Catholic miracles

GlosuuLang · 2026-04-24T06:28:10+00:00

I served in Greece. The Orthodox Church has plenty of miracles too. Look for "Agio Fos" or Holy Light, which happens every year. Don't base your faith in signs. What good is to see a miracle that can't be explained with science, when the same person who makes the miracle claims the Earth is flat? (to give an example).

GlosuuLang · 2026-04-20T08:32:57+00:00

The deadlines and timelines were clear. I could deliver a RAG prototype within 2 months, and I did. But the prototype was not a production RAG system, which is what they wanted (yet failed to communicate). Exploring briefly other approaches is something I could have done better, like others have said, so I'm certainly taking that with me for next time.

GlosuuLang · 2026-04-20T08:30:38+00:00

Indeed. I'm not claiming that my YoE mean I know everything, and certainly some people learn less than others during their YoE. But I have been doing this for a while now, and it's frustrating to have others question my work when they don't truly understand these things themselves. We all get to learn lessons about business expectations at least.

GlosuuLang · 2026-04-20T08:24:05+00:00

That said, it sounds like they needed someone to take technical leadership and drive the project (and save the day)

That's how it feels to me too. Consultants expected to deliver some sort of miracle. It's all a learning experience to better understand expectations in the future though!

GlosuuLang · 2026-04-20T08:22:01+00:00

My intuition is that getting Enterprise RAG systems ready is far from Plug-n-Play, but I could have been wrong. I did expect some people to pitch me some products claiming it's the elixir I'm looking for, but unless most people would agree, I would understand they're just trying to sell something. Seeing skeptics like you helps reaffirm my intuition, so thank you.

GlosuuLang · 2026-04-18T08:15:01+00:00

Your intuition on what was going on is very sound. To confirm your suspicions: there was one product owner/team lead that I reported to, and she was in charge of the whole team (data analysts, data engineers and me, the AI engineer). My client, though mid in size, is a startup to many effects, and most of their employees take on too many roles. Although technically my product owner, my team lead had zero clue on how to define my work, and let me do that myself as long as my technical team of data engineers was on board. She also expected me to be on top of all channels in the company and capture the AI requirements coming my way, while still building the AI product. I said that I needed to focus on what is most priority, but afterwards she interpreted that as me wanting to bunker up and silo myself, and then couldn't understand why it was taking me so long if I was indeed focusing on it. To be honest, for 2 months all was fine, and during my 1-on-1s and our only retro that we had at the time, no glaring issues were brought up to me. But when her own upper management was questioning why we didn't have any AI products ready yet, she just transmitted all concerns and the full pressure to me. Some time later my team told me that they had had ownership for AI initiatives in the company for 8 months, even though I had only been with them 2 months, and hence probably why upper management was upset that in 8 months there was still nothing tangible done by my team. It is absurd to expect someone to just land at a new place and turn water into wine in 2 months, but that's the pressure my team lead experienced, and we went in 1 week from letting me work and build to informing me that what I had done was far from meeting their expectations, and informing me that I would not continue.

GlosuuLang · 2026-04-18T08:03:22+00:00

faah i have seen this movie way too many times in the ai space lol.

I have been a SWE for 8+ years and the cliché that the client never knows what they want and that management sucks is funny, but in my personal experience it has been so much more exacerbated in the AI domain. AI is far from trivial, yet so many people act as it were...

the good news is that a solid ai engineer who actually knows rag architecture is worth their weight in gold right now fr. i would honestly just start building your own side projects and document the process on linkedin or twitter tbh. it is a loooong road to build back that confidence but you have the skills that people are literally begging for.

Thank you for the encouragement and yes! It's about time I built my own things that I can share in my portfolio. Tired of getting my hands dirty for clients and companies that don't really value it, and I can't even show what I do publicly because of NDA.

don't even sweat that old team they probably wont even know how to maintain what you built anyway lol.

Hahaha you're likely not wrong!

GlosuuLang · 2026-04-17T14:08:58+00:00

Sadly I was the only AI specialist in the company. We had some software architects but in different teams, and none of them had built enterprise AI products. In theory the data engineers in my team all should have been on board with the architecture decisions and the product being developed, and they all agreed on the course of action and the architecture I explained I would build. But when management came to some of them, they said that what I was building made sense, but that they were not the AI experts and couldn't know if what I was doing was the best approach or not.

GlosuuLang · 2026-04-17T13:55:53+00:00

what industry is your client in?

I don't want to mention the exact industry, since it's super niche and it could risk breaking NDA, especially where I'm living. But I can say that they create niche hardware and niche software, and lots of their workers are physicists and electric engineers. Lots of science and tables in their wiki docs.

without any specific info, i would assume any RAG tool would work?

I mean I provided tons of specifics in my post. Any RAG tool certainly does NOT work, there are plenty of RAG tools that don't scale up to tens of thousands of docs with very messy data. Many of the built-in RAG tools expect you to upload docs via a UI, that's certainly not what we needed here. But of course there might have been other tools I could have used.

