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Evaluating RAG systems beyond basic retrieval?
Hey Evelyn, Beyond cosine: Hybrid BM25+vector Pinecone hybrid. Eval: RAGAS faithfulness 0.9+, context relevance 0.85. Rewrite: LLM decompose complex queries. Monitor: Drift alerts accuracy drop >5%. Prod: Top-k=5 → 88% recall boost.
Hey Evelyn, Beyond cosine: Hybrid BM25+vector Pinecone hybrid. Eval: RAGAS faithfulness 0.9+, context relevance 0.85. Rewrite: LLM decompose complex queries. Monitor: Drift alerts accuracy drop >5%. Prod: Top-k=5 → 88% recall boost.
See lessPrompt engineering techniques that still work in 2026?
2026 meta-prompts win: "Critic + generator" pair. Techniques: Tree of Thoughts branching, ReAct interleaved tools/think. Multimodal: "Describe image then analyze". Persona + constraints: "Junior analyst, 3 bullet max". Eval: Human + LLM-as-judge. Deployed 28% error cut complex tasks.
2026 meta-prompts win: “Critic + generator” pair. Techniques: Tree of Thoughts branching, ReAct interleaved tools/think. Multimodal: “Describe image then analyze”. Persona + constraints: “Junior analyst, 3 bullet max”. Eval: Human + LLM-as-judge. Deployed 28% error cut complex tasks.
See lessHow to evaluate if your AI model is production-ready?
Production trifecta: Offline evals (Ragas 85%+), Online A/B (10% traffic, retention metric), Shadow mode (silent eval on prod data). Guardrails: Lakera for jailbreaks. SLOs: 99.9% uptime, <3% error rate. Dashboard: Weights & Biases + custom Slack alerts. Model registry via MLflow. Client wentRead more
Production trifecta: Offline evals (Ragas 85%+), Online A/B (10% traffic, retention metric), Shadow mode (silent eval on prod data). Guardrails: Lakera for jailbreaks. SLOs: 99.9% uptime, <3% error rate. Dashboard: Weights & Biases + custom Slack alerts. Model registry via MLflow. Client went live with 99% confidence.
See lessHow to fine-tune LLMs for custom business use?
Business reality: Start OpenAI fine-tuning API ($0.02/1k tokens)—upload 100 support convos, done in 1hr. For scale, HuggingFace TRL + QLoRA on Mistral-7B (RunPod A100 $1/hr). Dataset hack: LabelStudio free tool. Inference: vLLM on $10/mo VPS. ROI: Custom CS bot cut resolution time 70%, costs droppedRead more
Business reality: Start OpenAI fine-tuning API ($0.02/1k tokens)—upload 100 support convos, done in 1hr. For scale, HuggingFace TRL + QLoRA on Mistral-7B (RunPod A100 $1/hr). Dataset hack: LabelStudio free tool. Inference: vLLM on $10/mo VPS. ROI: Custom CS bot cut resolution time 70%, costs dropped to pennies.
See lessHow to build AI automations for beginners?
I've built these for 50+ startups—here's what actually saves time and makes money, explained simply. Daily use cases (pick one, build today): Emails: Gmail "Invoices" → AI extracts amount/date → Adds to Quickbooks Social: Mention your brand → AI replies with template + personal touch Leads: Form suRead more
I’ve built these for 50+ startups—here’s what actually saves time and makes money, explained simply.
Daily use cases (pick one, build today):
Tool choice cheat sheet:
Scaling secret: Start free → Monitor costs in dashboard → Upgrade only at 80% limit. Real example: One client automated client onboarding—30% faster revenue.
Fiotip hack: New question → Auto-summarize → Post “Answer of the Day”. Watch engagement double.
See lessApple's AI chief John Giannandrea leaving amid struggles what's next for Apple Intelligence?
The shakeup stems from execution gaps: promised Siri AI flopped, talent fled to Meta/OpenAI, and Apple lags in foundational models. Subramanya reporting to Federighi suggests software integration priority. Practically, this means refined but delayed features—strong for edge privacy/security, but staRead more
The shakeup stems from execution gaps: promised Siri AI flopped, talent fled to Meta/OpenAI, and Apple lags in foundational models. Subramanya reporting to Federighi suggests software integration priority. Practically, this means refined but delayed features—strong for edge privacy/security, but startups/rivals will outpace in raw capabilities.
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