u/Early-Matter-8123

Problem: Most SME businesses don’t have a CFO.

They have QBO, Xero or Sage and maybe an accountant they speak with a few times a year, and a stack of reports that technically answer everything… but don’t actually answer the questions they’re trying to ask.

Things like:

• Why is cash tighter this month when sales were up?
• Which expenses are quietly growing faster than revenue?
• Which customers are actually the most profitable?
• What changed since last month that deserves my attention?
• If I only had 15 minutes to review my finances, where should I start?

The information exists. Connecting the dots is usually the hard part.

I’m working on a simple dashboard that tries to explain the story behind the numbers instead of simply displaying financial statements. Before I spend more time building it, I’d rather hear from actual business owners than make assumptions.

If you could make your accounting software answer one question automatically every month, what would it be?

For anyone interested in giving brutally honest feedback, I’ve put together a very early prototype. I’m not looking for praise, users, waitlist. I’d genuinely like to know what’s confusing, what’s missing, and what would actually make it useful.

Building and hosting websites is not really our space. But it is a quick turn opp for some of our small clients that I still want to help.

Right now I'm considering Vercel as my go to.

Would you go with the Pro account and manage client domains and backend stuff? (not that I really want to manage that end either - again its a quick turn $$)

or

Just build - transfer code and put Vercel in client name? But then im thinking im loosing future opportunities with these clients.

thoughts - what works for other small dev teams right now?

Agents and Automation seem to be the new words of 2026. So I'm curious what you're focused on when you are developing software and AI Native applications?

Most frontier AI models are multi-modal out of the box.

Gemma 4 recently dropped and it natively multi-model so it doesn't use transcoders. Its Free and the 12B model is said to run on a 16GM of memory suitable for most current laptops.

I've been enjoying tooling around with the openAI realtime 2 api for voice. I'm very impressed with it. Though I'm still not sure there is a deeper commercialized use case for it as just a pure chat feature. Especially because of its costs. But it sure is fun.

What I find pretty cool though is that you can now build some amazing websites with some very interesting applications behind the scene.

We are currently testing a very simple wave form visual for our experimental website.

Not visible content. Just a microphone and the visual wave form feedback that changes patterns and colours depending on what the model is actually doing - Web_search, Tool_Call, Responding...

Site visitors simply ask questions and interact with the voice model. We use a GraphRag for strict content control. the model will render a content modal with the dynamic content on demand instead of user scrolling pages or navigating pages.

I've been thinking about this lately because I feel like people use the term "prompt engineering" to describe two very different things.

On one end, you have what most people are familiar with:

A person opens ChatGPT, Claude, Gemini, etc., and writes a carefully structured prompt.

They define a role, provide context, establish goals, set constraints, maybe include examples, and iterate until they get the output they want.

Most people seem to call this prompt engineering.

But on the other end, when I'm building AI systems, prompt engineering looks completely different.

The prompt isn't really a prompt anymore. It's much more of a dynamic pipeline.

Variables are injected from databases, user input, APIs, previous conversations, tools, memory systems, retrieval systems, business rules, and workflow state.

Decision trees determine which instructions are included and which are excluded.

Prompts become assembled in real time based on context.

In some cases, the "prompt" is really just an orchestration layer made up of dozens of smaller prompts, conditionals, guardrails, routing decisions, and context windows.

At that point, are we still talking about prompt engineering?

Or are we actually talking about system design, context engineering, workflow engineering, orchestration, or something else entirely?

Personally, I see prompt engineering as a spectrum:

Level 1: Writing a better prompt.

Level 2: Designing reusable prompt templates.

Level 3: Building dynamic prompts with variables and context injection.

Level 4: Engineering entire prompt-driven systems with routing, memory, tools, retrieval, and decision logic.

Curious where others draw the line.

When you hear "prompt engineering," are you thinking about writing prompts, building workflows, designing agent systems, or all of the above?

Has the term become too broad to be useful?

I see a lot of "I'll build you a website" on reddit and I suppose this is no different except!

