Reviewing code generated by AI tools like GitHub Copilot, ChatGPT, or other agents is becoming an essential part of the modern developer workflow. This guide provides practical techniques, emphasizes the importance of human oversight and testing, and includes example prompts to showcase how AI can assist in the review process.
For both legacy codebases and larger pull requests in particular, a thorough review process is critical. Combining human expertise with automated tools can ensure that AI-generated code meets quality standards, aligns with project goals, and adheres to best practices.
With Copilot, you can streamline your review process and enhance your ability to identify potential issues in AI-generated code. — Read More
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The Last Software Engineer
For more than a decade, I have taught software engineers how to implement testing, React, Remix, MCP, and more
I built courses around practice. I would simulate a real work environment: a product manager gives you a task, you read the docs, you work in the codebase, you build the feature, and then you compare your solution with mine.
That was valuable because implementation was valuable.
It still is. But it is becoming less scarce.
AI coding agents are slowly eating away at the tasks software engineers have done for decades. — Read More
Terraform Audit Guide: Monitoring, Logging & Compliance
Running an audit on your Terraform code enables you to systematically review your IaC code and determine whether your infrastructure respects your organization’s compliance and governance standards.
In this article, we walk through a Terraform audit, what can/can’t be learned from Terraform’s state file, how to run a Terraform audit step by step, what are the most popular Terraform audit tools, and the best practices around Terraform audits. — Read More
Enabling a new model for healthcare with AI co-clinician
Health systems worldwide are striving for better outcomes, lower costs, and an improved experience for both patients and clinicians. However, progress is constrained by a global shortage of clinical experts, with the World Health Organization predicting a shortfall of more than 10 million health workers by 2030.
While AI is often seen as the key to bridging this gap, it has not yet been able to fully meet the needs of clinicians and patients. That’s why, today, we are announcing our AI co-clinician research initiative, to explore how AI could better amplify doctors’ expertise and deliver higher quality care to patients.
At Google DeepMind, our journey in medical AI has evolved from mastering examination-style tests of medical knowledge with MedPaLM, to matching physician performance in text-based simulated medical consultations with AMIE, including in real-world feasibility trial settings. We also have a long history of studying how clinicians and AI systems might work together. — Read More
China’s $1 Billion Robot Army Is Replacing Human Maintenance Crews with 8,500 AI Robots
Power grids worldwide face an aging infrastructure crisis, but China just announced a $1 billion solution involving 8,500 AI robots. State Grid Corporation of China plans to deploy this robotic workforce across 26 provincial regions by 2026, representing one of the most ambitious grid-specific robotics deployments ever attempted. Your energy bills and power reliability might never be the same. — Read More
Higgsfield AI for Creative Professionals: A Deep Dive
Higgsfield AI is a generative video model and platform designed for creating high-fidelity, controllable, and stylistically consistent video content from text and image prompts. Unlike many early-generation AI video tools that produce short, often disjointed clips, Higgsfield focuses on solving one of the biggest problems for professional use: consistency. It aims to give creators the ability to maintain the same character, aesthetic, and environment across multiple shots, making it a viable tool for narrative and commercial projects. — Read More
Salesforce Headless 360: Wrapping My Head Around It — Part 1
So, Salesforce did a thing to announce Salesforce Headless 360 at TDX last week and I’ve been wrapping my ‘head’ around it since then.
… So, what exactly is Salesforce Headless?
Salesforce defines it as ‘Everything on Salesforce is now an API, MCP tool, or CLI command, and agents can use all of it.’
There’s also a fairly bold punch line to go with it — ‘No Browser Required’ — Read More
As Deep as the Grave | Official Trailer (Val Kilmer AI Performance, 2026)
What If We Prompted AI for Outcomes Instead of Outputs?
I’ve been to a lot of meetups about AI in the last year. Across all of those there’s been a common refrain that gets repeated by the experts and the newly empowered noobs alike. “If you don’t know how to get what you need out of your AI tool, just ask it.” It’s one of the most powerful aspects of the AI revolution. You can’t ask a hammer how to build a cabinet. You can ask Claude how to build the web app you’ve imagined for the last 20 years.
In all of these cases though, the prompt is always focused on creating a specific thing, an output. However, there’s a question worth sitting with — one we’ve started discussing internally lately. What would it look like to prompt AI for an outcome instead of an output? — Read More
Apple UX Principle: How Simplicity Drives Apple’s 5–10% Conversion Rates
The Apple UX Principle is often misunderstood as a design style defined by minimalism and clean interfaces. In reality, what Apple Inc. has built is far more strategic. It is a system designed to influence how people think, feel, and ultimately decide.
This case study explores how Apple applies five core UX principles, usability, communication, functionality, aesthetics, and emotional connection, to create product experiences that consistently outperform industry benchmarks. More specifically, it examines how these principles contribute to Apple’s estimated 5–10% conversion rates, significantly higher than the typical ecommerce average of 2–3%.
The goal is not to replicate Apple’s design, but to understand the mechanisms behind its performance. — Read More
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