A year back, this engineer titled his 2024 retrospective “interconnected themes galore”. That said, both new and expanded connections can sometimes lead to chaotic results, yes?

As any of you who’ve already seen my precursor “2026 Look Ahead” piece may remember, we’ve intentionally flipped the ordering of my two end-of-year writeups once again this year. This time, I’ll be looking back over 2025: for historical perspective, here are my prior retrospectives for 2019, 2021, 2022, 2023, and 2024 (we skipped 2020).

As I’ve done in past years, I thought I’d start by scoring the key topics I wrote about a year ago in forecasting the year to come:

• The 2024 United States election (outcome, that is)
• Ongoing unpredictable geopolitical tensions, and
• AI: Will transformation counteract diminishing ROI?

Maybe I’m just biased, but in retrospect, I think I nailed ‘em all as being particularly impactful. In the sections that follow, I’m going to elaborate on several of the above themes, as well as discuss other topics that didn’t make my year-ago forecast but ended up being particularly notable (IMHO, of course).

Tariffs, constrained shipments, and government investments

A significant portion of the initial “2024 United States election outcome” section in my year-back look-ahead piece was devoted to the likely potential for rapidly-announced significant tariffs by the new U.S. administration against various other countries, both import- and export-based in nature, and both “blanket” and product-specific, as well as for predictable reactive tariffs and shipment constraints by those other countries in response.

And indeed this all came to pass, most notably with the “Liberation Day” Executive Order-packaged suite of import duties issued on April 2, 2025, many of which were subsequently amended (multiple times in a number of cases) in the subsequent months in response to other countries’ tit-for-tat reactions, trade agreements, and other détente cooling-off measures, and the like.

My point in bringing this all up, echoing what I wrote a year back (as well as both the month and the year before that), is not to be political. As I’ve written several times before:

I have not (and will not) reveal personal opinions on any of this.

and I will again “stay the course” this time. Whether or not tariffs are wise or, for that matter, were even legally issued as-is are decisions for the Supreme Court (near term) and the voters (eventually) to decide. So then why do I mention it at all? Another requote:

Americans are accused of inappropriately acting as if their country and its citizens are the “center of the world”. That said, the United States’ policies, economy, events, and trends inarguably do notably affect those of its allies, foes and other countries and entities, as well as the world at large, which is why I’m including this particular entry in my list.

This time, I’m going to focus on a couple of different angles on the topic. Maybe your company sells its products and/or services only within the country in which it’s headquartered. Or maybe, on the opposite end of the spectrum, it’s a multinational corporation with divisions scattered around the world. Or any point in between these spectrum extremes.

Regardless (and regardless too of whether or not it’s a U.S.-headquartered company), both the tariff and shipment-restriction policies of the U.S. and other countries will undoubtedly and notably affect your business strategies.

Unfortunately, though, while such tariff and restriction policies can be issued, amended, and rescinded “on a dime”, your company’s strategies inherently can’t be even close to as nimble, no matter how you aspire to both proactively and reactively structure your organization and its associated supply chains.

As I write these words I’m reminded, for example, of a segment I saw in a PBS NewsHour episode last weekend that discussed (among other things) Christmas goods suppliers’ financial results impacts of tariffs, along with the just-in-case speculative stockpiling they began doing a year ago in preparation (conceptually echoing my own “Chi-Fi” pre-tariff purchases at the beginning of 2025):

The other angle on the issue that I’d like to highlight involves the increasingly prevalent direct government involvement in companies’ financial fortunes.

Back in August, for example, just two weeks after initially demanding that Intel’s new CEO resign due to the perception of improper conflicts involving Chinese companies, the Trump administration announced that it was instead converting prior approved CHIPS Act funding for Intel into stock purchases, effectively transforming the U.S. into a ~10% Intel shareholder.

More recently, NVIDIA was once again approved to ship its prior-generation H200 AI accelerators into China…in exchange for the U.S. getting a 25% share of the resultant sales revenue, and following up on broader 15%-revenue-share agreements made by both AMD and NVIDIA back in August in exchange for securing China-export licenses.

And President Trump has already publicly stated that such equity and revenue-sharing arrangements, potentially broadening to also include other U.S. companies, will increasingly be the norm versus the exception in the future. Again, wise or not? I’ll keep my own opinions to myself and rely on time to answer that one. For now, I’ll just say…different.

Robotaxis

Waymo is on a roll. The Google-sibling Alphabet subsidiary now blankets not only San Francisco, California (where its usage by customers is increasingly the norm versus a novelty exception) but large chunks of the broader Silicon Valley region, now including freeways and airports.

