Select Star SQL
An interactive book to master SQL through real-world data.
🚀 The definitive roadmap to becoming a Forward Deployment Engineer (FDE). Master AI Agents, Enterprise Data Architecture, and Strategic Consulting. Bridging the gap between HQ and the field. Inspired by the "Delta" role at Palantir, OpenAI, and Scale AI.
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
An interactive book to master SQL through real-world data.
The "Bible" for understanding how data systems actually work under the hood.
The standard for turning "Data Engineering" into "Analytics Engineering".
A critical tool for fast, local analysis of client CSV/Parquet files without setting up a full cluster.
The definitive guide to building secure, resilient, and cost-effective systems on GCP.
Essential reading for understanding how traffic flows inside a cluster.
The documentation you will live in daily.
Hands-on labs for BigQuery and Dataflow.
A critical skill for FDEs working with sensitive enterprise data.
Specifically the "Monitoring" and "Incident Response" chapters to keep client deployments alive.
How to move from being a "vendor" to a "partner".
The gold standard for executive communication.
Sounds cliché, but vital for dealing with resistant IT staff at client sites.
Frameworks for thinking about business problems like an engineer.
The mandatory "Origin Story" of the FDE role.
Real-world case studies on deploying GPT-4 into complex workflows (e.g., Morgan Stanley, Harvey).
Focus on GKE, BigQuery, and Gemini Enterprise Agent Platform (formerly Vertex AI) enterprise patterns.
Deep dive into the "Evals" mindset required for production AI.
(formerly Vertex AI Gen AI Evaluation Service): The unified service for both Rapid Evaluation (synchronous, for dev/test) and Pipeline Evaluation (asynchronous, for massive datasets).
(formerly Vertex AI Model Monitoring): Essential for "Day 2" operations. FDEs set up monitoring to detect Prediction Drift and Feature Attribution changes in production, ensuring the agentic system doesn't degrade over time as client data evolves.
Master clustering and partitioning for TB-scale client datasets.
A critical skill for FDEs working with sensitive enterprise data.
The documentation you will live in daily.
(Cloud Trace, Cloud Logging, Cloud Monitoring — formerly Stackdriver): Tracking agent latency and debugging failed tool calls in the field.
Integrated with ADK to visualize exactly where an agent's "chain of thought" broke.
The ultimate resource for architecting systems that don't crash under client load.
Start here to build your first multi-agent team.
The opinionated lifecycle tool for ADK. Install once, drive from any AI coding agent — or standalone from your terminal.
Source, install instructions (uvx google-agents-cli setup), and skills reference.
The Google Developers Blog announcement from Google Cloud Next '26.
Companion Google Cloud practitioner deep-dive.
End-to-end walkthrough of the scaffold → eval → deploy → publish loop.
Coding-agent-driven variant of the same lifecycle.
Production-ready templates with built-in CI/CD and evaluation.
Best end-to-end RAG education.
The DoD's centralized repository of pre-hardened, STIG-compliant, continuously-scanned container images. If a base image isn't in Iron Bank, it typically can't run on Platform One clusters.
/ MicroK8s / k0s: Single-binary Kubernetes distributions designed for edge and disconnected environments.
Google's managed-style Kubernetes running inside a customer's own data center or air-gapped enclave, with periodic sync to the control plane.
The DoD's DevSecOps reference platform — read the docs even if you're not building for DoD; the patterns transfer directly to any regulated on-prem client.
(the 110 requirements that currently underpin CMMC Level 2) and Rev. 3 (May 2024, 97 requirements — the future baseline).
The canonical architecture doc for accredited software factories.
Cosign, Rekor, Fulcio — the modern supply-chain-security toolkit that has become table stakes in accredited environments.
A concrete walkthrough of getting Kubernetes running without a package repo.
Real-world case study of an AI platform designed for disconnected tactical operations.
The gold standard for executive communication.
(Mutually Exclusive, Collectively Exhaustive). Ensure your project plan covers all bases without overlapping work.
Frameworks for thinking about business problems like an engineer.
Learning to identify the "crux" of a client's problem.
A critical tool for FDEs to document why a certain design choice was made at a client site.
A masterclass in integrating thousands of disparate data sources (beds, staff, PPE) into a single "Operating System" in weeks.
How FDEs turned 100,000+ PDFs of financial research into an internal "Assistant" that maintains the bank's strict compliance standards.
Deploying computer vision models to the "Tactical Edge"—processing satellite and drone data where internet is intermittent.
Using GCP to modernize manufacturing and deploy AI across the supply chain.
The "Bible" for understanding how data systems actually work under the hood.
How to move from being a "vendor" to a "partner".
(Barbara Minto): The McKinsey standard for communication. Learn to lead with the conclusion and support it with data—essential for talking to client executives.
(Gregor Hohpe): Essential for Phase 2. It teaches you how to "glue" legacy systems together using messaging, gateways, and translators.
(Will Larson): FDE is often a "Staff-plus" role in terms of scope. This book helps you navigate the high-level technical leadership required at client sites.
The ancestor of GCS (Google Cloud Storage).
The foundation of NoSQL on GCP.
The paper that started the Transformer/LLM revolution.
The logic behind how Agentic systems (like Google ADK) actually work.
The best podcast for the "AI Engineer" era. Deep dives into RAG, Agents, and Evals.
Interviews with the people actually building the frontier models you will be deploying.
Search their archives for "GCP," "Palantir," or "Distributed Systems".
Vital for staying updated on the "Modern Data Stack".
A weekly summary of AI progress and—crucially—AI policy/safety.
A non-official but highly curated list of every update in the Google Cloud ecosystem.
Deep technical analysis of LLM training and alignment.
Insights into how big tech companies actually operate and ship software.
Weekly deep dives on production LLM inference: model selection, cost and latency tradeoffs, and the serving failure modes that surface when a demo meets a client's hardware.
A fantastic archive of CS paper summaries.
Incredible deep dives on building production-grade ML and Recommendation systems.
List of useful resources about Data, AI & Cloud.
jaywcjlove/awesome-mac
 This project is dedicated to collecting high-quality macOS software and organizing them systematically by different categories for easy search and use.
serhii-londar/open-source-mac-os-apps
🚀 Awesome list of open source applications for macOS. https://t.me/s/opensourcemacosapps
ramitsurana/awesome-kubernetes
A curated list for awesome kubernetes sources :ship::tada:
sindresorhus/awesome-nodejs
:zap: Delightful Node.js packages and resources [BECAUSE OF TOO MUCH SPAM AND LOW-QUALITY SUBMISSIONS, SUBMISSIONS ARE PAUSED TEMPORARILY]
frenck/awesome-home-assistant
A curated list of amazingly awesome Home Assistant resources.
vsouza/awesome-ios
A curated list of awesome iOS ecosystem, including Objective-C and Swift Projects