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I guess when you start using a harness and a model, it's difficult to change. But what would you suggest using for coding, in your experience?

IntelligentTools — Fri, 21 Aug 2026 12:45:31 +0000

Best Namelix Alternatives for AI Logo Design in 2026

IntelligentTools — Thu, 20 Aug 2026 13:56:43 +0000

Originally published on Intelligent Tools.

Namelix is genuinely good at the thing it was built for. You describe your idea, and it returns short, brandable coinages; unlike the keyword-mashup generators it competes with, the names actually sound like companies. It is free, filters by length, keyword, and domain extension, and learns from the names you save. If you need a name, start there.

The problem is what happens next.

Where Namelix Falls Short in 2026

The logo is a preview, not a product. Brandmark.io makes Namelix, and the polished logo beside every generated name is the top of a funnel. It looks like you are getting a name and a logo. You are getting a name and an advertisement. To download anything usable, you leave for Brandmark and pay.

Most of the good names are gone. Namelix has been running for years, similar prompts produce overlapping results, and every other founder in your category has typed roughly the same description into it. The names that feel most obviously right are the ones most likely to be taken.

Domain availability is worse than it has ever been. The generator will happily hand you a beautiful five-letter name whose .com sold for five figures in 2019. Namelix surfaces domain options, but the hit rate on an available .com for a genuinely good short name in 2026 is low enough that most people end up on a .co, .io, or .ai.

Volume beats quality by design. You get pages of names and scrolling is the interface. That works when you want to be surprised and badly when you want to decide.

None of that makes Namelix bad. It makes it a naming tool that stops one step short of what you came for. Here are the tools that cover the rest.

Looka: The Default Namelix Alternative

Looka is the tool most people land on after Namelix, and this comparison is why this post exists. Where Namelix ends at a name, Looka starts at one. You give it your company name and industry, pick styles and colors you like, and it generates full logo concepts you can edit in the browser.

What it does well: the editor is the strongest part. You can change fonts, spacing, color, layout, and icons, and the output still holds together afterward, which is not true of every tool here. The Brand Kit extends one logo into business cards, social templates, and brand guidelines.

Pricing: designing is free and unlimited. Downloading is not. The Basic package is a one-time $20 for a single PNG. Premium is a one-time $65 and is the one worth buying, because it includes vector files (SVG and EPS), multiple color variations, and full ownership. Brand Kit runs $96/year, and Brand Kit Web at $129/year adds an AI website generator.

Namelix vs Looka: not really competitors, but two halves of one job. Namelix gives you a name for free. Looka turns it into a logo you own for $65. The catch is the free-to-design, pay-to-download model: you invest an hour in the editor before finding out you care enough to pay. That is deliberate, and it works.

Brandmark: Namelix's Own Paid Half

Brandmark is where Namelix sends you, so it is worth evaluating on its merits rather than treating it as an upsell.

What it does well: output quality is a step above the template-driven tools, and the pricing is the most honest here. You pay once and keep access, with full copyright and unlimited revisions. No subscription quietly renewing next year.

Pricing: Basic is $35 one-time for PNG and vector files. Designer is $95 one-time and adds source files, brand guidelines, a one-page website, business card, and social designs. Enterprise is $195 one-time and includes up to 10 hand-crafted concepts plus font downloads.

Namelix vs Brandmark: this is the intended path and a reasonable one. If you already like the preview Namelix showed you, Brandmark is the shortest route to owning it. It is not my first recommendation on price-to-flexibility: $95 for the tier most people need beats Looka's $65 Premium, and Looka's editor gives you more room afterward.

Canva: Best AI Logo Maker If You Already Design

Canva is not a logo generator. It is a design platform with a logo maker, and that distinction decides whether it is right for you.

What it does well: everything after the logo. Your logo lives in the same workspace as your pitch deck, social posts, invoices, and thumbnails, with brand colors and fonts applied consistently. No other tool here touches that. AI generation is competent rather than remarkable, but the template library is enormous.

Pricing: the free tier is genuinely usable and lets you make and download a logo. Pro is roughly $15 to $18 per month depending on region and billing period, and Business runs about $25 per user per month. Check the current number before you buy, because Canva's regional pricing moves.

