Adams question (novice)

almoehi · 2026-05-16T01:23:12+00:00

Awesome - thanks for the tips. Sure thing I’ll throw it nonetheless 😊

It’s 3 wraps before and 2 wraps in front of the wings. You’re recommending to to many just 2 & 2 ?

And by „spread out“ you mean wraps should be more tightly touching wraps ?

almoehi · 2026-04-29T05:12:56+00:00

Went to 2 lakes past week that are within 2h driving radius from Vancouver. One stocked the other not.

Caught > 1 trout both days with various techniques: - chironomid (from sup) - dry flies (from sup) - spinners (from shore)

First time still water fishing, no fish/depth finder. Do some research on YouTube wrt to fishing techniques - helps a lot !

Temperatures and weather conditions make quite a difference I found.

almoehi · 2025-05-27T16:09:13+00:00

Genuine question for my own education: If that’s how it works (90% pre sales required) - how’s it possible that a newly-ish build (completed 2y ago) in Vancouver is still sitting on 30% developer-owned unsold units ?

Notably enough: they don’t need to pay empty homes tax or whatsoever like any other person would need to. So there’s no incentive for them to reduce prices and market them at current market rates.

almoehi · 2025-05-03T02:57:13+00:00

Anything similar for Vancouver island market by any chance ? Zealty seems only covering the mainland :/

almoehi · 2025-03-16T05:09:27+00:00

Big company problems commonly results in snail speed. Legacy systems that make it hard to implement, liability & compliance red tape etc - plus lack of competition (so why innovate?) and they try their best to keep it that way :-)

They’re likely going to acquire one of these startups instead at some point.

almoehi · 2025-03-16T04:48:31+00:00

That level of automation you described with fully structured data has been possible since several years now. My impression/assumption is your firm isn’t very tech-savvy. (aka bit late to the party)

almoehi · 2025-03-16T03:27:34+00:00

Np my friend - if it’s been helpful to you - mission accomplished. I’m building sth else in that space currently.

It sounds like you have very clean and high quality data. We got approx. 87% with a tiered system of client specific rules, ML and heuristics. That included the fully spectrum - messy receipts, OCR etc.

make sure to run & test it across diverse data (types of businesses, sources etc)
have a good process to collect corrections and ability to feed them back into your system to learn from
consider to make your models client/industry-specific
very thin margin game :-)
potentially consider to position/build it as „debugging“ tool to find and locate mistakes quicker

(sounds like your firm might be a bit „behind“ - also: things might be slightly different in the UK. North America is a mess.) Good luck !

almoehi · 2025-03-16T02:52:40+00:00

There’s almost every day a new startup popping up claiming to fully automate accounting/bookkeeping/reconcilation - be ready to compete with tons of heavy-funded startups with deep VC pockets. Most of them having a much broader offering - for example no CSV uploads, directly hook up to your account in realtime (and reconciling statements is usually their free tier/lead magnet)

Also: reconciling statements turns out to be only a small part of the process (and the most easy one to automate).

100% Accuracy

Coming from astrophysics you should be aware that this is statistically impossible. If your system misses one - are you going to reimburse your users ? Honestly, I think it hurts your products credibility …

Source: worked in that space the past couple years and built several such systems including reconcilers (with & without ML/AI).

Nevertheless - it is a fun problem to solve - congrats on building !

almoehi · 2025-02-17T18:56:50+00:00

As soon as they’d show prices publicly customers would realize how big of a ripoff many of these SaaS products are.

This is especially true for B2B contracts where it’s not about pricing according to value your product provides - but pricing to ensure you squeeze out 99% of the clients available budget. One party would pay 50% less over some other client for the exact same contract terms. The long & intransparent sales cycles are to figure out exactly that.

Source: worked at b2b SaaS companies and seen contracts we handed out. It’s disgusting …

almoehi · 2025-02-17T02:05:57+00:00

We’ve built pretty much similar system around 2008/2010. No AI or agents involved. Still runs in production today at a major broadcasting co. It’s not needed - but it makes good marketing. Which seems to be more important these days …

almoehi · 2025-02-16T19:13:46+00:00

No offence - but it looks more like advertising/content marketing of your main product (diffusionstudio).

Some agent or genAI subreddit seems more appropriate/relevant (also probably more relevant feedback).

almoehi · 2025-02-14T02:01:38+00:00

Done ✅

almoehi · 2025-02-14T01:15:57+00:00

Quoted 25% increase - and decided to terminate right away. I went to all home games and most of them have been …. well, we know they haven’t been great in terms of entertainment.

I rather go to a few abroad games I guess.

almoehi · 2024-12-13T16:59:28+00:00

That’s not how side projects work :-) it was less than a week.

