OpenSCAD is perfect for the "programmer's brain" approach to CAD. Being able to parametrize everything means I can design something like a project enclosure once, then generate variants for different screen sizes or component layouts by just changing a few variables.
Pro tip: Use the latest nightly build and switch to the Manifold backend in preferences. Render times drop from minutes to seconds for complex models. The official 2021 release is painfully outdated.
Also, the BOSL2 library is essential - it adds proper filleting, rounding, and attachment operations that vanilla OpenSCAD lacks. Makes the difference between toy projects and actually useful designs.
The Git-friendliness is underrated too. Diffing .scad files is trivial compared to trying to understand what changed in a binary Fusion 360 file.
Yes these are horrible pain points. I can only hope Apple improves this stuff if it's true that they're adding MCP support throughout the OS which should require better multi-agent handling
You can use worktrees to have multiple copies building or testing at once
I'm a solo dev so I rarely use some git features like rebase. I work out of trunk only without branches (if I need a branch, I use a feature flag). So I can't help with that
What I did is build an Xcode MCP server that controls Xcode via AppleScript and the simulator via accessibility & idb. For running, it gives locks to the agent that the agent releases once it's done via another command (or by pattern matching on logs output or scripting via JS criteria for ending the lock "atomically" without requiring a follow-up command, for more typical use). For testing, it serializes the requests into a queue and blocks the MCP response.
This works well for me because I care more about autonomous parallelization than I do eliminating waiting states, as long as I myself am not ever waiting. (This is all very interesting to me as a former DevOps/Continuous Deployment specialist - dramatically different practices around optimizing delivery these days...)
Once I get this tool working better I will productize it. It runs fully inside the macOS sandbox so I will deploy it to the Mac App Store and have an iOS companion for monitoring & managing it that syncs via iCloud and TailScale (no server on my end, more privacy friendly). If this sounds useful to you please let me know!
In addition to this, I also just work on ~3 projects at the same time and rotate through them by having about 20 iTerm2 tabs open where I use the titles of each tab (cmd-i to update) as the task title for my sake.
I've also started building more with SwiftWASM (with SQLite WASM, and I am working on porting SQLiteData to WASM too so I can have a unified data layer that has iCloud sync on Apple platforms) and web deployment for some of my apps features so that I can iterate more quickly and reuse the work in the apps.
We were heavy users of Claude Code ($70K+ spend per year) and have almost completely switched to codex CLI. I'm doing massive lifts with it on software that would never before have been feasible for me personally, or any team I've ever run. I'll use Claude Code maybe once every two weeks as a second set of eyes to inspect code and document a bug, with mixed success. But my experience has been that initially Claude Code was amazing and a "just take my frikkin money" product. Then Codex overtook CC and is much better at longer runs on hard problems. I've seen Claude Code literally just give up on a hard problem and tell me to buy something off the shelf. Whereas Codex's ability to profoundly increase the capabilities of a software org is a secret that's slowly getting out.
I don't have any relationship with any AI company, and honestly I was rooting for Anthropic, but Codex CLI is just way way better.
Also Codex CLI is cheaper than Claude Code.
I think Anthropic are going to have to somehow leapfrog OpenAI to regain the position they were in around June of this year. But right now they're being handed their hat.
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I wonder why people keep building more. I know each has its own quirks and things they're better at, but the difference is really quite minimal.
One of the things I really would like is zero-trust 'lighthouses'. With current Zerotier and Tailscale, you really have to trust them because they can add nodes on your account whenever they want. I don't want that, I want fully self-hosted and for the lighthouses to just coordinate but not to be part of the network. I have to do some research to see what would be best.
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Black Canyon Consulting (BCC) is hiring Platform Systems Engineers of all levels to join our team at the National Center for Biotechnology Information (NCBI).
Our team is dedicated to building cutting-edge tools and systems. Our mission is to empower developers across NCBI to build, deploy, and manage software, data, and web services that make a real difference in the lives of millions of Americans.