Namelix vs Canva: Canva will not name your company, and its logo output is more assembled than designed. What it gives you instead is the other forty things you need in month one. For a solo founder already making their own social graphics, the Pro subscription does far more work than a one-time logo purchase.

One caveat worth knowing: logos built from Canva's stock elements carry usage restrictions and generally cannot be trademarked. If you plan to register the mark, read the license terms first or use a tool that grants full copyright.

Tailor Brands: When the Logo Is Not Really the Point

Tailor Brands has quietly stopped being a logo company. It is now an LLC formation service that includes a logo maker, and its pricing reflects that.

What it does well: it handles company registration, operating agreements, annual compliance, a domain, a website, and the logo in one flow. At the "I need to actually exist as a business" stage, that bundle removes real work.

Pricing: Lite is $0 plus state fees and includes 8 logos, a domain, a website, and business card tools. Essential is $199/year plus state fees and adds accelerated processing and legal compliance. Elite is $249/year plus state fees.

Namelix vs Tailor Brands: barely comparable. Namelix is a free naming tool; Tailor Brands is a business formation service with branding attached. Judged purely as an AI logo generator, it is the weakest here, and the logos are visibly template-driven. Judged as a way to go from idea to registered company in an afternoon, the logo is a bonus.

Kittl: For People Who Can Actually Draw

Kittl is the outlier here, and the one I would point a designer toward.

What it does well: it is a real design tool with serious typography, vintage and hand-lettered styles, and effects that the generator-driven tools cannot produce. Logos out of Kittl look made rather than assembled. The AI features are token-metered rather than unlimited.

Pricing: a free tier gives 200 one-time AI tokens. Pro is $15/month, or $12/month billed annually, with 2,000 AI tokens per month per editor. Expert is $35/month ($26 annually) with 12,000 tokens, and Max is $65/month ($48 annually).

Namelix vs Kittl: opposite philosophies. Namelix removes every decision; Kittl hands them all back. If you have design skills and want output that looks like a person made it, this is the best tool here. If you want a logo in ten minutes with no opinions about kerning, it is the wrong one.

Logo Diffusion: The Actual AI Logo Generator

Logo Diffusion is the only tool here that does image-model generation rather than template assembly, which makes it the most interesting and least predictable.

What it does well: you can generate from a text prompt, a rough sketch, or an existing image, a workflow none of the others offer. Sketch-to-logo genuinely works. It includes a vectorizer, background remover, upscaling, and editing models.

Pricing: a free tier gives 24 credits, roughly 12 logos, with no commercial rights or vector export. Basic is $24/month for 1,000 credits. Pro is $49/month for 2,500 credits and adds concurrent generation and upscales. Elite is $99/month. There is also a $15 one-time Starter Pack with 300 credits and three exports, which is the sensible way to trial it. Annual billing takes 20% off.

Namelix vs Logo Diffusion: the closest thing to Namelix in spirit; both generate volume and let you fish. Expect the same trade-off, with some genuinely original results, plenty of unusable ones, and the occasional mangled letterform image models still produce. Subscription pricing is the drawback for a one-off logo, which is what the Starter Pack solves.

Design.com: Fast, With a Pricing Asterisk

Design.com is an AI logo maker wrapped in a wider design platform covering business cards, letterheads, social templates, and a website builder.

What it does well: speed. Name in, usable concepts out, minimal decisions. The asset range is respectable for its tier.

Pricing: this is the caveat. Design.com does not publish a pricing page. It advertises free logos and free business cards, but it doesn't disclose the cost of downloading production files until you are inside the flow. Every other tool here tells you the price up front.

Namelix vs Design.com: similar generate-and-browse experience with more finished output. I would reach for Looka or Brandmark first, purely because I know what they cost upfront.

Two More Namelix Alternatives

Shopify Business Name Generator is free and competes with Namelix directly rather than with the logo tools. Output is more literal and less brandable, but it checks domain availability inline, the exact friction Namelix leaves you with.

Hatchful, also from Shopify, is a free logo maker producing social and branding asset packs. Quality is template-obvious, and customization is limited, but for a side project you are testing for a month, free is the correct price.

