From Prompts to Agents: AI Agent Skills in Claude Code

Snowflake Intelligence: The End of Dashboards?

Your dashboards only answer the questions you thought of last quarter. Every new question is a ticket, a dependency, or a gut call. Snowflake Intelligence wants to fix that -- a chat interface on top of governed enterprise data that turns plain English into SQL, runs it, and gives you a chart back. No analysts involved. Jelle builds the full setup live: semantic view, verified queries, Cortex Agent, access control. They get honest about what this actually requires -- data quality, governance, and whether Snowflake is worth the cost. Resources: - Snowflake Intelligence docs: https://docs.snowflake.com/en/user-guide/snowflake-intelligence - Demo code: https://github.com/datamindedbe/demo-technology-exploration Creators & Guests * Jonny Daenen [https://techex-data-ai.transistor.fm/people/jonny-daenen] - Host * Jelle De Vleminck [https://techex-data-ai.transistor.fm/people/jelle-de-vleminck] - Guest --- Click here to watch a video of this episode. [https://www.youtube.com/watch?v=Gp-BntPgpcU] Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb * (00:00) - Intro & meet Jelle * (02:04) - What is Snowflake Intelligence? * (02:54) - Demo: talking to your data * (10:36) - Where it fits & how it works * (15:14) - Build: the Semantic View * (22:37) - Build: the Agent * (29:20) - Challenges & data quality * (34:26) - How ETL is evolving * (40:33) - Will this replace engineers & analysts? * (43:23) - Is Snowflake worth the cost? * (45:14) - How do you get started? * (50:06) - Summary & takeaways --- Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype. Music by Aleksandr Karabanov from Pixabay

AI Workflows in Agno: Building Deterministic Agents

Enterprise data is full of sensitive information: different teams, different access rights, different rules. When you ask an AI agent a simple question and get "access denied," it's not a permissions bug. It's a design problem. Pascal has been exploring how to tackle this using Agno, an agent framework built around deterministic workflows. Instead of letting a single agent roam freely across your data, Agno lets you build specialized agents, each with its own access rules and instructions. Workflows orchestrate these agents with guardrails that keep humans in the loop when it matters. In this episode, Pascal Knapen, CTO at Dataminded, demos the full flow: from a natural language question, through an access check, to a verified answer. We explore how skills differ from workflows, how Agno handles dynamic agent creation and deployment, and how LLM-based evaluations act as a quality judge for agent responses. Additional Resources: * Demo code: https://github.com/datamindedbe/demo-technology-exploration/tree/main/demos/agno-workflows Intro music by Aleksandr Karabanov from Pixabay * (00:00) - Intro: AI agents and enterprise data * (01:50) - Two ways to give AI access to your data * (03:23) - Skills vs Workflows * (04:45) - Demo: AI with controlled data access * (07:45) - The workflow is deterministic - the agents aren't * (09:13) - Demo: evaluations & reliability * (11:00) - Code walkthrough with Agno * (17:45) - Why Agno? An honest take * (19:46) - Identity & exposing as an API * (20:24) - Takeaways

Managing Airflow at Scale using the Flowrs TUI

Jan opens 12 browser tabs every morning to check overnight pipelines. Log in, check, close. Twelve times. So he built a terminal app instead. Flowrs is a TUI for Apache Airflow written in Rust. Navigate all your environments from the keyboard, drill into failed tasks, tail live logs, bulk-mark runs -- no browser, no mouse. In this episode Jan demos it live, walks through the architecture of a TUI (event loop, state, render), compares the main frameworks (Ratatui, Bubble Tea, Textual), and gives his honest take on whether agents will eventually replace tools like this. "Go forth and mulTUIply. Life is too short to click around." Resources: - Install Flowrs: brew install flowrs - GitHub: https://github.com/janbvanbuel/flowrs --- Creators & Guests * Jonny Daenen [https://techex-data-ai.transistor.fm/people/jonny-daenen] - Host * Jan Vanbuel [https://techex-data-ai.transistor.fm/people/jan-vanbuel] - Guest Click here to watch a video of this episode. [https://www.youtube.com/watch?v=KyO5oXboRtI] Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb * (00:00) - Introduction * (01:17) - What is Flowrs & Airflow? * (03:27) - Demo: Flowrs in action * (10:18) - The evolution of CLIs and TUIs * (13:07) - Why not just use agents? * (14:25) - TUI frameworks: Bubble Tea, Textual, Ratatui * (15:21) - What's up with the Rust hype? * (16:51) - Building the Flowrs UI * (19:20) - How to install Flowrs yourself * (22:34) - Takeaways & what's next --- Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype. Music by Aleksandr Karabanov from Pixabay

