Fastest Way to AI Adoption — Straight Talk

 

What is the fastest way to meet your board’s AI goals? What is the fastest way to become AI Engineer? How are the two related?

I am a team competence player-coach building disruptive teams for decades — let me give you a shortcut.

First, and most importantly, I am not talking about buying ChatGPT for your organisation. Nor any other pointless tool trope. I am talking about real AI producing measurable business value, both for your company and yourself. Take a look at The current State of Things and AI Adoption Phases to get a better sense of my scope here.

It’s all very simple. Success boils down to a way of thinking and a little technical magic. I had already described the winning investment matrix: 70/20/10. And it really is "little" —  paradoxical considering the rate of failures. For DX, teams needed 2-3 weeks before producing results. With AI? One day or a weekend. Here is how it’s done:

1. People and Processes — 80%;

2. Technical Competence — 20%.

And this is also exactly the formula for an individual contributor to enter the AI Adoption field. Later I will elaborate on this too.

People and Processes

We already know why AI adoption fails so much, since July 2023: American AI Integration Trap — most of the businesses did not complete Digital Transformation (DX), and just swept things under the rug. Ironically, from the DX we only really need one thing — the last one — business domain modeling skill sets and abilities. Your generative AI is just a tool. A tool that can, if used competently, produce a business capability. And it is that business capability that creates "money in the bank" not the means it’s begotten with. Yet the means are necessary — and the means are people, not gadgets. This is why most effort is on "People and Processes," not gadgets.

Enabling People

We start with a "self-empowered" gang of folks representing business experts and domain software engineers in a single business context. Any less and it won’t work. And a coach, such as myself, leaves — we’re also directly interested in the final outcome. Here we must understand that people:

1. Cannot be empowered by someone else;

2. Cannot be told what to do.

I am not going to elaborate on the above facts — that is a different topic. And now that we have our domain team I really must do very little to get things going:

1. Check team alignment;

2. Break team biases;

3. Enable with the right magic.

Team alignment: I must make sure every teammate that contributes, and hopefully that’s everyone, clearly understands how the business outcome maps to their personal success. What is the business outcome — shared understanding on valuable domain behavior, not a tool or a library. What is the team’s success — measurable return on investment for the business from the team. What is personal success — how does the company and department brand map to individual’s personal brand. This is quickly done with some "pep talk" and then "continued dialectic" — not my favorite part, but after decades of doing this for many teams I no longer feel annoyed or bored through this part — I learned to make this step fun for everyone as well.

Discover and Break Team Bias: remove psychological impediments people feel breaking into different work style and kind. And this part is always fun. The secret — make it the entire team’s journey. For business experts this would typically be related to the experience bias (look up SEEDS Model, I have a lot of luck with it). If I don’t help them find and break assumptions there, then the resistance will cause the new tools applied in old ways. For engineers this would typically be the similarity bias problem. If unchecked we get "Impostor Syndrome" roadblocks as well as catalyst for experience bias related friction. For example, AI works opposite to developer written code: with AI we want patterns automatically discovered instead of explicitly enforced by the coder. Yet such a small thing can cause comprehension issues and resistance to learning.

Enable with the right Methods and Tools: provide the path of least resistance to the actual payoff. There are better and worse ways to do everything. Most teams won’t be able to guide themselves yet because the job is new to them. It is the primary accountability of the coach to understand the best path for his team. And to effectively nudge the team in the right direction. Necessary methods and tools exist in all the major platform providers today: GCP, AWS, etc…​ Yet with that, the ergonomics and learning curves are nonetheless vastly different. That is because platform vendors bet on vastly different differentiators, such as: cost, developer ergonomics and training, or legacy markets integrations like the Office software. And some align better to what the team already experienced in the past. There is another potentially nasty pitfall here I’ll mention later.

All of the above is to simply build up confidence and motivation for the team to attempt the necessary challenge before them.

Technical Nightmare

Now this part is only 20% of the effort. And here I will let you on a little secret: it’s here the project is most likely to fail. Not because there is a lot to fathom or do. But because the actual technical experts we need to get through this challenge are scarce. Many can easily learn organisational development and succeed in aligning the team — the previous part. But to align the team through a technical delivery one needs someone like myself — a bearded old hacker who just codes all the time, daily through decades. The problem stems from the fact that software engineering is one of the most difficult trades, akin to medicine or law but deprecating even faster. It comes naturally to less than 10% of the workforce. And even then must be diligently maintained because even a single hiatus can be the last one. Steering team wrong kills the chances. And since most coaches we profiled don’t actually code — we get what we have today.

And that’s unfortunate. Because in the end the technical increment is very small for any already performing team. All I have to do to succeed quickly is to stop engineers thinking about AI and ANNs and bring their attention to few systems engineering topics — and we’re in prod!

Technical Enablement:

Secret number 2: platforms are important! In all American companies today there is sycophantic following to different cloud providers. "We’re Microsoft and Azure all the way, and Microsoft owns OpenAI." Hmmm., but neither has anything to do with what you need for business AI success! The same is true about stacks: "We’re a Java shop not Kotlin" — hmmm…​ by saying that you are actually telling me that you are competent in neither! This is also a part of biases I’d spoke of earlier, except a little more global.

So we must take a closer look at the Methods and Tools again. It isn’t just bias-management and domain-modeling. It’s also design and implementation. And in the latter part all things are not created equal. Long time ago I wrote how Google will corner AI Integration market by befriending the developer. 2023: Why Google Beat OpenAI with Technical Teams. And Google just delivered the last nail in that coffin with Gemini 3 (YouTube @Fireship: Did Google just kill OpenAI?) and even better Developer Courtship and integration. Simply, for midsize and small companies there is little contest. Because it’s not your Claude or Gpt5 that you will be using in your product.

