We've built the same blog system hundreds of times. Different products, different frontends, hundreds of times writing the same infrastructure. Each rebuild took weeks away from actual product development.

The breaking point

Recently, we opened our code editor to create another 'posts' table and stopped. After twenty years building products that reached over 25 million people, working with companies like Ocado and Midcounties Co-op, we knew better. What if we built this once, properly, and used it everywhere?

Five days to ship

We gave ourselves a week. Constraints breed clarity.

Day 1: Database schema. Multi-tenant from the start—each site isolated, clean API boundaries.

Days 2-3: Dashboard and post editor. TipTap for editing, shadcn/ui for components. Good enough to use today.

Day 4: REST API with authentication, rate limiting, webhooks for static site rebuilds.

Day 5: Polish and deployment. By evening, the first post was created via API. It worked.

What Blot actually is

Blot is a headless CMS with one job: manage blog content across multiple projects from a single dashboard. Posts, categories, tags, authors, and a solid API. Nothing more.

Multi-tenant because we manage multiple projects. API-first because we use different frontend frameworks. Webhooks because static sites need to rebuild when content changes. These aren't theoretical features—they're solutions to actual problems.

Using it in the real world

Today, Blot powers blogs for our products. Same dashboard, different API keys, different frontends. One post published triggers rebuilds across Next.js, Astro, wherever.

The economics work too. No per-seat pricing. Flat monthly pricing. Own the infrastructure. No vendor lock-in.

What we learned

Most 'essential' features aren't.

We shipped the minimum useful product and started using it immediately. Being our own customer created an instant feedback loop. Instead of building custom fields, content versioning, or visual page builders, we focused on what actually mattered.

What's next

Improvements continue based on actual use. Recent additions include team collaboration, custom domains, and import tools. The roadmap focuses on what builders need: better media management, content versioning, analytics.

Stop rebuilding blog systems. Build it once, use it everywhere.

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Why We Built ContentNow

I watched content creators struggle with the same problem: their brand voice kept changing. One post sounded professional. The next, casual. Blog articles read differently than social posts. Every piece of content was a fresh start, reinventing tone and style.

The real cost wasn't money—it was consistency.

The Brand Consistency Problem

Most AI writing tools treat every generation as isolated. You paste a prompt, get content back, hope it matches your brand. Next time? Start over. Describe your voice again. Hope the AI remembers your guidelines.

For the 52 Products challenge I'm running, this was unsustainable. I needed every product announcement, every social post, every article to sound like the same person wrote it. Because building trust means sounding consistent.

What ContentNow Does Differently

Brand Profiles: Define your voice once. Your tone, your guidelines, your content standards. Every piece you generate maintains those standards automatically.

Custom Templates: Build content templates that embed your brand voice. Generate variations that stay on-brand, not random outputs hoping for the best.

Batch Generation: Create 50 social posts that all sound like you. Plan months of content knowing it'll maintain your voice.

Unified Publishing: Publish to Webflow CMS and schedule social posts from one place. Your consistent brand voice reaches every platform.

Oh, and the Bring Your Own Keys model? That saves 80% on AI costs. But the real value is knowing every piece of content sounds like your brand.

We Use It Daily

Every product in my 52 Products challenge runs through ContentNow. Every announcement maintains the same voice. Every social post sounds consistent. Every blog article reflects the same brand standards.

Because that's what content should do: build trust through consistency.

Who It's For

Content creators and marketers who value brand consistency over one-off generations. Who need their voice maintained across Webflow and social media. Who want tools that remember their brand standards.

Free tier: 50 generations monthly. Pro tier: thousands of generations, all maintaining your brand voice.

Your brand. Your voice. Your content. Consistent.

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The Problem

Fire door inspection is broken. The UK has 50+ million fire doors that need inspecting 1-2 times per year. Every single one is done manually, taking 10-15 minutes per door.

I watched inspectors spend entire days in buildings, checking gaps with feeler gauges, photographing damage, writing everything down. Miss something after 30 doors? That's a compliance violation. And fire doors don't give second chances.

The Solution

We built FireDoor360 in 5 days. Take four photos of a door, AI analyzes it against BS 8214:2016, get faults with severity and remediation guidance in 3 seconds.

