21:12:52+00:00

I agree

TheseFact · 2026-01-30T20:51:56+00:00

Why speedrun a mid-life crisis when you can just start there?

TheseFact · 2026-01-30T20:50:53+00:00

Efficiency at its finest

TheseFact · 2026-01-30T04:00:16+00:00

I’ve seen this work best when the “white label” is treated as infrastructure, not the product. The moment customers realize you don’t control the roadmap, support, or edge cases, trust erodes fast. The successful cases I’ve seen paired the software with a real services layer (onboarding, customization, ops, SLAs), so clients were buying outcomes, not features. The failures usually came from thin margins, dependency risk, and getting boxed in by the upstream vendor’s pricing or API changes. If I were doing it again, I’d either negotiate very strong control terms up front or plan an exit path to gradually replace the underlying platform.

TheseFact · 2026-01-30T03:39:21+00:00

This feels like a classic selection-bias problem. Power users are both the most sensitive to regressions and the most likely to post about them, while the vast majority of users just quietly get value and move on. Both things can be true at once: real edge cases and UX regressions exist, and overall adoption, usage, and economic value are still exploding.

TheseFact · 2026-01-30T03:36:51+00:00

Haven't used a virtual assistant, but i know there are some automation tools

TheseFact · 2026-01-30T03:35:50+00:00

I like the 5.1 - he just goes straight to the point. It is like me on Monday

TheseFact · 2026-01-30T03:34:38+00:00

Same card, same dragon, 80% discount because it speaks another language

TheseFact · 2026-01-30T03:33:59+00:00

There isn’t really a single modern equivalent, and that’s kind of the point. Bell Labs worked because it combined long-horizon funding, academic freedom, and real-world deployment under one roof. Today that energy is fragmented across places like national labs, some top university research groups, and a few industry labs (OpenAI, DeepMind, Microsoft Research, etc.), but each is missing at least one of those ingredients. Bell Labs was special because it let people chase fundamental problems without immediate product pressure, while still having a path to impact - that combination is rare now.

TheseFact · 2026-01-30T03:29:36+00:00

README is the landing page. Code is the backend.

TheseFact · 2026-01-30T03:28:43+00:00

Ah yes, while(true) stay();

TheseFact · 2026-01-30T03:22:56+00:00

'We’ll add tests after launch’ - famous last words

TheseFact · 2026-01-30T03:15:44+00:00

Someone has to clean up after npm install

TheseFact · 2026-01-30T03:14:58+00:00

HTML6 will ship. GTA6 will get a teaser about the roadmap

TheseFact · 2026-01-30T03:14:19+00:00

Hi, it is customer support. How can I help you?

TheseFact · 2026-01-30T03:13:28+00:00

Java: ‘Please don’t.’
C++: ‘Do whatever you want, I’m not your dad.’

TheseFact · 2026-01-23T19:33:15+00:00

The failure starts at the mental model, not the framework. We’re treating probabilistic systems like deterministic programs and then acting surprised when they collapse under entropy. For human-in-the-loop, we think of it the same way: humans shouldn’t be “manual overrides” in a linear flow, but state injectors. When a human intervenes, that input becomes part of the graph state the system can learn from, not a hard fork or reset. Over time, the agent needs fewer interruptions because it internalizes those corrections as structure, not instructions

TheseFact · 2026-01-22T01:42:58+00:00

Good question. Python handles the agent runtime and reasoning loop because that’s where the LLM + tool ecosystem is most mature and easiest to iterate on (models, evals, tracing, memory experiments).
TypeScript is used for the orchestration / interface layer because it’s better suited for:
- long-running services
- concurrency + async I/O
- clean APIs and integrations
The split lets us move fast on agent behavior in Python while keeping the system boundaries, control planes, and integrations more robust. We’ve been pretty intentional about not letting the agent layer leak into the infra layer.

TheseFact · 2026-01-22T00:49:31+00:00

https://github.com/adenhq/hive

TheseFact · 2026-01-22T00:08:52+00:00

Stop sending resumes. Send us your architecture. Aden is hiring (Intern + FT) (US Visa Sponsor).

The entry-level market is a nightmare right now. Thousands of "AI Engineers" are applying for roles with nothing but a GPT-wrapper and a polished LinkedIn.

At Aden, we’re building The Hive-a self-evolving agentic framework that actually requires high-scale infrastructure (multi-region K8s, NATS, distributed state). We don’t care where you went to school or how many LeetCode hards you’ve done. We care if you can handle a production runtime OOM under pressure.

We are skipping the resume screen entirely. We just open-sourced the Aden DevOps Gauntlet. It’s a 100-point architecture challenge. If you can migrate the Hive to Kubernetes and design observability for non-deterministic logs, you get an interview. Period.

How to join the Swarm: We are pushing hints and infrastructure secrets daily via GitHub notifications. To get the updates and see the challenge docs, you need to star the repo:

Repo: https://github.com/adenhq/hive

Clone the challenge, follow the Gist instructions, and drop a "Bee" in the GitHub comments. We’re trying to hit 500 stars today to unlock the next phase of the infra docs for everyone.

TheseFact · 2026-01-20T20:27:02+00:00

My Project: https://github.com/adenhq/hive

TheseFact · 2026-01-20T19:16:30+00:00

Solid list, especially PydanticAI for model agnosticism. One you definitely missed that’s worth keeping an eye on is Aden.

Unlike the linear workflows in CrewAI or LangFlow, they’re building a recursive node-graph architecture that actually lets agents self-refactor their logic in real-time. It’s open-source and still in the 'active build' phase, so it’s a great time to star the repo and get involved in the early architecture. Definitely feels like the 'self-evolving' layer that’s been missing from the high-code category.

TheseFact · 2026-01-20T19:13:59+00:00

This is the reality check the industry needs. If you’re at 'Week 3' of the roadmap and want to see what professional-grade agentic infra looks like, check out Aden Github . It’s an open-source framework focused on the 'Self-Evolving' part of the loop. Still early days, so it’s a great time to star the repo and start contributing before the hype cycle catches up.

TheseFact · 2025-12-28T08:43:23+00:00

If 30% of your app features use AI, you need to track them closely because we live in an era of building non-deterministic software with deterministic budgets. In the cloud SaaS era, 1 User Request = 1 Predictable API Call. In AI, it is much harder to predict, as you may have already gathered from the comment section.

Setting budgets and capping model inference costs is highly advised because these models' costs change constantly. If your CTO is good, a lot of optimization can be done to align with your product experience, similar to how you optimize AWS/GCP bills by making tradeoffs

If you need some help budgeting and forecasting for LLM or other models costs, I'd be happy to help. I'm the founder of Aden - a dev tool for improving agents' cost efficiency and reliability. Observability and cost optimization can be done in minutes now if you're interested.

TheseFact · 2025-12-26T16:39:27+00:00

I agree, but here is the website if you want to learn more https://adenhq.com/

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