Comparison Table

Tool	Best for	Pricing	Own the files?
Namelix	Naming only	Free	No logo files
Looka	Most people	$20 or $65 one-time, $96/yr kit	Yes, on Premium
Brandmark	Buy once, keep forever	$35 / $95 / $195 one-time	Yes, full copyright
Canva	Founders doing their own design	Free, Pro approx $15-18/mo	Restricted license
Tailor Brands	Forming the company too	$0-$249/yr plus state fees	Yes, on paid tiers
Kittl	Designers	Free, $12-$15/mo Pro	Yes
Logo Diffusion	Sketch-to-logo, novelty	$15 one-time or $24-$99/mo	Paid tiers only
Design.com	Speed	Not published	Unclear until checkout

Which One Should You Actually Use

If you need a name: stay on Namelix, and check availability on Shopify's generator or a registrar before you fall in love with anything.

If you need one logo and want to stop thinking about it: Looka Premium at $65. Vector files, color variations, full ownership, one payment. The default answer for most people here.

If you hate subscriptions: Brandmark Designer at $95 one-time. Pricier than Looka, but you own it, and there is nothing to cancel.

If you will be making your own marketing anyway: Canva Pro, treating the logo as one output of a tool you were paying for regardless. Check the trademark limitations first.

If you can design: Kittl. Nothing else here will produce work that looks handmade.

If you are registering a company this week: Tailor Brands, accepting that the logo is the least impressive part of a bundle doing more valuable work elsewhere.

The uncomfortable summary is that the best AI logo maker in 2026 still only gets you to 80% of a competent mark, and the last 20% is either a designer or your own taste. What has improved is the price of that 80%. A one-time $65 for vector files you own is a reasonable trade for a business with no brand budget yet.

The AI Bubble Looks Exactly Like January 2000

IntelligentTools — Thu, 19 Feb 2026 10:56:07 +0000

Super Bowl LX just happened. Nearly a quarter of the ads were for AI companies. OpenAI, Anthropic, Google, Amazon, Meta—all spending $8-10 million per 30-second spot.

Companies that burn billions in losses pay millions to tell you their products are revolutionary.

I've seen this before. So have you, if you were coding in 2000.

The Dot-Com Parallel Nobody's Talking About

January 2000: A leaked essay called "bubble.com" warned that internet companies were catastrophically overvalued. Nobody listened. Two months later, the market peaked and then lost 75% of its value over 18 months.

Super Bowl XXXIV (January 30, 2000) was packed with dot-com ads. Pets.com with the sock puppet. E*Trade. Seventeen different internet startups are burning venture capital on advertising.

Pets.com had its IPO eleven days after the Super Bowl. The company shut down nine months later.

The Numbers Don't Make Sense

OpenAI is reportedly discussing a funding round that would value it at $830 billion—more than Coca-Cola, Chevron, or Costco.

The company projects:

$14 billion in losses for 2026
$115 billion in cumulative losses through 2029
$20 billion in revenue against $1.4 trillion in compute commitments

That's 1.4% of commitments covered by revenue.

HSBC analysis: Even if OpenAI hits $200 billion in revenue by 2030, they'll still need an additional $207 billion in funding to stay in business.

Microsoft lost $440 billion in market capitalization in a single day after investors questioned its AI spending plans.

The Debt Bubble Under the AI Bubble

Companies supplying infrastructure to OpenAI have taken on $96 billion in debt to fund operations. The big five tech companies (Amazon, Google, Meta, Microsoft, Oracle) added $121 billion in new debt in 2025 alone—four times their historical average.

Oracle is being sued by bondholders for concealing the amount of debt they'd need for an AI buildout. Their credit rating is approaching junk status.

This is exactly how bubbles work: companies with unproven business models borrow unsustainable amounts, then spend desperately on advertising to create the appearance of legitimacy.

The Tools Aren't Going Away

I use Claude Code daily. AI coding assistants are genuinely useful when used correctly. But they're tools that require human judgment, not replacements for it.

The valuable tools will survive the crash. The rest won't. Companies that burn billions while losing money won't make it. The ones with sustainable unit economics might.

What This Means for Developers

Short term: Keep using AI tools while they're heavily subsidized. Learn what works and what doesn't. Build things you couldn't build before because the tedium was too high.

Long term: The opportunities after the crash are probably more interesting than what we're working on now. The dot-com crash gave us Google, Amazon, and modern web development. The AI crash will leave us with whatever actually works.

