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3️⃣ 2️⃣ 1️⃣ Our free course on LLM evaluations for AI product teams starts today!

🎥 7 days of byte-sized videos into your inbox
⭐️ Certificate upon completion
👩‍💻 No coding skills required
👩‍🎓500+ students have signed up

You can still join the course👇
evidentlyai.com/llm-evaluation…
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GitHub shares their learnings on evals across LLM-powered systems – for code analysis, developer tools, security, data analysis, and other production workflows.

github.blog/ai-and-ml/llms…
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How DoorDash runs evals for support chatbots using simulated conversations - at scale: careersatdoordash.com/blog/doordashs…
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How Netflix evaluates the quality of show synopsis using LLM-as-a-judge approach:
netflixtechblog.com/evaluating-net…
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How Zalando builds a search quality assurance framework with LLM-as-a-judge:

engineering.zalando.com/posts/2026/03/…
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📌 In case you missed it

How to evaluate an AI agent?

Follow the tutorial as we:
1️⃣ Build an AI agent,
2️⃣ Create a test dataset,
3️⃣ Assess responses and tool choice,
4️⃣ Track the agent’s behaviour.

Follow the tutorial from our LLM evals course: youtube.com/watch?v=9KMmad…
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A Friday ML use case 📕

📚 From the database of 800 ML & LLM systems: cutt.ly/SwrZWL0g

How Uber improves driver availability at airports: Estimated time-to-request model, Earnings-per-hour prediction, and Driver-deficit forecasting.

uber.com/en-GB/blog/for…
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🦾 More AI agents aren’t always better.

Google evaluated 180 agent setups and found multi-agent systems help with parallel tasks but can hurt sequential ones.

The work also proposes a model to predict optimal agentic designs.

research.google/blog/towards-a…
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📌 In case you missed it

Let’s test your RAG system!

Follow the tutorial as we:
1️⃣ Build a RAG system,
2️⃣ Generate test data,
3️⃣ Evaluate answers for correctness and faithfulness.

Watch the tutorial from our LLM evals course: youtube.com/watch?v=jckp5R…
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A Friday ML use case 📕

📚 From the database of 800 ML & LLM systems: cutt.ly/SwrZWL0g

How GoDaddy built Lighthouse, an internal AI analytics platform: prompt engineering framework, model orchestration, solution architecture, and use cases.

godaddy.com/resources/news…
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Evidently AI retweeted
(policyNIM oss tool)

preflight command is working. when I provide a coding task, it kicks off a search through indexed policies to determine which rules are relevant for implementation.

@nvidia for embedding w/ @OpenAI + @lancedb for vector storage.

eval command is also lyAI for running eval suite.
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🚦 Meta’s “Agents Rule of Two”

According to Meta, AI agents should satisfy at most two of these conditions per session to reduce prompt-injection risk:

- Handle untrusted inputs
- Access sensitive data
- Change state / act externally

ai.meta.com/blog/practical…
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📌 In case you missed it

How do you know if your RAG works?

You need to check:
✅ Can it find the right information?
✅ Is the final answer complete, relevant, and free of hallucinations?

Watch the intro to RAG evaluation from our LLM evals course: youtube.com/watch?v=qI2qQf…
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A Friday ML use case 📕

📚 From the database of 800 ML & LLM systems: cutt.ly/SwrZWL0g

How DoorDash improves its RecSys using LLMs to bridge behavioral silos in multi-vertical recommendations.

careersatdoordash.com/blog/doordash-…
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💭 Can AI systems introspect?

Anthropic’s new research suggests Claude models can sometimes identify and describe their own internal states.

It’s still unreliable, but marks a step toward more transparent AI reasoning.

anthropic.com/research/intro…
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📌 In case you missed it

Can LLMs write engaging tech tweets?

Follow the tutorial as we:
1️⃣ Build a tweet generator,
2️⃣ Score its outputs with custom LLM judges,
3️⃣ Improve the results with prompt iteration.

Watch the tutorial from our LLM evals course: youtube.com/watch?v=KhkiM9…
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A Friday ML use case 📕

📚 From the database of 800 ML & LLM systems: cutt.ly/SwrZWL0g

How Shopify transformed its product classification system from basic categorization to an AI-driven framework using Vision Language Models.

shopify.engineering/evolution-prod…
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📚 Context is everything.

OpenAI shares how it built an in-house data agent that answers complex questions in minutes.
It uses 6 layers of context:

- Table metadata
- Human annotations
- Codex enrichment
- Company knowledge
- Memory
- Runtime context

openai.com/index/inside-o…
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📌 In case you missed it

Are LLMs good for classification tasks?

We built an LLM-based classifier for a travel support chatbot and compared its performance to a classic ML model.

Watch the tutorial from our LLM evals course: youtube.com/watch?v=Gl2X_o…
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A Friday ML use case 📕

📚 From the database of 800 ML & LLM systems: cutt.ly/SwrZWL0g

How Wayfair built Wilma, a customer service agent copilot: workflow, prompt templates, and the copilot’s evolution.

aboutwayfair.com/careers/tech-b…
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🤖 How to develop and deploy chatbots at scale?

DoorDash shares how they created a simulation platform and evaluation flywheel, allowing them to test chatbots with fast feedback loops and without production risk.

careersatdoordash.com/blog/doordash-…
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