Tari Ibaba is a software developer with years of experience building websites and apps. He has written extensively on a wide range of programming topics and has created dozens of apps and open-source libraries.
If you’re still obsessed with writing “clean code” in 2025 then you are living in the stone age.
The clean code era is over. AI is here.
Your precious descriptive variable names,
Your admirable small functions,
Your meticulous design patterns and tireless refactorings…
All these things are far far less important now in the age of AI.
I can’t even remember the last time I created a variable by myself.
Wrote a function from scratch by myself?
Even created a file by myself? 🤔 (super rare)
Nobody codes like that anymore (sorry).
AI is here and modern developers don’t code that way.
Lol, you people and your annoying AI hype. Vibe coding is useless and AI can never replace programmers in any way. Stop talking nonsense.
Ha ha, yes I know some of you are still scoffing with disdain at the recent uprising of vibe coding and coding agents.
You proudly refuse to use even the slightest bit of AI in your coding.
Even basic Copilot code completions from 2021 are a no-no for you.
Well hate to break it to you but the world is leaving people like this behind.
There’s no going back — AI-first development is fast becoming the gold standard.
What matters most now is not clean or clear code — what matters is clear intent, goals, and context for the AI agent.
Not descriptive variable names — but now descriptive well-written prompts.
No longer just using the DRY principle in your code — but now also in all your AI interactions by setting powerful system prompts and personalized style guides.
No longer just about using the most intuitive and powerful libraries and APIs — but now using the all most powerful and highly capable MCP Servers.
Coding in 2025 is no longer about typing — it’s about thinking.
Actually it’s always been — but now the power of your thoughts has exploded drastically.
A thought, a design, an idea that took several days and weeks to be typed into life now takes a few minutes of prompting.
AI has astronomically expanded the power of our minds to do far more than ever before at any point in human history.
Should we still be wasting so much time obsessing over low-level details like whether we named our variables with snake case or camel case?
It’s time to level up and achieve our true potential.
Comprehensive context provisions, sophisticated prompting techniques, elaborate intent definitions, hyper-personalized system prompts, high-powered MCP server integrations…
These are the crucial things you need to focus right now.
These are what will turn you into a god-mode developer.
The new Stitch tool from Google may have just completely ruined the careers of millions of web & UI designers — and it’s only just get started.
Just check out these stunning designs:
This is an absolute game changer for anyone who’s ever dreamed of building an app but felt intimidated by the whole design thing.
It’s a huge huge deal.
Just imagine you have a classic app idea — photo sharing app, workout app, todo-list whatever…
❌ Before:
You either hire a designer or spend hours wrestling with design software trying to create a pixel perfect UI.
Or maybe you even just try to wing it and hope for the best, making crucial design decisions on the fly as you develop the app.
✅ Now:
Just tell Stitch whatever the hell you’re thinking.
Literally just describe your app in plain English.
“A blue-themed photo-sharing app”:
Look how Stitch let me easily the design — adding likes for every photo:
Or, if you’ve got a rough sketch on a napkin, snap a pic and upload it. Stitch takes your input, whatever it is, and then — BOOM — it generates a visual design for your app’s user interface. It’s like having a personal UI designer at your fingertips.
But it doesn’t stop there. This is where it gets really cool — especially for developers.
Stitch doesn’t just give you a pretty picture. It also spits out the actual HTML and CSS code that brings that design to life.
Suddenly your app concept isn’t just an idea — it’s a working prototype.
How amazing is that?
Stitch is pretty smart too. It can give you different versions of your design, so you can pick the one you like best. You can also tweak things – change the colors, switch up the fonts, adjust the layout. It’s incredibly flexible. And if you want to make changes, just chat with Stitch. Tell it what you want to adjust, and it’ll make it happen. It’s a conversation, not a command line.
Behind all this magic are Google’s powerful AI models, Gemini 2.5 Pro and Gemini 2.5 Flash. These are the brains making sense of your ideas and turning them into designs and code. The whole process is surprisingly fast.
Who is this for?
Everyone. If you’re a complete beginner with zero design or coding experience, Stitch is your new best friend. You can create professional-looking apps without breaking a sweat.
It’s a fantastic way to rapidly prototype ideas and get a head start on coding for seasoned developers.
Right now, Stitch is in public beta, available in 212 countries, though it only speaks English for now. And yes, you can use it for free, with a monthly limit on how many designs you can generate.
It’s a super-powered starting gun for your app development journey. It streamlines the early stages to get you from a raw idea to a tangible design and code much faster.
And if you still want more fine-grained control, you can always export your design to Figma.