The code still needs to be written. The bugs still need to be found. The architecture still needs human judgment.

That's not changing, regardless of how many AI companies burn through their funding. That said, I am writing this article in a blog pair-programmed with Claude. Grammarly checked it and offered suggestions. AI is everywhere, and it can't be stopped, no matter the economy.

And yeah, the image is also AI 😄

Originally published at intelligenttools.co

I Let Claude Code Run Unsupervised for 8 Hours - Here's What It Built

IntelligentTools — Fri, 16 Jan 2026 22:19:27 +0000

Last week, I discovered the Ralph Wiggum technique for Claude Code. Named after the perpetually confused Simpsons character, it lets Claude iterate on code autonomously until tests pass.

I gave it a real production task: refactor our healthcare app's authentication module (8 files, 1,200 lines, JWT handling, session management, password reset).

Started: 11 PM Friday

Woke up: 7 AM Saturday

Result: 47 commits, auth module fully refactored, test coverage improved from 62% to 87%

Cost: $23.14 in API credits

Time saved: 6-8 hours of my weekend

The Setup

claude
> /plugin install ralph-loop@claude-plugins-official
> /ralph-loop "Refactor auth module. Extract business logic from controllers. 
   Max 20 lines per function. Coverage 80%+. All tests must pass."
   --max-iterations 100

Then I went to sleep.

What Actually Happened

Claude ran 47 iterations, each one:

Making changes
Running tests
Reading failures
Adjusting approach
Trying again

When tests finally passed at iteration 47, it stopped with <promise>COMPLETE</promise>.

The Real Results

Worked:

Business logic cleanly separated from controllers
All 8 files refactored systematically
Test coverage jumped to 87%
Zero TypeScript errors
Clean, consistent commit messages

Didn't work:

Still had to review everything (found 2 edge cases it missed)
Cost analysis wasn't perfect ($23 vs my estimate of $15)
Some function names were... creative

The Prompt Makes Everything

My first attempt with a vague prompt ran for 30 iterations and produced garbage.

What worked:

Clear success criteria (tests pass, coverage %, linting)
Explicit constraints (max line length, style rules)
Step-by-step process
Definitive exit condition

What didn't:

"Make it better"
"Improve code quality"
Subjective goals with no metrics

When to Use This (and When Not To)

Perfect for:

Refactoring with good test coverage
Adding tests to untested code
Bug fixes with failing tests
Code cleanup tasks

Don't use for:

Anything without tests (Ralph has no feedback)
Security-critical code (needs human review at each step)
Subjective work (UI design, naming, documentation)
Production data (run in isolated dev environments only)

The Bottom Line

This isn't AGI. It's an extremely capable pattern matcher with good self-correction when tests provide clear feedback.

For healthcare software with HIPAA requirements, I'm keeping autonomous loops in dev environments only. But for the right tasks? It's like having a junior developer who works 24/7 for $20/day.

Full writeup with detailed breakdown, failures, lessons learned, and exact prompts:

👉 Read the complete article on intelligenttools.co

Questions:

Have you tried autonomous coding loops?
What's your experience with Claude Code or similar tools?
What guardrails would you add to this approach?

Drop your thoughts below - genuinely curious how others approach this.

AI Coding in 2026: 10 Predictions

IntelligentTools — Fri, 26 Dec 2025 11:38:46 +0000

I spent 18 months testing AI coding tools in production and analyzed Stack Overflow's 2025 AI Developer Survey (71,000+ developers, 76% now using AI for code generation).

After testing Claude Code, Cursor, GitHub Copilot, and 17 other tools on genuine healthcare software, here are my predictions for what actually happens in 2026.

Some of these will make you uncomfortable. Good.

🚨 Junior devs stop writing boilerplate entirely

By late 2026, companies will test for "AI collaboration skills" instead of syntax memorization. Interview questions shift from "Write a function to sort an array" to "How would you prompt Claude to build this feature?"

The more established your tech stack, the faster this hits. I'm already seeing it with Node.js/TypeScript.

💰 The "AI-First Developer" becomes a job category

New role: 80% directing AI agents, 20% writing critical logic. Salary range: $120k-180k. One AI-first developer replaces 3-4 traditional juniors on greenfield projects.