We are located in North America (Canada to be exact)

Our team has 2 CS graduates from the University of Western Ontario (located in London Ont), a Project Manager with over 5 yrs experience, 2 front end designers and 1 Sr. Dev.

Here is what IntelliSync offers as our base website:

- Website = unlimited pages (if you really need that).
- Blog - optional AI setup to refine your blog (not straight up write it...unless thats what you want) + Cron job for auto-publish. Built in RSS (you can set up your business LinkedIn page to automatically pull your blog once per day for expanded reach.
- AI Chat integration with your full website content as context. (We can use any model but our pref is OpenAI Responses API GPT 5 family models).
-Admin login for Dashboard:
- Custom Web traffic analytics (we use Re-charts a lot)
- All data & Meta data is structured and optimized for AI search/Citation readiness. That includes the following LLM.txt, crawlers.txt, JSON-LD, robots.txt, HumanQuery.json for FAQ & AI discoverability.
- DataBase - (we really like Convex for this)

Stack:

Next.js (latest stable. we only experiment on our own site)
Shad/cn
Tailwind
ReCharts
Font family of your choice (we tend to default to google fonts)
Icon Lib of your choice (we tend to default to Lucide-React)
Framer Motion - for animation and interactivity
Re-hype - Custom markdown rendering
Zod - for validation schema
Convex - Database
OpenAI Responses API w/ GPT 5 model family

You can host on Vercel Free (if you're into some light lifting we help set you up)

Convex DB you can also run Free (you we can help you with that too if you need)

Can you believe we can offer this for <$3,000 CDN.
If you're a Solo-entrepreneur you get all of this for $1,500 and no funny stuff. We don't believe in vendor lock-in.

If you don't like our services it's your code, you can deliver to any web dev and let them easily take over anytime you like.

We can show examples, demos and client testimonial

At Google I/O,

Google showed where Search is heading next:

AI-generated answers. Intelligent search agents. Dynamic results built in real time.

For marketers, that changes the game.

Being cited by AI systems is becoming just as important as ranking in search results.

And while AI discoverability currently overlaps with traditional SEO, the signals are not the same.

The top factors were not backlinks or keyword stuffing.

They were:

• Freshness and recency (91%)
• Structured formatting (79%)
• Clear, direct language (43%)

We’ve been messing around with the new OpenAI realtime voice + translation APIs over the last little while and I keep coming back to the same thought… I don’t think people fully get where this is going yet.

We wired it into our own website as a test. Nothing fancy. Just wanted to see what actually breaks when you let people talk to a site instead of click through it.

At first I thought it would just feel like a slightly better chatbot. It doesn’t.

Once I hooked it into tools and gave it the ability to actually do things (we’re using the Agents SDK + Playwright for web browsing and control by a sub-agent), the whole interaction changed. I can literally just talk to the site like I would talk to a person and it can move around, pull info, trigger actions, and respond in context.

I wanted a layer that that could navigate and respond by just talking.

I know that sounds obvious, but it’s not how websites are designed at all. Ours certainly was not.

A few things that have been interesting (and honestly a bit brutal) is how quickly this exposed weak structure. Our content was vague... so if your metadata sucks, if your pages are bloated or unclear… voice didn't let us hide behind a pretty UI design. The model just struggles or gives bad answers immediately. There’s no masking it with a nice UI.

Latency has improved way more than I expected with the new voice model API. Before, when someone was talking, even small delays felt awkward. The new Realtime 2API tolerates those pauses wonderfully.

We also started playing with the realtime translation side and that also feels like a bigger deal than it’s getting credit for. Not in a “multi-language support” way, more like… you just speak however you want and the system handles it. No toggles, no switching context. It’s subtle but it completely changes the feel. Our website is language agnostic. (13 supported languages using the Realtime 2 API)

The bigger shift for me seems to be changing the way I want to think about websites and interactions.

People don’t think in menus. They don’t think in pages. They don’t think in navigation.

They think by intent and the second I added voice, i was forced to deal with that reality whether our website system was not ready. Great learning lesson.