No training data needed. Claude Vision already understood building codes through reasoning. We just had to ask properly.

What It Does

• Detects door damage, excessive gaps, seal issues, hardware defects
• Reduces inspection time from 15 minutes to 3 minutes per door
• Generates professional PDF reports automatically
• Standardizes quality across inspectors

The Real Lesson

You don't need a grand vision. You need a real problem worth solving.

Inspectors were wasting hours per building on work that should take minutes. We didn't validate a hypothesis. We built the solution to a problem we could see clearly.

7,200 lines of code in five days. Not because we're fast. Because we cut everything that wasn't essential. No fancy features. Just the job that needed doing.

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The Problem Started at My Gym

I wasn't trying to start a nutrition company. I was just trying to help my gym owner solve a problem.

He'd been recommending nutrition tracking apps to members, but they kept giving up. The apps were too complicated—weighing food, scanning barcodes, entering fifteen ingredients for one meal. It was turning nutrition tracking into a second job.

I'm a product designer, and I knew there had to be a better way.

Building It the Right Way: Fast

I didn't spend months planning. I used Precode's 5-day MVP sprint methodology to build the first version.

The goal was simple: create nutrition tracking that actually respects people's time. No barcode scanning. No food scales. No fifteen-tap processes.

Just take a photo of what you ate or tell the app. Let AI figure out the macros and calories. See your progress. That's it.

AI as a Tool, Not a Gimmick

Here's what I've learned about building products: technology should be invisible. Nobody wants to use AI for the sake of using AI. They want to solve a problem.

The problem was clear: people want to track nutrition without it taking over their lives.

AI-powered tracking wasn't the goal—it was simply the best tool for the job. Instead of forcing you to become a data entry clerk, AI understands what you ate from a simple description or photo. Snap a picture of your meal, and the AI logs your macros and calories automatically. It does the tedious work while you focus on your goals.

What Simple Actually Means

Simple isn't easy to build. Simple means saying no to features that would complicate things.

For Spartan Nutrition, simple means:

• No barcode scanning
• No weighing food
• No complicated logging processes
• No overwhelming dashboards

Just take a photo of your meal or tell us what you ate. The AI figures out your macros, calories, and nutrition. You see your progress. Done.

Built for Consistency, Not Perfection

Spartan Nutrition won't give you perfect macros to the decimal point. That's not the goal.

The goal is consistency. Most people quit tracking not because the data isn't precise enough, but because the process is too painful.

The AI-powered tracking is accurate enough to help you reach your goals, and simple enough that you'll actually use it every day.

Why Simple Matters

You shouldn't need a PhD to track your lunch. You shouldn't need to carry a food scale everywhere. You shouldn't need to spend fifteen minutes logging what took five minutes to eat.

That's not a discipline problem. That's a software problem. And software problems can be solved.

Spartan Nutrition is my attempt at solving it. Simply and effectively for people who just want to track their nutrition without it taking over their lives.

No fluff. No complexity. Just AI-powered nutrition tracking that actually works.

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I was losing customers and didn't even know it.

Someone on Reddit was asking about tools like mine. Perfect opportunity, right? Except I found out three days later. Three days. By then, the thread was dead and someone else had swooped in.

This happened again. And again.

So I tried the "proper" social listening tools. You know the ones. Enterprise. Dashboard with seventeen tabs. Setup wizard that takes forty-five minutes. Monthly cost that makes you wince.

They're built for brands monitoring Super Bowl campaigns, not for someone running a small SaaS with their laptop and a dream.

Here's What's Wrong With Social Listening

The big players assume you've got a team. A budget. Time to configure Boolean queries and train junior staff on their Byzantine interface.

They're optimised for quarterly reports, not for "someone just mentioned my competitor and I need to reply in the next hour."

And the pricing? Insane. You're paying for features you'll never use, data you don't need, and support for platforms that don't matter to you.

What We Actually Need

I just wanted to know when people talk about my space. That's it.

I wanted alerts I could actually act on. Not a firehose of noise. Not sentiment charts I'd ignore. Just the good stuff, filtered intelligently, delivered when it matters.

