Lesson: Never underestimate an edge case in payment flows.
On https://t.co/Tn4xPmXzEU, we implemented resumable checkouts with signed resume tokens. Result: zero lost transactions.
Every edge handled, every webhook secured.
#TechTalks#BackendEngineering
Trending: Constraint Decay in LLM Agents. Garbage in, garbage grounded. If your RAG chatbot hallucinates, it's not fine-tuningโit's retrieval quality. Chunk well, retrieve smartly. #RAG#LLM
Founders: what manual task is quietly eating your week?
Data entry. Follow-up emails. Reporting. Onboarding. Invoicing.
Reply with your biggest time-suck and I'll tell you if (and how) it can be automated.
No pitch. Just free audits for the first 20 replies. ๐
@alexabelonix Thanks, Alexa! ๐ Curious what stack you're running for your AI sales SaaS โ always looking to compare notes on cost-efficient setups.
Always-on AI is a money leak.
Tip: Split tasks into cheap-triage (rules-based) and expensive-generate (LLM).
Example: Use simple keyword checks for initial input filtering, only trigger full LLM generation when necessary.
#LLM#CostOptimization
Building Farovu solo taught me: When you own DB schema to pixels, you cut through the fluff. Direct paths, no handoffs. But it's a double-edged sword.
What's your take on solo full-stack ownership? #FullStack#Development
@Jamesfrank55n Hey, instead of hiring for all these roles separately, I can build AI agents that automate most of them. From document processing and virtual assistance to social media posting, AI can handle the repetitive work with little to no manual effort. If you're open to it
Always-on AI is a money leak. Full LLM generation on every input scales cost with volume, not usage. Deferred drafting + cheap-triage/expensive-generate splits are your friends. Optimize or pay the price. #AI#CostOptimization
The push for 'always-on' AI is a money leak. Full generation on every input scales cost with volume, not usage. Time to get serious about deferred drafting, cheap-triage/expensive-generate splits, and caching.
#LLM#AIoptimization
If your AI agent can't handle failures gracefully, it's not production-ready.
The clever parts are never the problem. It's the messy failure handling that breaks in real-world scenarios.
Build robust, anticipate the unexpected. #AI#ProductBuilding
Building Farovu solo, I realized that full-stack ownership means you're both the architect and the debugger. A bug in the REST API delayed a feature launch by a week. Lesson: When you own it all, each decision is critical.
#FullStack#Building