My Takeaway so far:

Right now most of what I’m hearing and reading, people/businesses treats voice like a feature. Like and Add-on. Cool. Nice to have. Unsure if its practical.

I don’t think that’s where this ends.

I think this starts pushing toward systems you can just interact with directly. Personal assistants that actually execute. Internal tools you can talk to. Intake flows that don’t feel like forms. Stuff like that.

Minimal website visuals. More dynamically displayed content based on interpretation of user intent. [Basically a cool wave form that animates differently depending on interaction stage] No direct site content visually.

We’re still early and there’s definitely some friction [writing a second voice prompt on top of the text prompt so there is parity between our text chat and voice chat, but I’m pretty bullish on this direction - Guardrails, Rate-limits, Prompt Injection...].

Curious if anyone else here is actually building with it yet and what you’re running into. Feels like we’re right on the edge between “cool demo” and “this changes how software works,” and I’m not sure which way most people are approaching it yet.

This is the core tension I think people are feeling right now with AI.

After posting and commenting nn various SM platforms the signals have been very mixed. (no surprise there) It's equally both fascinating and frustrating at the same time.

So if you read this, I'm curious to hear your thoughts about the AI divide.

The technology itself is not really the whole story anymore. The deeper issue is that AI has started disrupting the social signals people use to measure credibility, effort, expertise, and legitimacy. Across platforms like Reddit, LinkedIn, X, and TikTok, AI use is increasingly treated less like a workflow decision and more like character evidence. “AI slop,” “prompt monkey,” “fake creator”… these aren’t technical criticisms. They’re status attacks. They reflect a growing fear that visible human effort is losing value in a world where polished output can be generated instantly.

What makes this complicated is that the backlash is not entirely irrational. People are being flooded with synthetic content, automated spam, shallow engagement farming, and low-effort AI-generated noise at industrial scale. Platforms themselves are now openly responding to “inauthentic content” and AI saturation. But somewhere along the way, skepticism started mutating into moral theatre. Instead of evaluating work on quality, verification, transparency, or usefulness, people increasingly judge whether the creator feels “human enough” to deserve credibility in the first place.

That’s why this debate feels so emotionally charged. AI compresses the distance between novice and expert in ways that make people deeply uncomfortable. When someone can produce something polished quickly, others instinctively question whether the skill, labor, or expertise behind it was “earned.” In response, creators now perform proof-of-humanity rituals: showing drafts, edits, handwritten notes, behind-the-scenes process clips, and visible struggle. The artifact itself no longer feels like enough proof of value. People want to see the scars.

The real divide probably isn’t “pro-AI vs anti-AI.” It’s whether we can maintain standards in an environment where authenticity signals are becoming unstable. AI didn’t invent status anxiety, fraud, performance culture, or social posturing. It just accelerated all of them at machine speed. And now the internet is trying to decide whether AI is a tool, a shortcut, a threat, or a social stain.

Mostly by yelling at each other in comment sections. Civilization remains majestic.  

I think there’s a growing opportunity for people who can simply help businesses make sense of AI.

Not “AI experts.” Not futuristic consultants.
Not people trying to turn every business into a Silicon Valley startup.

Just people who can translate all this noise into something practical.

a lot of small business owners are overwhelmed right now and most businesses don’t need someone explaining neural networks or agentic infrastructure to them.

They need someone who can walk into their business, understand how work actually flows, identify friction, simplify a few things, and help them apply AI in ways that are actually useful.

Hi everyone,

We are building an early-stage platform/community for women founders and women in leadership, and we’re currently in the founding member onboarding stage.

We started with a simple question:

What would make a women-led professional community actually worth returning to?

So far, we have 22 accepted founding members across technology, healthcare, finance, nonprofit, real estate, marketing, education, legal, media, hospitality, consulting, and entrepreneurship.

A few early signals stood out:

- 50% of founding members have logged activity

- 40.9% have participated beyond just logging in

- 36.4% have posted comments

- Our first direction-setting poll had 40.9% participation

- The top-voted priority was: Events, Working Sessions + Mentorship

- The second strongest priority was: Focused Discussion Rooms + Peer Circles

The interesting part is that the responses are not pointing toward “another networking group.”

