Merchants of complexity strike again with Google's A2A joining Anthropic's MCP. If AI is supposedly marching toward superintelligence, why are we creating more layers of abstraction instead of simplifying?

I'm not jumping on the MCP bandwagon just for LLM context. OpenAPI specs and REST APIs over Unix domain sockets already solve most of these problems effectively with mature tooling and adoption.

The promise of AI-assisted development should be simplification, not more protocols and abstractions.

Everyone gets knocked down; the difference is who stays down.

When you’re on the ground, you’ll hear people saying, ‘That's not fair’ or ‘That shouldn't happen.’ The longer you lie there, the louder the voices become.

Getting up isn’t easy, but it’s the only way forward.

Sometimes the best engineering is hitting ⌫

Of course, there’s more to refactoring code than deletes.

As LLMs grow more capable at reasoning and specialized tasks, we should question our reflex to add more abstraction layers. The future of AI isn't about building more complex frameworks - it's about achieving more with less. True innovation often means elegant simplification
#ai #ml #kiss

Been seeing a lot of noise about O3 and the usual "end of SE" hot takes 🙄

But hey, here's something actually interesting that's flying under the radar - ModernBERT just dropped, and it's pretty sweet. 8x longer sequences and way faster processing!

huggingface.co/blog/modernbert

Just paid $195 for pest control... or wait, $201.96 because apparently my credit card is also a pest that needs controlling. 🙄 FedNow, where you at?
#InterchangeFees #DeathByAThousandFees

“Stop trying to be spectacular. Start being consistent.”
—Shane Parrish

💯 The best engineering teams I've worked with focused on being boringly reliable rather than trying to be super smart.

"Just a ChatGPT wrapper"
"Just a database wrapper"
"Just an AWS wrapper"
"Just a CRUD app"

Every meaningful software product wraps powerful primitives with purpose-built abstractions that solve real problems. The value is in how you orchestrate and deliver.

#buildinpublic #buildwithai

During yesterday's OpenAI outage, Brain Studio's observability caught the disruption immediately. Our fault tolerance kicked in - automatic retries and fallbacks kept customer systems running. Solid engineering practices matter - especially with AI.
#BuildWithAI #BuildInPublic

Languages as personalities:

Java: Corporate vet who memorized design patterns

Go: Efficiency expert optimizing morning routines

Rust: Safety inspector requiring permits for everything

TypeScript: Java's cousin who does frontend

Python: Prof who knows everyone

(Java dev for 15+ years 🙂)

How do you know if your LLM prompts are actually working?

We built internal tools to find out. Now making them open source. Brain Studio helps you track prompt performance, catch regressions, and optimize costs - across any LLM provider. First preview next week.

#BuildWithAI #BuildInPublic

1/4
After evaluating Java libraries for LLM integration, we identified a need for a minimalist solution focused on modern Java features. While comprehensive libraries like Langchain4j serve many use cases well, we're developing an alternative that prioritizes simplicity and performance.

1/4 Traditionally, we've approached business software with a "one-size-fits-most" mindset, building highly abstract, configurable systems with extensive customization options.

First principles rethinking: Why use 20 rigid tools when AI can synthesize what you need? Combining LLMs with genetic algorithms to evolve software that adapts to each business. Moving from Software-as-a-Service to Software-that-Serves!

🚨 Real talk: AI wrote perfectly-looking code but overwhelmed the DB with uncommitted transactions piling up. Those 5-min app demos are misleading - AI code needs extra scrutiny, not blind trust.

The merchants of complexity in software are living on borrowed time. AI is the great simplifier. Soon, we'll wonder why we ever needed all those abstractions. The future is elegantly minimal code.