标签：#agenticengineering

What the court actually held Amazon sued Perplexity in November 2025 over its Comet browser, pleading the federal Computer Fraud and Abuse Act and California's Comprehensive Computer Data Access and Fraud Act. A district court granted a preliminary injunction in March 2026. The Ninth Circuit stayed it pending appeal, and in August 2026 vacated it. The reasoning is the part worth carrying away. On the record before the panel, the systems were being accessed by Amazon's own customers, signed into their own accounts, using software they had chosen. Perplexity was not the one accessing Amazon. On that basis Amazon was unlikely to prevail on a statute written about unauthorised access. It is the first federal appellate ruling on whether AI agents acting for a user may access an online platform, and the panel was careful to say it was deciding that record rather than announcing a doctrine. What it did not hold It did not say agents are welcome, and it did not say a site has lost control of its own front door. Contract claims were not what the panel found weak. Terms of service, trademark questions and state-law theories are all untouched. A different record with different facts, particularly one where the agent operates at scale rather than for one signed-in customer, could come out differently. The useful summary is narrow and worth stating without decoration: computer-misuse law is a weak instrument against software a customer chose to run on their own account. The distinction the ruling turns on Crawler User's agent Acting for Its operator One signed-in customer Scale Many sites, high volume One session at a time Authenticated Usually not As the customer Data ends up In the operator's product In front of the person who asked The ruling's reasoning Does not apply Applies Most blocking rules in the wild do not make this distinction. A blanket refusal of automated access catches a customer's own agent alongside the scraper it was aimed at, and those two are commercially o

DISCLAIMER: This post was written entirely by me! I used AI for a little research, spelling, grammar, and comprehension checks. This post was originally shared on Hackernoon Entertain me for a moment, let's appreciate where we are today by understanding where we've been… or at least, where I've been. I remember when I first learned to code. I was bad, like really bad. But I was so curious! It all started by writing some VBA in an MS Access Database to create an IT Inventory app in the late 90s. Then I learned JavaScript, ASP (without the .Net), then C#, .Net ( I still have my .Net for Dummies book, see below) , jQuery, Python, Java, Angular, ReactJS, and Python again (yeah, had to relearn that one for some reason), and I'm sure there are others in there I forgot about. Learning to write code was rewarding! There were those days I'd spend hours on a bug, only to realize I didn't initialize the variable or forgot a semicolon. I learned .Net over a weekend thanks to the above book. I never became an artist of the craft, like some of my colleagues have (you know who you are: Josh, Kevin, and many others), but I knew how to build anything. I loved that ability: I could build anything. Pure joy! If you haven't had the joy of learning to code, do your best to learn it, because you can't prompt your way to being a Senior Engineer . As I progressed in my career, I became an architect and senior lead. I started off by leading a single engineering team, and now I support large programs and teams. All the while, I never let go of hands-on-code. I still love coding for work and my myriad of side projects. Then, a few years ago, this GenAI thing showed up. Put me in that group of: oh-no-there-goes-my-joy. Joy, yes, not my job. I love my job because I get to do what I love. I loved the dramatic rollercoasters: architecting a perfect solution, realizing it's wrong, getting to write every line of code, chasing impossible bugs, panicking with deadlines, late nights chasing hot fixes,