Your contributions will play a crucial role in modernizing government technology infrastructure, fostering innovation, and ultimately making a tangible impact on communities across the country and globally. This is your chance to be part of a mission-driven team that’s shaping the future of digital government.
Tech: Linux, k8s, Service Mesh, Kafka, GitLab, ArgoCD, Elastic APM, Python, C++
The Supreme Court said in Loper Bright that previous cases decided under Chevron are still good law. But this lawsuit challenged a brand new FCC order that had not been previously litigated.
The opening sequence 3D wireframe graphics were rendered on a cluster of prototype ZX Spectrums and were the inspiration for ILM's groundbreaking work on Tron.
Just wanted to share my experience with combining OpenCAD and some AI models for small-scale 3D printing projects. So far, it's been a real game-changer. The precision and accuracy have been impressive.
Has anyone else taken this combo to the next level? I'm curious to know if there are any brick walls I'm not seeing yet. Are there limitations or challenges that come with scaling up this approach? Would love to hear about others' experiences with OpenCAD + AI in 3D printing.
My first law of robotics in production environments:
1. In order to effectively deploy real robots to solve real problems, you have to foresee and fix any problem that may occur in 99.5% of scenarios. As automation
is added in series, the higher that number must be to remain economically effective.
My second law of robotics:
2. Robots depreciate, which has tax advantages. Human wages do not.
---
Discussion:
A realistic scenario is an assembly plant that makes 1,000 widgets per day. Imagine cars, washing machines, etc.
Your widget plant has 10 footprints. Any robot stoppage takes at least 5 minutes to clear.
With a 99.5% success rate and one robot, you lose 25 minutes a day (1000*0.005 = 5 stoppages ) * 5 minutes.
If all 10 footprints have robots with a 99.5% success rate, you lose 250 minutes a day (naive model!). That's over 4 hours.
In reality, each station would have manual bypass procedures, or you would go bankrupt.
Ilya's issue isn't developing a Safe AI. Its developing a Safe Business. You can make a safe AI today, but what happens when the next person is managing things? Are they so kindhearted, or are they cold and calculated like the management of many harmful industries today? If you solve the issue of Safe Business and eliminate the incentive structures that lead to 'unsafe' business, you basically obviate a lot of the societal harm that exists today. Short of solving this issue, I don't think you can ever confidently say you will create a safe AI and that also makes me not trust your claims because they must be born from either ignorance or malice.
The site is a little misleading, saying "Several of these devices even led to patient injuries including bleeding, organ puncture, and even cobalt poisoning." The majority of documentation in the 510k process is to mitigate harms to the patient. The catch phrase they use is "safety and efficacy". FDA doesn't really care if your device works as well / better / etc. The market will decide that. FDA cares that you don't injure people more than necessary / more than the predicate device does. (If that sounds strange, consider say a biopsy needle.)
The reason 510k is so popular is that introducing a completley new device is incredibly costly typically requriing a PMA (premarket authorization) requiring clinical trial data. If I'm making a new ultrasound machine I don't need to show that ultrasound works -- that's known. I need to show it works as well as one expectes an ultrasound to work, without danger to the patient. Same as if I'm releasing an updated version, re-trialing that doesn't make sense.
Honestly a lot of the documentation requirements are absurd -- you'd think "why would anyone do something so badly we need to document that we didn't do that"... but sadly most rules exist becuase of corners that were cut in the past...
A vice president once asked me how I was able to get effective change in large organizations when no amount of exhortation on the part of senior management had been successful. I pointed out to him that the people who resist the change the hardest are the ones who cannot see what their job would be post change. As a result the change is perceived as an existential risk to their own job and they will go to great lengths to sabotage the change because of that. This is the Shirky Principle embodied in individuals, and small groups some times too.