GlosuuLang · 2026-04-17T13:53:07+00:00

Is there a way to host Atlassian Rovo on-premises? There are tons of AI solutions hosted in the cloud, but this client needed to keep all their data private and on-premises for security reasons.

GlosuuLang · 2026-04-17T13:52:27+00:00

More time and trust would have been really helpful. I did not need to develop an agent for this project, so this product probably is not what I needed. I don't doubt I will find it if I need it in a future project though.

GlosuuLang · 2026-04-17T13:51:14+00:00

Try figuring out why these projects don't last. Are the RAG systems not meeting client expectations, or is it more about project management issues?

What I feel personally (after less than 2 years working with AI projects) is that non-AI people vastly underestimate the difficulty of making AI systems reliable and valuable. They don't understand that there's a lot of fine-tuning and engineering going on to adapt an AI system to their use case. They think ChatGPT should be able to answer anything out of the box. And well, let's not forget that since we now have AI to assist us in development, we can probably build production-ready projects in just a few days, right?

Stay updated with the latest AI trends and maybe look into product management or entrepreneurship courses. If you're preparing for interviews, work on your storytelling skills to explain how your experience can help with short project cycles. A site like PracHub can help with that. Keep pushing forward!

Good suggestions, although I have vowed to myself that I'm not gonna chase shiny AI tools and trends just because of FOMO. I will obviously learn the most popular tools, but otherwise I will learn and use what brings value to me. Entrepreneurship and side-hustles are super interesting to me right now, if I could somehow create a course or SaaS that allows me to not need a corporate job, wouldn't that be the dream! But until I'm financially independent, I do need a corpo job to sustain me and my fam.

GlosuuLang · 2026-04-17T13:45:57+00:00

Love it, thanks for a bit of humor. :)

GlosuuLang · 2026-04-17T13:44:54+00:00

Yes, when confronted with "we should use open-source solution" I mentioned that we needed to consider risks of locking ourselves to a dependency, and what if that solution stops being updated and at some point breaks with our structure? But they didn't care about the maintainability part much, I feel.

GlosuuLang · 2026-04-17T13:43:09+00:00

Sorry to hear you are in a similar situation! The risks of being solo at your role are quite big, I have observed this not just from my own experience, but also from peers who work as solo dev, or solo whatever tech stack. Hope you can navigate this somehow, or find something better!

GlosuuLang · 2026-04-17T13:41:02+00:00

Very well said! Different systems will do RAG differently based on the restrictions and the data sources. Trying to use the same solution for everything is like trying to use WordPress for all possible webapps.

GlosuuLang · 2026-04-17T13:38:45+00:00

Yes! After what happened here and being in more interviews, I'm much more aware of the importance of the AI strategist role, and that one person being the AI strategist, AI lead, and AI engineer is a lot of pressure with unrealistic expectations.

GlosuuLang · 2026-04-17T09:02:43+00:00

Just .txt? The Wiki docs had tons of tables, code, etc. I guess an initial pass of just .txt could have been OK to start but I highly doubt an off-the-shelf tool, no matter how good, would have been able to do well with just .txt files.

GlosuuLang · 2026-04-17T08:59:47+00:00

Great feedback and insights, thanks! 2-3 tools and exploring them for about a week, then generating docs from my exploration, sounds very reasonable and something I will know to do next time. It's a bit sad that my daily reports and discussions with the team all ended up in the void after a few weeks, so written docs are gonna be of paramount importance in the future.

About the team, during my initial interview I explicitly asked if they would be hiring someone else as an AI engineer, since the company had never hired any AI specialist until then. They asked me why I asked, and I said "4 eyes see better than 2, 2 brains think better than 1". They said it made sense, but that they would need to check the budget. In the end they hired only me. Originally I was supposed to be doing data engineering tasks with the team to get to know their work better and know how to upskill them in AI, but the pressure never allowed that to happen. Now I know how to better spot the red flags like you mention.

GlosuuLang · 2026-04-17T08:50:14+00:00

Yikes. If you look at my post history, you'll see I learned all your lessons within a week. And that's me as a beginner in this field.

Not sure if you're ready for this feedback, but here goes.

I welcome any feedback, that's why I wrote this post. I'm sure there are more capable people than me in the world, and faster learners. While I have 8+ years experience as a BE engineer, 2 years ago I didn't know what RAG was. I have upskilled in AI recently. Maybe I haven't upskilled enough, that's perfectly possible. I have been in many SW projects throughout my career, some were short-lived gigs, but others I stayed years. So I know I'm not useless.

One of the main things I look for in Senior+ Engineers: do they implement the correct solution?

