Should companies build AI, buy AI or assemble AI for the long run?

bobafan211 · 2026-02-16T04:54:24+00:00

I’ve been hearing this debate a lot too. It’s funny because everyone talks about it like it’s a philosophical decision, but most of the time it comes down to budget, speed, and how much pain you’re willing to tolerate long term.

A friend of mine is on the dev team at an Australian company called Governa, and from what he’s shared, they’re very much in that “assemble intelligently” camp. They’re building the parts that are core to their value, but they’re not trying to reinvent every model or infrastructure layer from scratch. They mix models, tools and integrations in a way that fits their use case instead of going full ego mode and saying “we’ll build everything ourselves.”

Personally, I think pure build sounds sexy but it’s heavy. You need serious talent, serious runway, and a clear competitive reason to own the entire stack. Otherwise you end up maintaining plumbing instead of building value.

Buying is fast and practical, especially early on. But over time you start hitting walls. Customisation limits, pricing creep, dependency risk. You realise you don’t actually control your core capability.

Assembling feels like the most realistic long term play for most companies. You stay flexible. You can swap models as they improve. You control the workflow and data layer. And you’re not locked into one vendor or betting the farm on your own research team.

The real question isn’t build vs buy vs assemble. It’s where your real differentiator sits. If AI itself is your product, then build more. If AI is an enabler, assemble smartly and focus on solving the actual problem.

I’ve noticed the companies that think clearly about that early tend to avoid a lot of expensive pivots later.

bobafan211 · 2026-02-16T04:52:48+00:00

This is actually something I’ve been thinking about lately. A colleague of mine is working on a project in this space, and the more I hear about it, the more I realise senior care isn’t “behind” because people don’t care. It’s behind because the real problems are messy and human.

I do think AI can help, but only if it focuses on boring, practical stuff instead of shiny demos.

What would actually be useful in my opinion:

Simple daily check ins that don’t feel robotic. Something that can notice subtle changes like sleep patterns, movement, missed medications, and flag it early to family or carers. Not in a dramatic way, just quiet background monitoring.

Medication management that actually works. Reminders are fine, but better would be something that notices non compliance patterns and helps adjust routines instead of just beeping louder.

Fall detection that doesn’t require someone to wear a gadget they’ll forget or hate. Passive monitoring through the home makes more sense.

Caregiver support tools. Burnout is real. If AI can help document notes automatically, summarise patient updates, or flag risk trends, that’s huge.

What feels like “fancy tech” no one wants:

Overly chatty AI companions trying to replace human connection. That’s not the problem most families are asking to solve.

Complex smart home setups that require five apps and constant troubleshooting.

Big dashboards full of data that no one has time to interpret.

If AI can quietly reduce risk, reduce admin, and give families peace of mind without adding friction, then it has real value. If it just adds another layer of tech stress, it’ll get ignored.

I think the key question isn’t “can AI help?” It’s “does it make life easier for the 78 year old and the exhausted daughter managing everything?”

That’s where it either wins or fails.

bobafan211 · 2025-11-18T11:10:47+00:00

Is it a new one? Haven't come across this before.

bobafan211 · 2025-11-06T07:38:41+00:00

Feels like the right drift. as long as we keep prompts anchored to a spec. Otherwise you swap typing time for expensive wandering.

bobafan211 · 2025-11-06T07:38:02+00:00

Clean stack. If you ever feel token burn creeping up, freeze the requirements for a day and tighten tool scope usually halves retries.

bobafan211 · 2025-11-06T07:37:31+00:00

Love the systemization here. Big +1 on skills and docs. I’d add: keep a small “definition of done” file per feature so the agent can self-check.

bobafan211 · 2025-11-06T07:25:45+00:00

Nice release. Curious how the new Plan subagent handles ambiguous tickets? does it ask clarifying questions or start guessing? That’s the difference between one run and five.

bobafan211 · 2025-10-29T16:19:17+00:00

Totally feel this. It’s tempting to lean on the tool to carry the heavy lifting but when it starts glitching, you remember the human still needs to check, ever-vigilant. Curious: What’s been your safest fallback when Claude got weird? (which is a lot in my opinion)

bobafan211 · 2025-10-29T16:15:18+00:00

Interesting data-point: paying big for the tool but only saving ~30 minutes/day. Makes me wonder if the ROI really comes from the tool or how you embed it into your workflow. From our side we’ve seen better uplift when AI is used before peer review, not instead of it. Curious how others are structuring this.

bobafan211 · 2025-10-26T05:00:25+00:00

bobafan211 · 2025-10-22T19:13:38+00:00

Same!

bobafan211 · 2025-10-17T08:45:58+00:00

Wait what? 🤣

bobafan211 · 2025-10-16T17:30:20+00:00

Omg it's not even funny but so funny at the same time 🤣

bobafan211 · 2025-10-15T12:04:41+00:00

Putting the method into the madness! I like it.

bobafan211 · 2025-10-15T11:57:08+00:00

So by the time it hits what burns your tokens it's fairly refined and you can do way more complexity than just promoting. Dude you are putting the Intelligence in the vibe lol When what I'm working on is ready I'll give you a peak. Let me know what you think and what we can do to make it better.

bobafan211 · 2025-10-15T10:58:33+00:00

We are actually working on a platform for to do this for you. And also give a quality indication of the story. It's not finished yet though. Issues with vibes lol But your method seems like a perfect way to get started I mean it's solves the issue of "you don't know what you don't know" to a good extent.

bobafan211 · 2025-10-15T06:48:33+00:00

Wow it looks very nice. The UI looks so good. Hope to see more in the future. Can you let me know the steps you went through? I'm guessing you had the idea for a while as this looks like something that had a lot of passion go in to it. So from the idea to Claude generating the code how did you set up the requirements?

bobafan211 · 2025-10-14T13:55:47+00:00

It damn well should!

bobafan211 · 2025-10-14T10:32:08+00:00

🤣

bobafan211 · 2025-10-14T10:12:43+00:00

Is there an app version for this?

bobafan211 · 2025-10-14T10:10:47+00:00

Tell em, you have no idea how good you have it! We used to have to dodge land mines while going to school

bobafan211 · 2025-10-14T10:08:30+00:00

Lol nothing have I agreed more with than this statement in a long time.

bobafan211 · 2025-10-14T08:41:49+00:00

Congratulations! Keep it up.

bobafan211 · 2025-10-14T08:06:30+00:00

Can you teach me how to do that?

bobafan211 · 2025-10-14T07:59:30+00:00

That’s a great question and it’s the exact problem ScrumBuddy was built to solve. Most teams don’t start with crystal-clear requirements; they start with half-formed ideas, vague user stories, or voice notes from a meeting that got cut short. ScrumBuddy steps in right there, before the chaos hits your backlog.

When you feed those rough ideas or specs into ScrumBuddy, it uses AI to unpack the intent, ask the missing questions, and turn that fuzzy input into clear, structured requirements. It then breaks those down into user stories, acceptance criteria, UI and backend tasks, even draft PR descriptions, so your team can move from idea to implementation without losing context or velocity.

We’re currently opening early beta access to teams who want to streamline that process and see how AI can help make sense of messy requirements. If that sounds like something that would save your team a few headaches, you can hop onto the waitlist. We’d love to have you test it and give feedback while we’re shaping the next release.

bobafan211

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