The pattern we’re seeing is that women want:

- deeper conversation

- practical support

- mentorship

- peer accountability

- honest discussion without performance pressure

- spaces that produce actual momentum, not just visibility

So our next platform goal is to test a structured Founding Circle format: small group working sessions around topics like sustainable leadership, burnout, decision-making, peer mentorship, and reducing cognitive load as founders/operators.

I’d love feedback from this group:

If you were joining a women founder platform today, what would actually make you participate consistently?

Would it be:

1. small peer circles

2. working sessions

3. mentorship matching

4. founder/operator resource sharing

5. async discussion prompts

6. AI-supported tools to reduce founder overwhelm

7. something else entirely?

We’re still early and intentionally building this with founding members, not around them.

If this sounds aligned and you’d like to be considered for the founding member group, I’m happy to share the link in the comments.

For anyone interested, here’s the founding member waitlist/application:

waitlist.intellisync.io

We’re still in the onboarding stage, so the goal right now is not scale. It’s finding women founders/operators who want to help shape the structure, culture, and first working sessions.

Hi everyone,

We are building an early-stage platform/community for women founders and women in leadership, and we’re currently in the founding member onboarding stage.

We started with a simple question:

What would make a women-led professional community actually worth returning to?

So far, we have 22 accepted founding members across technology, healthcare, finance, nonprofit, real estate, marketing, education, legal, media, hospitality, consulting, and entrepreneurship.

A few early signals stood out:

- 50% of founding members have logged activity

- 40.9% have participated beyond just logging in

- 36.4% have posted comments

- Our first direction-setting poll had 40.9% participation

- The top-voted priority was: Events, Working Sessions + Mentorship

- The second strongest priority was: Focused Discussion Rooms + Peer Circles

The interesting part is that the responses are not pointing toward “another networking group.”

The pattern we’re seeing is that women want:

- deeper conversation

- practical support

- mentorship

- peer accountability

- honest discussion without performance pressure

- spaces that produce actual momentum, not just visibility

So our next platform goal is to test a structured Founding Circle format: small group working sessions around topics like sustainable leadership, burnout, decision-making, peer mentorship, and reducing cognitive load as founders/operators.

I’d love feedback from this group:

If you were joining a women founder platform today, what would actually make you participate consistently?

Would it be:

1. small peer circles

2. working sessions

3. mentorship matching

4. founder/operator resource sharing

5. async discussion prompts

6. AI-supported tools to reduce founder overwhelm

7. something else entirely?

We’re still early and intentionally building this with founding members, not around them.

If this sounds aligned and you’d like to be considered for the founding member group, I’m happy to share the link in the comments.

For anyone interested, here’s the founding member waitlist/application:

waitlist.intellisync.io

We’re still in the onboarding stage, so the goal right now is not scale. It’s finding women founders/operators who want to help shape the structure, culture, and first working sessions.

Not by definition but by functionality?

How are you integrating AI into you websites?

For example we have automated blog generation into website.

Simple OpenAI API call on a cron job. Website owner logs in once per day edits/approves! published! Not hard to build. Done cleanly in < 1 day.

Why would we do this?

1: Use the blog as lead magnet / collecting consent emails.
2: the same ai that writes the blog creates a "personalized" email when email is captured. (routing and prompting)
3: Custom KPI tracking.

Curious what you would build onto of this or what ways you are using AI in websites/web apps?

After hearing too many horror stories, broken add-ons, slow load times, security risks and hidden costs I don't buy into Word Press as being "the" best website builder at all. forget about it as a small business intro. It just can't be worth it.

you can buy your domain name from any service provider.

you can host for free on Vercel, Netlify

spend $20.00 and use a AI for 1 month to build your website.

total cost = $50.00 + sales tax.

Hot take:

The future AI winners won’t be the companies using the “best model.”

They’ll be the companies with the best context systems.