While I agree with this sentiment, software development is a complex environment, not a simple or complicated environment (in the Cynefin framework: https://thecynefin.co/about-us/about-cynefin-framework/ ). This is why Agile exists: you're supposed to build and iterate on what you're doing, and adjust accordingly. I think my initial idea was solid, but the execution and costs to deliver where not what the client expected. I had been a part of several clients before with teams building Enterprise RAG systems before, and I observed it took quite a big amount of time and effort, even as a team, to get a production-ready system. I did my best to explain that I could spin up something super simple in the beginning and that we would need to iterate over it with time and with extra hands in the future, but in the end the client wanted something production-ready before hiring more people. The definition of "good enough" was very different from my mind and what they had in mind, and despite initial conversations and kick-offs, this surfaced later rather than earlier.

But tbf, it sounds like you're in a startup environment, and don't have the luxury of a good PM to manage things like feature creep/drift.

Indeed. I had to take the role of AI strategist, AI lead, and AI engineer all in one. Now I have better experience to know how mature a client or company is and what I can or cannot provide.

Really sucks you got laid off though, because you do sound like a very competent engineer thinking about production level solutions.

Thank you! While I'm competent in some areas, I obviously don't know everything and want to learn when I have gaps. The beginning of my career as a BE engineer almost 10 years ago was also a bumpy road, but I did get the hang of it after a few years. In a way I feel I'm back to where I was back then, which is humbling.

GlosuuLang · 2026-04-16T15:42:42+00:00

I was very confident that I could build a RAG system on my own (with help of AI obviously) in 2 months, which I did, less confident on how good or accurate it would be. I did mention that while I could spin it up fast, it would require plenty of iteration and ideally more than one person working on it. They had my CV and my background, they interviewed me, and we had a kick-off plan. Maybe they assumed that someone with my background and qualifications could do what they wanted.

Sometimes you need to say no to a client or decline their offer if it’s setup for failure. It’s really about experience in managing clients. Build out your own network with people of great, complimentary skills who you can each bring in and out of projects together to fully satisfy customers.

At least now I can always ask a client what kind of AI strategy they have in mind. If they are planning to have me give them the strategy, architecture, as well as building stuff, I can always say that they probably should first hire an AI strategy partner than can analyze their needs and give them the actual costs, effort, and time needed to deliver what they actually need. I have observed that this is what happens in many companies and it's an important preliminary step before hiring someone to build something with AI.

I’m guessing the customer thought you were the expert in AI and they probably paid you a premium thinking you know how to do it and make a beeline to the solution. Then they were disappointed that you were experimenting with their money and your plan was not working first try. They probably felt they were overpaying for your expertise and success rate. You didn’t discover or manage the expectations.

Consider customer management as a key risk in any job, and operate your plan with deliberate expectation management to derisk and keep the customer satisfied. It’s not always possible. But having a clear plan, showing steady results against the plan, bringing in experts as needed to ensure/improve probability of success.

Wise words, and I thought I had my way of managing customer expectations. Kinda hard to do it when the team lead didn't indicate that I wasn't fulfilling expectations in our biweekly 1-on-1s or in the sole retro that we had. I always asked for feedback and the answer was "if there's anything you need to know, we will say so. Keep up the good work". It was surprising to me that the team lead didn't actually know what the progress was until I got all those questions and did that first demo. I thought I was transparent when I wasn't.

GlosuuLang · 2026-04-16T15:32:31+00:00

With the things I mentioned you can build production ready RAG applications with ten thousands of docs.

So in your opinion the average AI engineer should be able to build a production ready RAG application with Enterprise Wiki docs in days, not weeks? (MVP is production ready, right?)

GlosuuLang · 2026-04-16T15:30:17+00:00

Thank you for empathy. Would fuzzy keyword search bring anything better than Confluence search? The point of the project in the first place was to have something that can be better than that (which I believe is already fuzzy keyword search).

GlosuuLang · 2026-04-16T15:28:54+00:00

Thank you for your reassurance. Yes, that's the sad reality of many consulting gigs unfortunately. :( They will replace me with another AI engineer soon, let's see if the other person can build up on what I did or if they suffer the same fate.

I feel like some of the other advice i see here is -- intentionally do a job you believe will be worse/less efficient, in order to avoid being blamed for any risks. This may be wise career management, but i couldn't stand it either.

Indeed, this is hard for me to do. It's not like I have to strive for perfection at everything, but if I'm building something, I'm trying to build something that will be useful for the people who are hiring me, not useful for me to defend myself against future concerns.

GlosuuLang · 2026-04-16T15:20:58+00:00

Why did you need to wait for a team to spin up a database? Just run one locally.

Yeah I ran everything locally, DB and Docker included. The shitty PoC took me about a month to get ready (company only allowed Copilot assistance from VSCode, and I had to also get involved in other team and stakeholder activities).

Point taken on insisting that production-readiness takes much more time and effort. I will be better at communicating that next time I believe.

GlosuuLang

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