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I load tested a Databricks SQL Warehouse as the backend for a high concurrency API, to find out whether you can skip the operational database.
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This is the story of how I overengineered a software project because I made the wrong assumptions too early.
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Over the last 3 years I’ve spent a lot of time building highly scalable Data APIs, to enable teams to access data from different sources with minimal effort.
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Reflecting back to the time I was deciding whether to start my own blog site has made me remember that it wasn’t an easy decisions.
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Over the past few months I’ve been using AI agents a lot to automate many engineering tasks that otherwise would take me much longer to do.
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Step 1 — Target Audience The Reader A junior, mid, or senior data engineer who builds data pipelines in the warehouse (DBT, Databricks, Snowflake) and orchestrates them with Airflow.
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Module 9: Ownership, security and new ways of working Closing section.
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Resources There Is an AI Code Review Bubble - Honest take on why most AI code review tools are fundamentally limited.
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Resources Claude Code: Agent Teams - Official documentation on running multi-agent teams with Claude Code.
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Introduction At this point we have already seen how to use spec driven development to create a structured engineering workflow and using feedback loops te ensure the code is validated and meeting the necessary standards.
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Introduction Once you get to the implementation phase, you can simply ask your agent to implement the task and end it there.
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Module 6: CLIs, MCPs and debugging Hands-on: attendees connect a CLI or MCP to their agent and use it in a spec or debug session.
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Module 3: Spec driven development First hands-on moment.
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Introduction — what you will have set up by the end of this chapter IDE agents vs CLI agents — the two flavours, narrow scope to CLI for this chapter Understanding the workspace — mental model of what the agent can see, do, and access before you install a…
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Module 1: How we got here Sets the stage.
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Coding agents work best when they have a good feedback loop they can use to verify their changes.
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Pablo Lopez Santori Edinburgh, UK | pablo.lopez.santori@gmail.com | github.com/wanderdust | wanderdust.github.io/newsletter Summary AI and Machine Learning Engineer with 6+ years of experience building production AI systems, from LLM-powered agents and RAG
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If you were to peek inside Postgres and see how the tables are stored, you’d be surprised they look nothing like the outuput you get when you do a SELECT query.
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This has been one of the years where I’ve learned the most things, probably since I first started learning programming almost 10 years ago.
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The hardware Compute nodes (thinkpads) NAS (Optional) Setting up the nodes 2.1) Installing Ubuntu Server 2.2) Setting up a static IP on the nodes See which is your ethernet name by looking at ip addr.
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I have passed the AWS Architect Professional exam with a score of 791/1000!
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In this post I wanted to describe the different options if you are considering a data role.
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Today I wanted to write about something that happens to me at work all the time: the process of asking for technical help, helps me discover the answer to my question.
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Typical Academic Roles (Career Progression) Role Approx.
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Slowly changing dimensions, what a confusing name.
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Interviewing for other jobs in tech can make you a more competent engineer.
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When working with distributed systems you can encounter terminology such as “replicas” or “standby” intstances.
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Practical strategies to protect your serverless applications from runaway AWS bills, including caching, rate limiting, WAF rules, and DynamoDB safeguards.
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GOAL: Highlight the differences between these strategies.
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After ignoring the whole “agent” hype for a while, I started to get that inevitable feeling of being left behind.
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I recently passed the AWS Solutions Architect Associate exam with a score of 848.
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Introduction This is a guide to myself if I need to deploy an Appsync App in the future.
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I recently had to run load testing for an API that fetches data from Postgres.
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In this post, guest writer Billy interviews Pablo on learning Dvorak.
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Replication refers to having copies of your data across different instances.
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Fiction Orbital This one tells the story of a team of 5 austronauts in their space mission.
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I currently have a basic setup in NeoVim: I use NvChad by default with treesitter to get pretty text highlighting, telescope to navigate files, conform for all my formatting needs and some python utilities such as pyright.
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In this post, I share how to build a Reverse ETL pipeline to upsert data from Delta (Databricks) into Postgres to provide sub-second response times to our tables.
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The other day my team came across a peculiar situation with our Postgres database.
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I recently needed to run load tests on a PostgreSQL database.
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We all know that person that always asks for unit tests on your Pull Request.
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Indexes are like going to the airport and looking at the signs to see where your gate is located.
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Learning To prepare for the exam I took the Udemy Kubernetes Certified Application Developer (CKAD) with Tests which I could access for free through my company.
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This is my story of how I went from non-tech into becoming a Machine Learning Engineer.