IT Guy. Poker player. Father of five Gen-Z adults. Founder of https://mach9poker.com/, http://ledga.us/, and creator of https://sharpee.net/
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David Cornelson here. Tons of dev, architecture, strategy, and advisory experience looking work. I'm well aware of the reset in pay at the moment and happily willing to adjust accordingly.
Location: Chicago/IL/USA
Remote: Y
Willing to relocate: Y (SF, DC, Raleigh/Durham, maybe Seattle/Austin)
Technologies: AWS, Azure, C#, .NET Core, Domain-Driven Design Modeling and Development, Event Storming Facilitation, all data storage types. GenAI dev/arch integration expert.
Email: Connect via LinkedIn
Yes and for crud systems relational is fine because you're unlikely to over-complicated your architecture. But when a system starts talking to other systems and its bounded contexts become complex, alternate solutions should be sought.
The problem with "schema change", and I did this for decades, is that it's always a massive blocker. In some companies the data architects had to approve and implement schema changes. You could wait days for that. NoSQL allows you to modify the document surface in mostly non-breaking change ways OR it's easier to version your APIs to handle different document versions.
Simple CRUD: Any data store is fine.
Complex multiple bounded contexts: Choose the appropriate data store for each bounded context accordingly.
My point was no one should be reaching for a relational database or starting with an ERD to build a system. Document behaviors. Model the system. Let the system decide what data storage it requires.
I was inspired by this. I made a Claude skill to take my resume and compare it to any job description to point out viability and gaps. Pretty cool skill. I'll post it somewhere.
I've not seen anything from the base models that replaces my engineering harness (workflow). There's a significant gap between what a generic LLM does and the domain I work in (software construction for complex applications).
- GenAI becomes a foundational requirement for tech and non tech sectors. If you’ve refused to engage, you’ve self-selected out of any of those sectors.
- GenAI usage shifts down to just the tech sector, but in an integrated fashion where current engineering practices are still desired. Everyone survives, but pay scales are adjusted down by a not-insignificant amount.
- GenAI bubbles badly, OpenAI and Anthropic merge with Google/Microsoft/Oracle/IBM/???. Tokens become extremely expensive and no one is leaning into agentic integration. Everyone thrives.
There are a number of reasons I’d site for the current job market tightness:
- political: there’s an enormous amount of uncertainty here. All businesses make plans and uncertainty puts them all on pause.
- economic: related to political, but we’re teetering on a very bad recession. Watch where national oil reserves go.
- AI: I throw this in with every new technology that comes out. There is always a period of chaos before normalization. We’re still in the chaos phase.
- Business Pain: Right now I don’t see any sector that’s in pain. Inflation has hurt consumers, but we’re still spending. When consumers lock it down, that pain comes back and job market shifts with it.
I have no solution other than figuring out a way to do your own thing. There’s no better time to be a founder.
The OPs domain/subject matter expertise is the part that should elevate their career. Understanding how large applications are constructed should also remain a pillar.
The coding and debugging part will be GenAI and possibly guardrails (harness engineering) tuned specifically for fintech, which they are also well-suited to implement.
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David Cornelson here. Tons of dev, architecture, strategy, and advisory experience looking work. I'm well aware of the reset in pay at the moment and happily willing to adjust accordingly.