They've also begun heavily pivoting hiring for dev roles to India now as well. I have cousins who attended no name universities in India getting SWE roles in Amazon - something that was unimaginable 5 years ago - and expanding Dev offices to lower CoL cities like Hyderabad while slowly pivoting away from Bangalore.
Addendum:
Also, the Indian branches (edit: of companies that aren't Amazon) are fairly remote work friendly. Now you have people earning $20-40k/yr living in their ancestral towns and villages where median incomes might be $3-5k
This is why I warned HN that remote first will make tech more competitive.
I had a comment here that described the committees that people could write to in order to change things, but it got voted down to zero.
> You could even trial it via a (much needed) VA nursing home program for vets
I appreciate the gesture but this is not a good idea. The VA's funding, as well as programs administered by the VA, is subject to tit for tat battles in the House Appropriations Committee. That's to say, it will get gutted over time if you create it. When it is gutted the two sides will create competing narratives of which you will never be able to discover truths from. This has been happening for generations and the VA frankly isn't that old.
This is where the government could step in and provide nursing homes. They already end up paying for most of it via Medicare, why not have more control over quality and standards. You could even trial it via a (much needed) VA nursing home program for vets
> If OP actually has 10PB on S3 currently, the OP may want to fallback to leaving the existing data on S3 and accessing new data in the new location.
Another option would be to leave data on S3, store new data locally, and proxy all S3 download requests, ie, all requests go to the local system first. If an object is on S3, download it, store it locally, then pass it on to your customer. That way your data will gradually migrate away from S3. Of course you can speed this up to any degree you want by copying objects from S3 without a customer request.
An advantage of doing this is that you can phase in your solution gradually, for example:
Phase 1: direct all requests to local proxies, always get the data from S3, send it to customers. You can do this before any local storage servers are setup.
Phase 2: configure a local storage server, send all requests to S3, store the S3 data before sending to customers. If the local storage server is full, skip the store.
Phase 3: send requests to S3, if local servers have the data, verify it matches, send to customer
Phase 4: if local servers have the data, send it w/o S3 request. If not, make S3 request, store it locally, send data
Phase 5: store new data both locally and on S3
At this point you are still storing data on S3, so it can be considered your master copy and your local copy is basically a cache. If you lose your entire local store, everything will still work, assuming your proxies work. For the next phase, your local copy becomes the master, so you need to make sure backups, replication, etc are all working before proceeding.
Phase 5: start storing new content locally only.
Phase 6: as a background maintenance task, start sending list requests to S3. For objects that are stored locally, issue S3 delete requests to the biggest objects first, at whatever rate you want. If an object isn't stored locally, make a note that you need to sync it sometime.
Phase 7: using the sync list, copy S3 objects locally, biggest objects first, and remove them from S3.
The advantage IMO is that it's a gradual cutover, so you don't have to have a complete, perfect local solution before you start gaining experience with new technology.
Company CFO and CIOs need to do better dilligence of their vendors. Two simple contract clauses: priced soliciting to price staff pouching, and treble-5x damages for IP theft.
Develop a heuristic - any consultancies brought on from 3rd party contracts must sign enhanced protection clauses. Cite publicly available info to support your position. All it takes is a quick google and a few boilerplate clauses
Entirely misses the point. The right frame for this is “AI wont take your job, but humans with ai will” [0]
There are countless examples of people up-skilling using AI. Today, that might threaten the bottom of the market. Soon, it will put everyone’s jobs at risk for disruption.
3% on payment processing, subscription management and collection.
7% on AWS.
10% on product support, account management and retention.
If you’re fast growing this is about right. If you’re starting to slow down then you can afford to spend more time optimising these, eg 2, 4 and 9, giving you a GM of 85% which is elite for a B2B SaaS.
Nah, that won’t hurt anything unless one of your future employers requirements include low personal initiative and extremely high risk aversion.
I strongly recommend following your passions and interests above all other considerations. Just be sure to set your projects up for fast, clean failure if they aren’t viable, nothing wastes more time than failing to violently pivot when needed. Learn what you came to learn and if it isn’t financially sustainable, apply your new knowledge to the next project.