Thus the biggest obstacles here are A) lack of coach technical competence; and then also B) institutional platform bias. I had a VP tell me once "But Netflix is all on AWS!" I didn’t argue, of course. Though his statement was NOT TRUE. Netflix does use AWS at the moment as their primary and most cost-effective production. But they’re not vendor-locked. Not only that, everything in AWS also exists elsewhere for Netflix. Not even all of Netflix is on AWS in production today. Yet his bias also poisoned his dev teams — boots on the ground. His developers' minds were blown when I showed then how easy it is to go hybrid.

Keep that in mind, especially for the Individual Developer Career part of our discussion.

Big Companies — Big Failures:

We can’t complete this topic without explaining what the big companies do today. And it is replacing teams. Instead of investing into existing domain teams many execs convinced themselves that "greenfield is better." Or, in other words, "new dog;" not the "old dog - new tricks." This is possible because of the money conglomerates throw into AI these days. And the following picture emerges:

An incumbent team is presented with a challenge: "Augment your business with Generative AI." Response: "But we’re Spring Boot developers, not AI scientists." Execs: "Okay, thank you."

And the new side-by-side "AI Team" is created. The incumbent Spring-Boot-Only team has NO IDEA that the New Team is also using Spring Boot to build their DDD Aggregates and MCP Servers. Hmmm…​. See where I am going with this?

This should make you think!

And yes, it doesn’t work well — the new team has no domain knowledge and the old team doesn’t want to learn anything new. In addition, both are sabotaging each-other. They’re fighting, not collaborating. Big business runs AI adoption ridiculously thick. But at least they’re making something new.

All Others — Paralysis by Analysis.

In another article my 16-y-o son explained how medium companies are uniquely positioned to fail. And how small companies have all they need but are afraid to try. Also the internet tells me I’m the first one to predict this state of things — I’m embarrassed for my America. Having quickly helped a few companies out I see two mutually exacerbating problems:

1. There is top-down failure — and there is no valid reason for it.

2. There is bottom-up failure — and there is no reason for it either.

Or, if there are valid reasons — then, I don’t see or understand them. Because any such possible reasons are not technical or organisational. Then they must be psychological — and that’s "Room 2," for a shrink, not a hacker.

Regardless — I know what to do! Shore up both pathways.

Executives' Path:

Executives must do "one thang and one thang only": enable your existing domain teams. Forget the fads! This is NOT about AI. Not one bit. This is about good old "systems engineering." Modern name — Domain Modeling.

For Medium Companies: Snuff the urgency and systematically grow your Community of Practice. You will need that for the next four phases, see AI Adoption Phases.

For the Small Companies: Stop cowering and objectively see where you can get help from generative tools. Start like everyone else — get Claude Max or better. Incorporate that in everyday business. When that gives your people some ideas — talk to us, i.e., other small companies that explicitly specialize in competence. You won’t get gouged and you might get enlightened. Most importantly, when it comes to your developers — help them do what’s in the next section.

Individuals' Path:

Now, this is the most important message I get to deliver here. People, engineers, architects, modelers — your toolbox has changed! Get on with the times.

The only question that remains — what is the best, fastest way to upskill oneself. I have evaluated ALL offerings out there. Not only because I need to coach teams and upskilling portals are my lifeline, but also because I like variety of sources, so I also checked all of the universities, online learning platforms, and private training institutions around RTP and online.

The path with lowest friction for new teams: Google’s developer ecosystem.

skills.google: Brand new platform launched in 2025, building on years of experience catering to developers in AI and Cloud. The service is so comprehensive that at first I was conflicted - upskilling software teams is my bread and butter. And this single service compiled everything I’d present to teams into one accessible portal. I’ve used it with customers and it works. Fortunately, I’m still needed. Because "Practical experience is knowing that which can no longer be corrected" - in other words, what not to do. But for individual career growth or team modernization, this is your primary resource.

Vertex AI: A one-stop shop for learning and working with production-grade AI. Running on Google Cloud with Vertex Generative AI Studio, you touch real infrastructure without building massive labs. Most importantly, ai.google.dev is your sandbox to actual Vertex AI - here’s the explanation. (See blogs "Google Skills" and training and certification).

Sample this AI class…​

Most importantly, developers.google.com - Google Developer Program: where it all begins and grows. This community is why I no longer maintain my own private portal. Once we were considered uniquely effective, yet today I send my mentees here.

What about other platforms? Yes, absolutely. They work well. I’m platform-agnostic by nature and no fan of vendor lock-in. But Google made a strategic bet on developer ergonomics while others bet on enterprise sales. For teams learning AI integration - start where the friction is lowest. Expand to multi-cloud as your production needs grow.

Full Disclosure:

I am not a fan of Google. Or anyone for that matter. Except maybe JetBrains, a little. Ever since Google founders left I have more to dislike than like. I live my life to die an honest man. And I don’t respect fishy business from others either. So consider my bias in my final advice.

Right now I have found no better way to launch a team quickly into AI stratosphere. Use this springboard to put yourself and your company in orbit. But don’t lock-in! Expand your reach instead. And the Google Developer community has been good to me. I found them very useful in launching startups for people, transforming Corporate America, and building my own products.

But know that yours truly, rdd13r, doesn’t trust Google. I fully expect them to start turning screws on devs and business as soon as they feel that their market is cornered. And that might be around the corner with Gemini 3 release. I know this music. I lived it before. So benefit to the max while you can. And remember — there is no magic bullet. All the magic is in you head. Use it!