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The session was very structured, including real life examples which helped to better understand the scope of the solution and how it could be used in real life.
During the call, he shared his screen and explained step by step how to configure the model to reproduce my tone of voice. He also shared a useful template that helped me set everything up.
We discussed architectures, LangGraph, production challenges and important considerations when building multi-agent systems - explained in a very clear, structured, easy-to-understand way.
Browse cases
Turning a Topic into a CMS-Ready SEO Article with an Agentic Pipeline
I show the agentic pipeline I built and now use for ChefPassport: topic ideation -> outline -> long-form draft -> QA pass -> formatting -> CMS-ready output, with the prompts and checks at each step. Or share your current content workflow and we redesign it into steps you can automate.
Matteo Ressa
I help PMs and founders turn AI ideas into products that hold up in production: LLM pipelines, agent MVPs and real apps built with Claude Code. Ex-Amazon PM, MSc in AI.
Building a Production Web App Solo with Claude Code
Live demo: I open the real ChefPassport rebuild (700+ commits, Next.js + Supabase + Stripe, built with Claude Code) and show how I run it - CLAUDE.md and memory files, how I slice work into tasks, plan-then-build, tests and verification, and where it still goes wrong. Or bring your own repo or vibe-coded prototype: we review your setup together and agree the next three changes to make it reliable.
Matteo Ressa
I help PMs and founders turn AI ideas into products that hold up in production: LLM pipelines, agent MVPs and real apps built with Claude Code. Ex-Amazon PM, MSc in AI.
Making Your RAG Pipeline Reliable in Production
A 1:1 deep dive into production RAG architecture: walk through a proven retrieval pipeline (chunking, hybrid search, reranking, evals) or review your current setup to diagnose hallucinations and retrieval failures before scaling up.
Bobby Aryasomayajula
Senior GenAI Automation Expert at ALDI DX
Speech-to-Text Pipelines with Whisper
A hands-on build of a transcription pipeline on RunPod that takes audio or video in bulk and returns clean, speaker-labelled, searchable transcripts. It covers picking the right Whisper model and GPU, speeding up inference, splitting long files, separating speakers, cleaning up output, and running it as a Serverless endpoint so you only pay while files are processing.
Abhineet Dubey
AI Engineer crafting autonomous solutions
Build a Voice AI Agent That Answers Your Calls
A step-by-step build of a voice agent that picks up calls, understands the caller, answers from your business information, books appointments or captures details, and transfers to a human when needed. It covers the choices that decide quality: voice selection, prompt design for spoken conversation, interruption handling, and cutting response delay so the conversation feels natural.
Abhineet Dubey
AI Engineer crafting autonomous solutions
Scoping an AI Agent MVP Your Engineers Can Actually Build
I walk through how I wrote the PRD and MVP scope for an agentic customer-support co-pilot: choosing the first workflows, human handoff, traceability requirements, and the metrics that decide go/no-go. Or bring your AI feature idea or draft PRD and we tighten scope and success criteria together.
Matteo Ressa
I help PMs and founders turn AI ideas into products that hold up in production: LLM pipelines, agent MVPs and real apps built with Claude Code. Ex-Amazon PM, MSc in AI.
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