So, if you’ve got an app idea bubbling in your mind, Google Stitch might just be the tool you’ve been waiting for to bring it to life.
This most intelligent AI model on the planet just got an incredible new coding CLI.
Grok — the genius model from xAI sitting comfortably in #1 of several notable AI benchmarks.
Massive boost in speed and power in your software development.
Carry out massive context-aware tasks on your codebase with simple English right from your CLI:
Refactor functions or files
Edit project code based on coding standards
Generate shell scripts or bash commands
Automate git operations
Integrate with any MCP server
What took an hour of manual coding and debugging before → Now: a few minutes.
Just describe whatever you want and it takes care of the rest.
grok-cli is open-source and growing FAST with dozens of contributions already.
Conversational
Launch Grok CLI with the grok command:
Opens an interactive session
Remembers previous prompts
Lets you refine requests naturally — like a real-life conversation.
Context-aware
Grok CLI reads your project files — it knows what it’s editing.
Ask it to:
Change the logic in a file
Rename functions
Split code into modules
It works from actual source context — no guesses or hallucinations.
Shell and bash
Ask something like “compress all images in the assets folder” or “create a backup of the .env file” — Grok CLI will generate and run the correct commands — like zip.
Built-in
Grok CLI includes smart tools for file editing, git management, and navigation.
These tools run automatically when your prompt matches what they handle — giving you a clean interface without memorizing commands.
Project-specific instructions
By placing a .grok/GROK.md file in your repo, you can customize how Grok CLI behaves.
For example, you can specify preferred frameworks, coding standards, or architectural constraints. This makes it ideal for team workflows and codebases with strict conventions.
Large project context support
Grok CLI supports large context windows. It can review and reason over entire projects or multiple files at once, making it suitable for complex refactors, architecture reviews, or onboarding support.
Installation and setup
To get started you need:
Node.js version 16 or higher
A Grok API key from x.ai
Installation is straightforward:
npm install -g @vibe-kit/grok-cli
Then run:
grok
You can also run one-off prompts with:
grok --prompt "What does this function do?"
Set API keys with:
GROK_API_KEY environment variable
.env file
CLI --apiKey flag
~/.grok/user-settings.json file
You can also configure the base URL and model via the same methods.
Workflow integration
Grok CLI is designed to work with your existing tools. It supports both interactive and headless modes.
Interactive mode: Launch with grok to enter a conversational session.
Headless mode: Use --prompt for scripting, CI pipelines, or automation.
Custom configuration: Use .grok/settings.json to define per-project behavior.
The CLI makes it easy to integrate AI into your day-to-day development without changing your habits or workflow.
Extend Grok CLI with MCP
One of Grok CLI’s most advanced features is support for the Model Context Protocol (MCP).
With MCP, you can connect Grok CLI to external services—like issue trackers, deployment tools, or custom APIs—and control them through the terminal.
Example:
grok mcp add linear --command "node" --args mcp-linear.js
Grok CLI will now be able to read issues from Linear, create tasks, or pull data—all through AI commands.
The built-in mcp command supports:
add: add a new server
list: view connected MCP servers
test: verify a server’s functionality
remove: disconnect a server
This turns Grok CLI from a code assistant into a full-fledged AI agent platform.
Grok CLI is more than just another AI chatbot—it’s a new kind of developer tool.
It brings powerful language models right into your command line — blending natural language prompts with deep integration into your codebase and workflow.
If you’re a developer who spends time in the terminal and wants to work faster, write better code, and automate tedious tasks using AI, Grok CLI is absolutely worth a try.
AI coding assistants are amazing and powerful—until they start lying.
Like it just gets really frustrating when they hallucinate APIs or forget your project structure and break more than they fix.
And why does this happen?
Context.
They just don’t have enough context.
Context is everything for AI assistants. That’s why MCP is so important.
These MCP servers fix that. They ground your AI in the truth of your codebase—your files, libraries, memory, and decisions—so it stops guessing and starts delivering.
These five will change everything.
Context7 MCP Server
Context7 revolutionizes how AI models interact with library documentation—eliminating outdated references, hallucinated APIs, and unnecessary guesswork.
It sources up-to-date, version-specific docs and examples directly from upstream repositories — to ensure every answer reflects the exact environment you’re coding in.
Whether you’re building with React, managing rapidly evolving dependencies, or onboarding a new library, Context7 keeps your AI grounded in reality—not legacy docs.
It seamlessly integrates with tools like Cursor, VS Code, Claude, and Windsurf, and supports both manual and automatic invocation. With just a line in your prompt or an MCP rule, Context7 starts delivering live documentation, targeted to your exact project context.
