StackPilot
826 posts

StackPilot
@TheStackPilot
Backend Engineer (7+ yrs) | Real production lessons on System Design, Scaling & Debugging in Spring Boot Daily threads + quick tips | DM for collabs
Katılım Mart 2026
802 Takip Edilen716 Takipçiler

Backend engineering is basically:
“Everything is working fine”
until one small config changes and suddenly:
Kafka stops consuming
Redis starts timing out
one microservice dies silently
alerts explode at 2AM
#BackendEngineering #Microservices #Java #SpringBoot

English

Looking to #connect with:
.Developers
.Indie Hackers
.Solopreneurs
.Designers
. Open-source
. software developer
Let's connect
#buildinpublic
English

gm @X
I’m looking to #connect with people interested in
- #buildinpublic
- founder
- indie hcker
- LLM (deepseek, Kimi, Claude, GPT)
- AI agent
- GTM
- B2B SaaS
- Local business software
Tell me what you build. join the builder community! Let’s connect and grow together
English

Hey @X
I'm looking to #connect with people interested in:
- SaaS
- Startup
- Marketing
-SaaS
-Tech
-Automation
-AI tools
- Mobile Development
-Web APP
-Devs
Let's grow together 🤝
#letsconnect #buildinpublic
English


Your microservices crashing at 3 AM?
Build autonomous self-healing with Spring AI + observability loop:
• Observe → Plan → Act → Learn
• LLM decides the fix and applies it
I’m prototyping this right now – already auto-fixed OOM and image-pull errors.
Would you trust an AI to fix your prod issues? Yes or no? Vote below 👇

English

LLM says ‘I’ll call the weather API’… but how the hell do you actually make it happen in code?
Spring AI tool calling does it in 5 lines:
• Define @ Tool
• Add to ChatClient
• LLM decides when to call
No more prompt hacks. Production-ready calling.
Tried tool calling? Did it actually work first try? 😂 Drop your story 👇

English

@sama 1 billion images?! 🔥
India is not just using AI, we’re absolutely flooding it…
From wedding invites to cricket memes, everyone’s hooked. What’s the wildest image an Indian has generated so far? 👀
English

Plain Postgres just got superpowers.
PGVector + Spring Boot = production-ready vector search in 10 lines:
• Add the extension
• Store embeddings
• Similarity search with @ Query
No extra DB, no extra cost. I switched last month and never looked back.
Still using a separate vector store?
Why? Tell me below 👇
#BackendDev

English