It’s also currently offering full service in Los Angeles, Phoenix (AZ), and Austin (TX) as I write these words in late December 2025, with active testing underway in roughly a dozen more U.S. municipalities, plus Japan and the UK, and with already-announced near-term service plans in around a dozen more. As Wikipedia notes:

As of November 2025, Waymo has 2,500 robotaxis in service. As of December 2025, Waymo is offering 450,000 paid rides per week. By the end of 2026, Waymo aims towards increasing this to 1 million taxi rides a week and are laying the groundwork to expand to over 20 cities, including London and Tokyo, up from the current six.

And this is key: these are fully autonomous vehicles, with no human operators inside (albeit still with remote human monitors who can, as needed, take over manual control):

Problem-free? Not exactly. Just in the few weeks prior to my writing these words, several animals have been hit, a Waymo car has wandered into an active police-presence scene, and they more generally haven’t seemingly figured out yet how to appropriately respond to school buses signaling they’re in the process of actively picking up and/or dropping off passengers.

So not perfect: those are the absolute statistics. But what about relative metrics?

Again and again, in data published both by Waymo (therefore understandably suspect) and independent observers and agencies, autonomous vehicles are seen as notably safer, both for occupants and the environment around them, than those piloted by humans…and the disparity is only growing in self-driving vehicles’ favor over time. And in China, for example, the robotaxi programs are, if anything, even more aggressive from both testing and active deployment standpoints.

To that last point, I’ll conclude this section with another note on this topic. In fairness, I feel compelled to give Tesla rare but justified kudos for finally kicking off the rollout of its own robotaxi service mid-year in Austin, after multiple yearly iterations of promises followed by delays.

Just a few days ago, as I write this, in fact, the company began testing without human monitors in the front seats (not that they were effective anyway, in at least one instance).

Agentic AI

In the subhead for my late-May Microsoft Build 2025 conference coverage, I sarcastically noted:

What is “agentic AI”? This engineer says: “I dunno, either.”

Snark aside, I truthfully already had at least some idea of what the “agentic web”, noted in the body text of that same writeup as an example of the trendy lingo that our industry is prone to exuberantly (albeit only impermanently) spew, meant. And I’ve certainly learned much more about it in the intervening months. Here’s what Wikipedia says about AI agents in its topic intro:

In the context of generative artificial intelligence, AI agents (also referred to as compound AI systems or agentic AI) are a class of intelligent agents distinguished by their ability to operate autonomously in complex environments. Agentic AI tools prioritize decision-making over content creation and do not require human prompts or continuous oversight.

And what about the aforementioned broader category of intelligent agents, of which AI agents are a subset? Glad you asked:

In artificial intelligence, an intelligent agent is an entity that perceives its environment, takes actions autonomously to achieve goals, and may improve its performance through machine learning or by acquiring knowledge. AI textbooks define artificial intelligence as the “study and design of intelligent agents,” emphasizing that goal-directed behavior is central to intelligence. A specialized subset of intelligent agents, agentic AI (also known as an AI agent or simply agent), expands this concept by proactively pursuing goals, making decisions, and taking actions over extended periods.

A recent post on Google’s Cloud Blog included, I thought, I concise summary of the aspiration:

“Agentic workflows” represent the next logical step in AI, where models don’t just respond to a single prompt but execute complex, multi-step tasks. An AI agent might be asked to “plan a trip to Paris,” requiring it to perform dozens of interconnected operations: browsing for flights, checking hotel availability, comparing reviews, and mapping locations. Each of these steps is an inference operation, creating a cascade of requests that must be orchestrated across different systems.

Key to the “interconnected operations” that are “orchestrated across different systems” is MCP, the open-source Model Context Protocol, which I highlighted in my late-May coverage. Originally created by two developers at Anthropic and subsequently announced by the company in late 2024, it’s now regularly referred to as “USB-C for AI” and has been broadly embraced and adopted by numerous organizations and their technologies and products.

Long-term trend aside, my decision to include agentic AI in my year-end list was notably influenced by the fact that agents (specifically) and AI chatbots (more generally) are already being widely implemented by developers as well as, notably, adopted by the masses. OpenAI recently added an AI holiday shopping research feature to its ChatGPT chatbot, for example, hot on the heels of competitor Google’s own encouragement to “Let AI do the hard parts of your holiday shopping”. And what of Amazon’s own Rufus AI service? Here’s TechCrunch’s beginning-of-December take on Amazon’s just-announced results:

On Black Friday, Amazon sessions that resulted in a sale were up 100% in the U.S. when the AI chatbot Rufus was used. They only increased by 20% when Rufus wasn’t used. 

Trust a hallucination- and bias-prone deep learning model to pick out presents for myself and others? Not me. But I’m guessing that both to some degree now, and increasingly in the future, I’ll be in the minority.