Key features
On-the-fly documentation: Fetches exact docs and usage examples based on your installed library versions—no hallucinated syntax.
Seamless invocation: Auto-invokes via MCP client config or simple prompt cues like “use context7”.
Live from source: Pulls real-time content straight from upstream repositories and published docs.
Customizable resolution: Offers tools like resolve-library-id and get-library-docs to fine-tune lookups.
Wide compatibility: Works out-of-the-box with most major MCP clients across dozens of programming languages.
Errors it prevents
Calling deprecated or removed APIs
Using mismatched or outdated function signatures
Writing syntax that no longer applies to your version
Missing new required parameters or arguments
Failing to import updated module paths or packages
Powerful use cases
Projects built on fast-evolving frameworks like React, Angular, Next.js, etc.
Onboarding to unfamiliar libraries without constant tab switching
Working on teams where multiple versions of a library may be in use
Auditing legacy codebases for outdated API usage
Auto-generating code or tests with correct syntax and parameters for specific versions
The Memory Bank MCP server gives your AI assistant persistent memory across coding sessions and projects.
Instead of repeating the same explanations, code patterns, or architectural decisions, your AI retains context from past work—saving time and improving coherence. It’s built to work across multiple projects with strict isolation, type safety, and remote access, making it ideal for both solo and collaborative development.
Key features
Centralized memory service for multiple projects
Persistent storage across sessions and application restarts
Secure path traversal prevention and structure enforcement
Remote access via MCP clients like Claude, Cursor, and more
Type-safe read, write, and update operations
Project-specific memory isolation
Errors it prevents
Duplicate or redundant function creation
Inconsistent naming and architectural patterns
Repeated explanations of project structure or goals
Lost decisions, assumptions, and design constraints between sessions
Memory loss when restarting the AI or development environment
Powerful use cases
Long-term development of large or complex codebases
Teams working together on shared projects needing consistent context
Developers aiming to preserve and reuse design rationale across sessions
Projects with strict architecture or coding standards
Solo developers who want continuity and reduced friction when resuming work
Definitely one of the most important MCP servers out there anywhere.
It’s designed to guide AI models through complex problem-solving processes — it enables structured and stepwise reasoning that evolves as new insights emerge.
Instead of jumping to conclusions or producing linear output, this server helps models think in layers—making it ideal for open-ended planning, design, or analysis where the path forward isn’t immediately obvious.
Key features
Step-by-step thought sequences: Breaks down complex problems into numbered “thoughts,” enabling logical progression.
Reflective thinking and branching: Allows the model to revise earlier steps, fork into alternative reasoning paths, or return to prior stages.
Dynamic scope control: Adjusts the total number of reasoning steps as the model gains more understanding.
Clear structure and traceability: Maintains a full record of the reasoning chain, including revisions, branches, and summaries.
Hypothesis testing: Facilitates the generation, exploration, and validation of multiple potential solutions.
Errors it prevents
Premature conclusions due to lack of iteration
Hallucinated or shallow reasoning in complex tasks
Linear, single-path thinking in areas requiring exploration
Loss of context or rationale behind decisions in multi-step outputs
Powerful use cases
Planning and project breakdowns
Software architecture and design decisions
Analyzing ambiguous or evolving problems
Creative brainstorming and research direction setting
Any situation where the model needs to explore multiple options or reflect on its own logic
Once you install it, it becomes a powerful extension of your model’s cognitive abilities—giving you not just answers, but the thinking behind them.
The Filesystem MCP server provides your AI with direct, accurate access to your local project’s structure and contents.
Instead of relying on guesses or hallucinated paths, your agent can read, write, and navigate files with precision—just like a developer would. This makes code generation, refactoring, and debugging dramatically more reliable.
No more broken imports, duplicate files, or mislocated code. With the Filesystem MCP your AI understands your actual workspace before making suggestions.
Key features
Read and write files programmatically
Create, list, and delete directories with precise control
Move and rename files or directories safely
Search files using pattern-matching queries
Retrieve file metadata and directory trees
Restrict all file access to pre-approved directories for security
Ideal scenarios
Managing project files during active development
Refactoring code across multiple directories
Searching for specific patterns or code smells at scale
Debugging with accurate file metadata
Maintaining structural consistency across large codebases
AI assistants can hallucinate APIs, suggest outdated patterns, and sometimes overwrite code that was just written.
GitMCP solves this by making your AI assistant fully git-aware—enabling it to understand your repository’s history, branches, files, and contributor context in real time.
Whether you’re working solo or in a team, GitMCP acts as a live context bridge between your local development environment and your AI tools. Instead of generic guesses, your assistant makes informed suggestions based on the actual state of your repo.