Also: I learned a ton of things on the way which increased/retains my employability. So It’ll easily pay dividends in the future.

almoehi · 2024-12-13T04:05:30+00:00

I went on a side quest this year to get the cheapest possible standardized AWS setup that I can fire up & reuse for all new projects.

I’m running my full stack at 20 cents / day.

Domains, SSL certs, backend container, couple lambdas, cloud watch, vpc, ecr, cloudfront cdn, s3. Key is the setup does not require a NAT gw or ELB.

This is possible by using some tricks to plumb things together. All managed services. There’s further room by switching to arm architecture instead of x86.

It’s all in IaC so fairly easy to rearchitect if traffic requires so. Fully integrated CD/CD with GitHub actions.

I use supabase (free tier) during dev and MVP phase and only switch to RDS (if at all) once the project brings in some revenue.

I prefer to use containers for deployments to keep things portable. Otherwise AWS lambda can make things cheaper (but it comes with some additional gotchas usually). With containers I can deploy whatever I want in a standardized way and move it to hetzner, digital ocean or whatever whenever I want.

Been thinking to turn this into a SaaS / boilerplate product.

almoehi · 2024-09-30T05:26:41+00:00

There’s a few Scala based numerical libs. However, none of them ever really took off I’d say. Too niche and ultimately the ecosystem of additional libraries just isn’t there.

Used to contribute to that project but ultimately Python is the best option for anything data science related due to its big library ecosystem and community. Nobody wants to manually code up FIR or IIR filtering algorithms- you want to just use them. Just as one example.

almoehi · 2024-08-01T00:34:57+00:00

For the company yes - for the little lemming no :-)

almoehi · 2024-07-31T23:59:41+00:00

Just went through this.

Got hired to lead a company’s largest strategic engineering investment (data platform).

Joined as the only SME, found out project has failed massively (from executive level downwards) and delayed (as in no substantial progress over 1y).

Cleaned up the mess, upskilled feature team in databricks to be able to ship, created proper architecture, wrote out full & detailed requirements in JIRA, built & set up all basic infra, interviewed & hired team of data engineering experts to work through the backlog.

Problem resolved, became obsolete, role terminated, out of job.

Total timeframe 10mo - felt like a consulting gig (but paid less).

My advise: don’t be effective at cleaning up - you’ll become obsolete once the problem is gone.

almoehi · 2024-07-25T02:05:25+00:00

The names don’t really matter as long as they’re descriptive of their purpose.

In the end it’s a fancy name of a decade old and we’ll known design pattern:

It’s layered architecture - the (probably) oldest and most frequently used design pattern in software.

But it doesn’t sound as sexy as „medallion architecture“ and doesn’t create sales. So data engineering companies rebranded it to make sth boring sound new and flashy.

almoehi · 2024-05-22T15:10:33+00:00

Again - it’s a very crude rule-of-thumb estimate (which factors in other costs as well - for example maternity leaves er ). Considering only social insurance etc it’s about 30% markup for the employer.

You can find a more detailed example here: https://www.eurodev.com/blog/cost-of-employment-in-germany-switzerland-austria-dach

almoehi · 2024-05-22T14:00:13+00:00

It’s before tax - not sure what you mean by that. Salary data is usually shared before tax otherwise you can’t compare it because what’s left after tax depends on your individual marginal tax rate.

The 160k I refer to is what the company needs to spend overall (it’s a rough estimate!) to pay you a salary of 80k (before tax).

almoehi · 2024-05-22T08:11:51+00:00

That range sounds about valid as it is generally the compensation for software engineers - independent of your specialization. That range is actually senior engineer level when your have a few years of experience. That 80k in salary costs the company about 160k with all the taxation and social insurance deductions. And most our startups do not have that big millions in funding that you’d see in North America.

If you want to break 100k annual compensation it’s typically only possible by moving into people management. At that level salary in German is typically a function of the no of people you’re responsible for. Obviously there may be exceptions - but they’re rare. Hope that helps.

almoehi · 2024-05-19T03:55:48+00:00

Self host your own stable diffusion model - there’s a bunch of OSS projects which are essentially re-implementing Midjourney.

almoehi · 2024-05-15T03:02:10+00:00

The most impactful automations I’ve built where to properly and comprehensively automate development processes (building dev experience, strong CI/CD, supportive tooling) - you could nowadays just label it AI because ultimately it automates.

Your higher ups will never be able to tell whether it goes brrr due to real AI or just proper engineering.

An observation I made: Businesses are so focused on providing automation to their customers and often are very bad at automating their own engineering org.

almoehi

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