You won’t spend your sunset years wishing you had done less of the things you wanted to do. Regret is the real enemy, discomfort and struggle are stepping stones.
My$.02 as an oldster with 40+ years mostly self entertained in tech with a lot of failures and a few successes in the rearview. The only things I regret are some risks not taken, tbh.
If I have advice that I think missing could nuke your chances of success in life it would be:
Establish a point of retreat in an inexpensive place to live. A home of your own, somewhere in the world, where the cost of living is very low. It should be an economical and simple home with low maintenance requirements, in a place that brings you a sense of serenity.
Being able to duck out and work on something without having to worry about significant costs has been critical to my freedom to choose my destiny. That and having a partner that is not adverse to adversity in the name of advancement, if you choose to have a life partner.
Essentially, non technical people who want to insert themselves into technical projects account for many of the new PMs we see, at least in consulting, nowadays.
I haven't used Bullet Train, but I've found their "Teams should be an MVP feature" blog post [1] a really great overview of how to model team structures in relational databases before. Worth a read!
Yeah but I've said before, if Google had GPT 4, we wouldn't have public access. The reality is Google has filled itself to the brim with experts on their domains, rather than experts on their domains as they fit into a larger picture.
It's cool to be a 10x engineer, but if you're turning basic tasks in 100x efforts in the pursuit of engineering rigor, you're going to get your lunch ate by 1x engineers using unsexy unscalable tech.
Based on its contents I was not convinced that Bard is actually so terrible vs Google's internal testers simply upholding a bar that's not realistic for the current crop of LLMs, especially when you read things like:
> In some, like child safety, engineers still need to clear the 100% threshold.
How do you child proof an LLM? Why wouldn't you instead just release it and say supervise your child's use the same way you would for 99% of the internet?
I built something in a similar space this past weekend, for the purpose of education. I’ve wanted to build personalized education for a while, and the tech is finally catching up!
Zuck actually posted about this on his Facebook[0].
Short answer is the first layoffs (seemingly) were rather random as far as who was affected. This new round is a lot more deliberate by
1. Cutting projects/efforts that don't make the cutline
2. Letting go the surplus of people previously needed to execute on those projects
> Since we reduced our workforce last year, one surprising result is that many things have gone faster. In retrospect, I underestimated the indirect costs of lower priority projects.
> It's tempting to think that a project is net positive as long as it generates more value than its direct costs. But that project needs a leader, so maybe we take someone great from another team or maybe we take a great engineer and put them into a management role, which both diffuses talent and creates more management layers. That project team needs space, and maybe it tips its overall product group into splitting across multiple floors or multiple time zones, which now makes communication harder for everyone. That project team needs laptops and HR benefits and may want to recruit more engineers, so that leads us to hire even more IT, HR and recruiting people, and now those orgs grow and become less efficient and responsive to higher priority teams as well. Maybe the project has overlap with work on another team or maybe it built a bespoke technical system when it should have used general infrastructure we'd already built, so now it will take leadership focus to deduplicate that effort. Indirect costs compound and it's easy to underestimate them.
> A leaner org will execute its highest priorities faster. People will be more productive, and their work will be more fun and fulfilling. We will become an even greater magnet for the most talented people. That's why in our Year of Efficiency, we are focused on canceling projects that are duplicative or lower priority and making every organization as lean as possible.
Pro tip: Use the latest nightly build and switch to the Manifold backend in preferences. Render times drop from minutes to seconds for complex models. The official 2021 release is painfully outdated.
Also, the BOSL2 library is essential - it adds proper filleting, rounding, and attachment operations that vanilla OpenSCAD lacks. Makes the difference between toy projects and actually useful designs.
The Git-friendliness is underrated too. Diffing .scad files is trivial compared to trying to understand what changed in a binary Fusion 360 file.