I wanted to reply quickly. Helpfully. While the conversation's still warm.

So We Built Overheard

It monitors keywords across Reddit, Twitter, and other places your customers actually hang out. AI figures out what's worth your attention and what's just noise. You get alerts. You reply (we'll even suggest responses). Done.

No setup wizards. No enterprise onboarding calls. No paying for a marketing team's worth of seats.

Here's the controversial bit: most "social listening" is just corporate vanity. Brands obsessing over mentions they can't do anything about. We built Overheard for people who actually want to have conversations, win customers, and help people.

It's social listening for builders, not boardrooms.

That's it. That's why Overheard exists.

We're opening up access soon. Join the waitlist if you're tired of missing conversations that matter.

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Here's the thing about AI tools: they're all good at different things.

Claude's brilliant for code reviews. ChatGPT crushes research. Gemini's fast for quick questions. Grok brings the spice.

But using them meant living in browser tab hell. Copy, paste, switch, repeat. Ask the same question four times. Compare answers. Waste time.

It felt stupid.

The Aha Moment

I was debugging a gnarly function at 2am. Asked Claude. Got a solid answer. But something felt incomplete.

So I asked ChatGPT the same thing. Different perspective. Better solution.

Then it hit me: Why am I doing this manually?

What if I could just type one message and get six AI perspectives at once? Let them duke it out. Cross-validate. Challenge each other's assumptions.

That's when I started building Nattr.

Everyone's Building the Wrong Thing

The AI tool space is obsessed with wrappers. Pretty UIs around a single model. Pick your favourite, lock yourself in.

That's backwards.

The future isn't "Which AI is best?" It's "Why choose?"

Every model has blind spots. Every provider has strengths. Using just one is like hiring a consultant and refusing to get a second opinion.

One Week, Six AIs, Zero BS

We built Nattr in one weeks of intense work. No funding rounds. No pitch decks. Just us and Claude Code, building the tool we wanted to exist.

Six AI providers in one chat. Type @all and they all respond. Toggle web search on. Watch them collaborate in real-time.

Claude can be your code reviewer. ChatGPT your research assistant. Gemini your quick-answer machine. All in the same conversation.

Want the same model playing different roles? Add three Claudes with different personas. One debugs, one reviews code quality, one challenges your architecture choices.

What We Actually Built

Nattr isn't trying to be everything. It's doing one thing well: letting you use multiple AIs without the copy-paste hell.

No revolutionary AI breakthrough. No proprietary model. Just a better way to work with the tools that already exist.

Sometimes the most useful product isn't the most innovative one. It's the one that removes friction from your actual workflow.

That's Nattr. Six AIs, one conversation, zero tab-switching.

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Why We Built Domain Checker

 Last month I was helping our outbound team set up new sending domains. We needed 20 available
 domains with variations of our brand name. You know, like getprecode.com, useprecode.co,
 precodehq.io - the usual cold email infrastructure.

 Simple task, right?

 I spent three hours checking domains one by one. Copy domain name. Paste into registrar. Wait for
 the "sorry, taken" message. Repeat.

 That's not work. That's punishment.

 So I did what any reasonable person would do: I built a tool to fix it.

 Domain Checker does one thing well. You type your brand name. You pick which TLDs you care about.
 You tell it how many available domains you need. It finds them.

 That's it.

 No account creation. No API keys to manage. No 47-tab pricing comparison. Just type, click, get
 results.

 The tool keeps checking variations until it finds what you asked for. Need 20 available domains?
 It'll check 50, 100, 200 if that's what it takes. You see results as they come in - no waiting for
  some loading spinner to finish.

 When it's done, export to CSV or copy straight to clipboard.

 We could have added a million features. Saved searches. Purchase integration. Price comparison.
 User accounts. All the stuff that turns simple tools into bloated software.

 We didn't.

 Not because we couldn't. Because the point was to solve that specific problem - finding available
 domain variations without wasting your afternoon.

 Cold email teams shouldn't spend their time hunting for domains. They should spend it writing
 emails that help people.

 We built Domain Checker so you can get back to the work that matters.

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