Most organizations are still treating AI like a vending machine:
prompt in → output out

But the real leverage appears when AI understands, your workflows, your approval chains, your organizational memory, your operational rules, your internal language and your customer patterns

Raw model intelligence matters less than people think once you cross a certain threshold. Context is becoming the primary interface.

That’s why a smaller model with strong context orchestration often outperforms a giant model thrown blindly at a business problem.

Very few are orgs are building smarter environments for AI to operate inside.

That distinction is going to matter a lot over the next 3 years.

Have never used remotion before and after review some docs looks really interesting.

looking for feedback from you and your pros and cons. Im still testing ideas so i don't have a specific implementation planned.

I would use mostly for website animations.

Businesses I know earning < $100K annual revenue are not sitting around discussing “agentic frameworks.” They are trying to survive inflation, customer acquisition, software fatigue, and the soul-crushing experience of posting on Facebook Marketplace at 11:42 PM hoping somebody buys handmade candles. Civilization really did peak at “boost this post for $17.”

One of the hardest things for small businesses right now is differentiation.

Not just: “How do I get customers?”

But: “How do I stay memorable when everyone suddenly has access to AI-generated marketing, AI-generated websites, AI-generated branding, AI-generated emails, and AI-generated content?”

As if standing out wasn’t already difficult enough.

Getting your first client is hard.
Getting the next 10 is harder.
Getting your first 100 can feel nearly impossible when you are competing against louder businesses with bigger budgets and more visibility.

Marketing and distribution are brutally difficult.

Every small business eventually runs into the same question:

“Where are my customers and how do I meet them there?”

I think a lot of SMB owners are overlooking something surprisingly practical:

Small branded micro-apps.

Not giant enterprise software.
Not expensive platforms.
Not some over-engineered Silicon Valley moonshot.

Simple useful tools tied directly to your business.

Examples:

• A contractor offering a renovation budget estimator
• A cleaning company with a recurring quote calculator
• A local butcher with meal planning + order prep reminders
• A hairstylist with a style inspiration tracker + booking reminders
• A landscaper with seasonal maintenance checklists
• A fitness coach with habit trackers and progress summaries
• A bakery with custom cake planning tools
• A mechanic with maintenance reminder tracking

These are not “apps” in the traditional sense people imagine. think of them as relationship tools.

Tiny branded utilities that keep your business connected to clients between transactions.

That matters because I'm a small businesses too and I cannot compete on just price anymore.

I'm competing on attention, trust, memory, convenience and consistency.

Your niche is not a limitation. It is your moat.

Honestly, I think the businesses under $100K revenue may benefit from this shift the most because they can move fast, stay personal, and create highly specific experiences larger companies cannot replicate without ten committees and a quarterly alignment meeting nobody wanted to attend.

I’m curious:

If someone built a tiny branded micro-app for your business tomorrow, what would actually help your customers the most?

Missing context is exposing fragmented workflows, undocumented processes, disconnected systems, and years of operational ambiguity businesses quietly learned to tolerate because “that’s just how we do things.”

Now they are throwing AI into those environments.

I'll be a brutally honest here. AI is NOT the answer.

Why?

Because AI does not fix operational confusion.

If your workflows are inconsistent, you will only scale inconsistency.
If your processes are undocumented, AI inherits those gaps.
If your business lacks visibility, AI produces output without operational understanding.

It's easy to feel disappointed after the initial excitement wears off.

That is why only some companies are getting value from AI.

…and most others are getting chaos.

I’ve spent 25+ years in Canadian banking working with everyone from personal clients and solo entrepreneurs to multi-layered SMB organizations. I've helped people launch their very first business, worked with clients that grew their business and owners that eventually sold their business.

One thing became obvious over time:

The businesses that scale well usually know their operations with uncanny precision.

Not approximately.
Not “Steve handles that somehow.”
Not “the spreadsheet should be on Debbie’s desktop.”

They know exactly:

• how decisions are made
• where information lives
• what creates profitability [and why]
• where friction exists
• what processes are repeatable
• what metrics actually matter
• and where / when risk begins to compound quietly in the background

The businesses struggling with any new implementation don't have that layer nailed. What they have is an operational clarity problem.