Building an AI Agent with Subagents and Skills

Every time you ask AI for help, it agrees. Fast, confident, and it never tells you your plan has holes. That's the problem Arete is built to fix. Jesus built a brainstorm agent on Claude Code skills that guides you through five phases -- Ground, Explore, Decide, Stress, Ship -- before you commit to anything. The output is an architectural decision record and an implementation plan you actually own. In this episode he demos it live, shows how parallel subagents work without polluting your main context, and answers the honest questions: tokens burned, vendor lock-in, debugging subagents, and whether this works with a team. Resources: - Install Arete: https://github.com/jesgarram/arete - Demo code: https://github.com/datamindedbe/demo-technology-exploration --- Creators & Guests * Jonny Daenen [https://techex-data-ai.transistor.fm/people/jonny-daenen] - Host * Jesús García Ramírez [https://techex-data-ai.transistor.fm/people/jesus-garcia-ramirez] - Guest Click here to watch a video of this episode. [https://www.youtube.com/watch?v=KExht8wZ2Ng] Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb * (00:00) - Intro & meeting Arete * (01:38) - The 5-step brainstorm workflow * (04:05) - Meta: This video was made with an AI skill * (06:02) - The demo: ground, explore, decide, stress, ship * (14:56) - Example results: ADR and Plan * (17:23) - Subagents and context engineering * (21:12) - Demo: the Researcher Agent * (22:48) - Practical concerns: vendor, files, big projects * (25:30) - How many tokens does it burn? * (26:51) - Control, agents vs skills, multi-human * (29:44) - How to install Arete * (30:44) - Wrap-up --- Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype. Music by Aleksandr Karabanov from Pixabay

From Prompts to Agents: AI Agent Skills in Claude Code

AI agents get messy fast once you move beyond simple prompts. Context windows fill up with noise, agents start reasoning in loops, and suddenly you're dealing with brittle behavior and hallucinations. Jesus walks through how Claude Code skills fix this -- packaging repeatable workflows into modular components that load only when needed. He demos two real examples: an Explain Code skill and a PR Review skill that forks context, limits tool permissions, and uses CLI commands to analyze pull requests. Resources: - Demo code: https://github.com/datamindedbe/demo-technology-exploration/tree/main/demos/agent_skills - Anthropic docs: https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview - Skills standard: https://agentskills.io - Curious about MCP? https://youtu.be/fIr55-koOJQ --- Creators & Guests * Jonny Daenen [https://techex-data-ai.transistor.fm/people/jonny-daenen] - Host * Jesús García Ramírez [https://techex-data-ai.transistor.fm/people/jesus-garcia-ramirez] - Guest Click here to watch a video of this episode. [https://www.youtube.com/watch?v=jlX4sTbNHpc] Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb * (00:00) - Introduction * (01:28) - Demo: Skills in Claude Code * (05:57) - How agents work: from prompts to context engineering * (08:19) - What are Skills? (vs MCP, RAG, Commands) * (10:33) - Building your own Skill * (15:20) - Skills vs MCPs * (16:29) - What about hallucinations? * (17:07) - Specs and Anthropic's Skill Guide * (19:28) - Skillception: a skill to create skills * (20:34) - Is MCP history? * (22:50) - Sharing skills & wrap-up --- Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype. Music by Aleksandr Karabanov from Pixabay