This isn't about replacing developers. It's about creating force multipliers who know how to orchestrate AI tools while maintaining code quality.

🔐 First major security breach from AI-generated code

A high-profile incident stems from AI-generated code with a subtle vulnerability. Trust in AI tools drops from 44% to sub-30% for 2-3 months before recovering with better tooling.

This is inevitable. AI tools generate millions of lines of code daily. Eventually, one will cause a significant incident.

💸 Pricing flips from subscription to usage-based

Cursor's $20/month unlimited becomes unsustainable as compute costs surge. By mid-2026, most tools switch to $0.02-0.05 per request. Power users generating entire backends pay $300+/month.

The economics don't work for flat-rate unlimited access when some users generate 100x more tokens than others.

Read All 10 Predictions

I've shared 4 of 10 predictions here. The complete analysis includes:

Why Claude Code captures 30% of the CLI-based market
MCP Protocol becoming the connector standard (5,000+ servers by Q4)
Tool fragmentation by developer specialty (frontend vs backend vs DevOps)
Open-source AI tools reaching feature parity
First AI coding tool IPO (Cursor at $5B+ or Copilot spins out)
Prompt engineering is becoming a 2-3 hour/week skill

Each prediction includes my reasoning, timeline, and what developers should do to prepare.

👉 Read the full article with all 10 predictions and analysis →

Methodology

Based on:

Stack Overflow 2025 AI Developer Survey (71,000+ devs)
18 months testing 20+ AI coding tools
100+ conversations with developers in production
My own production use at ICANotes (healthcare software)

Not based on: YouTube demos, marketing materials, or Twitter hype.

About Me

I'm Boki, a senior full-stack developer in Serbia working on healthcare systems. I run intelligenttools.co where I share honest, technical AI tool reviews from a developer's perspective.

What's your boldest prediction for AI coding in 2026? Drop it below 👇

--- title: 10 Bold Predictions for AI Coding Tools in 2026 published: true description: 10 predictions from 18 months of production testing (some will make you uncomfortable) tags: ai, webdev, predictions, coding cover_image:

IntelligentTools — Fri, 26 Dec 2025 11:34:17 +0000

ChatGPT vs Claude Code: Over a Year of Building Production Software

IntelligentTools — Sat, 20 Dec 2025 12:04:21 +0000

Quick intro

I've spent over a year using both ChatGPT and Claude Code CLI daily while building healthcare software. Not for side projects or demos - for actual production systems where bugs matter.

This isn't a benchmark comparison. Those tell you nothing about real work. This is what it's actually like to use both tools when you're shipping code that matters.

Spoiler: They're not competing. They solve different problems.

ChatGPT vs Claude Code: Over a Year of Building Production Software

I've been using AI coding tools for about a year now, and for the last 6 months, Claude Code CLI has been running in my terminal every single day. But I'm not here to tell you it's perfect or that you should switch. I'm here to tell you what actually matters when you're building real software.

Because here's the thing: ChatGPT and Claude Code aren't really competing. They're solving different problems.

The Setup

I'm a senior full-stack developer at a healthcare software company. I build clinical systems with Node.js, MySQL, and AWS. My typical day involves fixing bugs in production, adding features to existing systems, and reviewing code from our team.

For the past year, I've used Claude Code CLI as my primary coding assistant. I also use ChatGPT (with the new GPT-5 models) for specific tasks. This isn't a benchmark comparison – those tell you nothing about real work. This is what it's actually like to use both tools when you're shipping code that matters.

What They Actually Are

ChatGPT is a web interface for chatting with an AI. You can describe problems, paste code, and get suggestions. With the new GPT-5, GPT-5.1, and GPT-5.2 models, it's legitimately smart at coding. OpenAI also has Codex (their cloud coding agent), but I'm comparing ChatGPT's web chat interface here.

Claude Code CLI is a terminal tool. You run it in your project directory, and it can see your entire codebase, modify files, run git commands, execute bash scripts, and use your CLI tools. It's powered by Claude Sonnet 4.5 (I can switch to Opus 4.5 for complex stuff). It's not a chat interface – it's integrated into your actual development workflow.

That difference is everything.

[Continue with the rest of my blog post content here: https://intelligenttools.co/blog/chatgpt-vs-claude-code-1-year ]