If you think AI is going to be your magic bullet? You're wrong. It is a force multiplier. And not in a good way. We are already seeing it happen real-time.

If your workflows are fragmented, AI accelerates fragmentation.
If your processes are inconsistent, AI scales inconsistency.
If your systems lack context, AI produces contextless output at machine speed.

Which basically means we've finally invented a way to automate confusion and then act surprised when confusion arrived faster than expected.

Over my 25 yrs, successful businesses seeing real gain usually do a few things exceptionally well:

1. They know exactly what they are great at.
2. They understand where humans create the most value and where systems should support them.
3. They centralize operational knowledge instead of burying it across inboxes, sticky notes, disconnected software, and “that one employee who knows everything.”
4. They focus on decision quality, not just automation.
5. They build operational systems intentionally instead of layering new tools on top of unresolved dysfunction.

Most SMBs do not need billion-parameter moonshot technical infrastructure.

They need:

• cleaner workflows - end to end processes that don't break when the owner isn't around.
• better visibility - information is immediately available. Not in an hour, not by end of day.
• centralized knowledge - low tolerance for ambiguity.
• documented processes - No shortcuts, No one off. The same playbook every time.
• clearer intake systems - understand what good input is vs "good enough".
• consistent communication - Teams know what's going on.
• and operational systems that reduce ambiguity - Centralized knowledge with no room for misinterpretation.

That is where a meaningful AI adoption layer actually starts.

Not with prompts. Not with promises.
Not with hype. Not with demos.
And most definitely not with replacing people.

With clarity.

One of the strangest things I see happening in business right now.

Some companies are spending thousands on AI tools while their internal processes are still held together by PDFs, tribal knowledge, sticky notes, “ask Karen” and the real-really final spreadsheets named FINAL_v2_REAL.xlsx.

Then they wonder why they hear horror stories that AI outputs feel unreliable.

After the last 5 years I've learned that AI reflects operational maturity. Because if your systems are fragmented, your AI layer inherits fragmentation.

If your a SMB owner, solo-entrepreneur then implementation matters more than hype.

Small businesses don’t need Frontier AI models or 47 copilots. What they really need are structured workflows, standardized intake, searchable knowledge and a way to measure improvements and goals.

AI can automate admin task and routine process, sure. But the real advantage is creating Structure in your thinking.

I keep seeing SaaS pop-ups telling small businesses to “use AI.” Almost nobody explains to them what that actually means operationally. It's still some blackbox mystery.

So businesses end up with random ChatGPT prompts wrapped in some user interface, bad SaaS subscriptions, employees using shadow AI tools, zero governance, inconsistent outputs and no measurable ROI. I can understand the frustration and reluctance.

The small business we work with quickly discover they do not need some billion-parameter moonshot infrastructure or some 200 layer Agentic platform.

What they usually need, better intake systems/client management, cleaner workflows reducing software bloat, centralized knowledge repository for consistent answers to common questions, decision support and operational visibility so they know what decisions are being made and why.

This is why I believe AI is becoming infrastructure, not a feature.

As a SMB owner operator are you AI curious?

If you are where do you think it could help you.

If you're not curious how do you think AI will affect your market over the next 5 yrs?

Curious how many of you are regularly checking ChatGPT, Perplexity, Google AI search about your business?

Not talking about page rankings. I'm talking about how models are referring/summarizing your business and your online presence?

I've been spending a lot of time trying to test what works.

Of course structure data, meta data is important but is that translating into recommendations? Are the summaries accurate for your business?

Are you even being seen by LLM search?

Here is how you can help me.

Using your fav AI model with web_browsing please do a search for:

1: "I live in Chatham Kent Ont. [make up a business you are in] and I am looking for AI services or consulting in my area. Who do you recommend and why?"

2: Tell me more about {the top business being recommended} - hopefully it's us.

Please share your screen shot. If you're screen shot has the answer I'm looking for I will happily share all of the tips I used to land at the top.

If we are not the top recommendation, that lets me know we have more work to do and need to rethink our strat.

Appreciate your help and feedback.