Humanoid Robots

By now, I’m sure that many of you have already auditioned at least one (and if you’re like me, countless examples) of the entertaining and awe-inspiring videos published by Boston Dynamics over the years (and by the way, if you’ve ever wondered why the company was subsequently acquired by Hyundai, this excellent recent IEEE Spectrum coverage of the company’s increasingly robotics-dominated vehicle manufacturing plant in Georgia is a highly recommended read). While early showcased examples such as Spot were, as its name reflects, reminiscent of dogs and other animals (assuming they had structural relevance to anything at all, that is…hold that thought), the company’s newer Atlas, along with examples from a growing list of other companies, is distinctly humanoid-reminiscent. Quoting from Wikipedia:

A humanoid robot is a robot resembling the human body in shape. The design may be for functional purposes, such as interacting with human tools and environments and working alongside humans, for experimental purposes, such as the study of bipedal locomotion, or for other purposes. In general, humanoid robots have a torso, a head, two arms, and two legs, though some humanoid robots may replicate only part of the body. Androids are humanoid robots built to more closely resemble the human physique. (The term Gynoid is sometimes used for those that resemble women.)

As Wikipedia notes, part of the motivation for this trend is the fact that the modern world has been constructed with the human body in mind, and it’s therefore more straightforward from a robotics-inclusion standpoint to create automotons that mimic their human creators (and forebears?) than to adapt the environment to more optimally suit other robot form factors. Plus, I’m sure that at least some developers are rationalizing that robots that resemble humans are more likely to be accepted alongside humans, both in the workplace and in the home.

Still, I wonder how much sub-optimization of the overall robotic implementation potential is occurring in pursuit of this seeming single-minded human mimicking aspiration. I wonder, too, how much influence early robot examples in entertainment, such as Rosie (or Rosey) from The Jetsons or Gort from The Day the Earth Stood Still, have had in shaping the early thinking of children destined to be engineers when they grew up. And from a practical financial standpoint, given the large number of humanoid robot examples coming from China alone, I can’t help but wonder just how many “androids” (the robot, not the operating system) the world really needs, and how massive the looming corporate weeding-out may be as a result.

Unforeseen acquisitions

This last one might not have been seismically impactful from a broad industry standpoint…or then again, it may end up being so, both for Qualcomm and its competitors. Regardless, I’m including it because it personally rocked me back on my heels when I heard the news. In early October, Qualcomm announced its intention to acquire Arduino. For those of you not already familiar with Arduino, here’s Wikipedia’s intro:

Arduino is an Italian open-source hardware and software company…that designs and manufactures single-board microcontrollers and microcontroller kits for building digital devices. Its hardware products are licensed under a CC BY-SA license, while the software is licensed under the GNU Lesser General Public License (LGPL) or the GNU General Public License (GPL), permitting the manufacture of Arduino boards and software distribution by anyone.

First fruits of the merger are the UNO Q, a “next-generation single board computer featuring a “dual brain” architecture—a Linux Debian-capable microprocessor and a real-time microcontroller—to bridge high-performance computing with real-time control” and “powered by the Qualcomm Dragonwing QRB2210 processor running a full Linux environment”, and the Arduino App Lab, an “integrated development environment built to unify the Arduino development journey across Real-time OS, Linux, Python and AI flows.”

So, what’s the background to my surprise? This excerpt from IEEE Spectrum’s as-usual thorough coverage sums it up nicely: “Even so, the acquisition seems odd at first glance. Qualcomm sells expensive, high-performance SoC designs meant for flagship smartphones and PCs. Arduino sells microcontroller boards that often cost less than a large cheese pizza.”

Not to mention that Qualcomm’s historical customer base is comparatively small in number, large in per-customer volume, and rapid in each customer’s generational-uptake silicon churn, the exact opposite of Arduino’s typical customer profile (or that of Raspberry Pi, for that matter, who’s undoubtedly also “curious” about the acquisition and its outcome).

Auld Lang Syne (again)

I’m writing this in late December 2025. You’ll presumably be reading it sometime in January 2026, given that I’m targeting New Year’s Day publication for it. I’ll split the difference and, as I did last year, wrap up by first wishing you all a Happy New Year!

As usual, I originally planned to cover a number of additional topics in this piece. But (also) as usual, I ended up with more things that I wanted to write about than I had a reasonable wordcount budget to do so. Having just passed through 2,700 words, I’m going to restrain myself and wrap up, saving the additional topics (as well as updates on the ones I’ve explored here) for dedicated blog posts to come in the coming year(s). Let me know your thoughts on my top-topic selections, as well as what your list would have looked like, in the comments!

—Brian Dipert is the Principal at Sierra Media and a former technical editor at EDN Magazine, where he still regularly contributes as a freelancer.

Related Content

• 2024: A year’s worth of interconnected themes galore
• 2023: Is it just me, or was this year especially crazy?
• A tech look back at 2022: We can’t go back (and why would we want to?)
• A 2021 technology retrospective: Strange days indeed
• 10 consumer technology breakthroughs from 2019
• 2026 Look Ahead

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