GitMCP is available as a free, open-source MCP server, accessible via gitmcp.io/{owner}/{repo} or embedded directly into clients like Cursor, Claude Desktop, Windsurf, or any MCP-compatible tool. You can also self-host it for privacy or customization.
Key features
Full repository indexing with real-time context
Understands commit and branch history
Smart suggestions based on existing code and structure
Lightweight issue and contributor context integration
Live access to documentation and source via GitHub or GitHub Pages
No setup required for public repos—just add a URL and start coding
Errors it prevents
Code conflicts with recent commits
Suggestions that ignore your branching strategy
Overwriting teammates’ changes during collaboration
Breaking functionality due to missing context
AI confusion from outdated or hallucinated repo structure
Ideal scenarios
Collaborating in large teams with frequent commits
Working on feature branches that need context-specific suggestions
Reviewing and resolving code conflicts with full repo awareness
Structuring AI-driven workflows around GitHub issues
Performing large-scale refactors across multiple files and branches
This new AI coding agent from Google is simply incredible. Google is getting dead serious about dev tooling. No more messing around.
Jules is a genius agent can understand your intent, plan out steps, and execute complex coding tasks without even trying.
A super-smart teammate who can tackle coding tasks on its own asynchronously to make software dev so much easier.
It works seamlessly in the background so you can focus on other important stuff.
Gemini 2.5 Pro
Jules is powered by Gemini 2.5 Pro, which is Google’s advanced AI model for complex tasks. This gives it serious brainpower for understanding code.
And you bet 2.5 Flash is on its way to give it even more insane speeds.
When you give Jules a task it clones your codebase into a secure virtual machine in the Google Cloud. This is like a private workspace where Jules can experiment safely without messing with your live code.
It then understands the full context of your project. This is crucial because it helps Jules make smart, relevant changes. It doesn’t just look at isolated bits of code; it sees the whole picture.
After it’s done, Jules shows you its plan, its reasoning for the changes, and a “diff” of what it changed. You get to review everything and approve it before it goes into your main project. It even creates pull requests for you on GitHub!
Jules is quite the multi-tasker. It can handle a variety of coding chores you might not enjoy doing yourself.
For example, it can write tests for your code, which is super important for quality. It can also build new features from scratch, helping you speed up development.
Bug fixing? Yeah Jules can do that too. It can even bump dependency versions, which can be a tedious and error-prone task.
One cool feature is its audio changelogs. Jules can give you spoken summaries of recent code changes, turning your project history into something you can simply listen to.
Google has made it clear that you’re always in charge. Jules doesn’t train on your private code, and your data stays isolated. You can review and modify Jules’s proposed plans at every step.
It works directly with GitHub, so it integrates seamlessly with your existing workflow. No need to learn a new platform or switch between different tools.
Jules is currently in public beta, and it’s free to use with some limits. This is a big step towards “agentic development,” where AI systems take on more responsibility in the software development process.
It might sound like Jules is coming for developer jobs, but that’s probably not the goal here — at least for now.
Jules is meant to be a powerful tool that frees up developers to focus on higher-level thinking, design, and more creative problem-solving. It’s about making you more productive and efficient.
So, if you’re a developer, now’s a great time to check out Jules. It could really change the way you work.
By Tari Ibaba
/ Last updated on September 11, 2025
MCP MCP… what’s this annoying MCP thing I keep seeing everywhere? What does it even mean?
Just another annoying AI buzzword that will die out soon right?
If you think that then you are dead wrong. This is HUGE.
MCP is massive new invention that is going to change everything.
It’s a major milestone for LLMs and agents and the AI revolution in general.
Bla bla bla… what does it mean Tari?? Start talking or GTFO!
Okay okay I will now but you really need to understand just how much of a game changer this is.
So this is the part where I tell you that MCP is an acronym that means Model Context Protocol — but that wouldn’t be saying much and I’ll be boring you to sleep.
The best thing is to give you a fascinating and powerful real-world analogy that you will understand instantly without even trying.
Think of the brain. The human brain.
Your brain is incredibly powerful — far far more intelligent than all the other species (combined??). Not even close.
But have you ever realized that your brain is… USELESS?!
Duuuude just effin explain MCP for me, I didn’t ask for your insults
No listen I’m not calling you dumb or anything like that — what I mean is — your brain can’t DO anything on it’s own, as far as the external world is concerned.
The only way your brain actually does anything in the physical world is by being connected to the rest of your body.
You could be the greatest genius the universe has ever seen.
You could THINK of the most beautiful poem, the most persuasive argument, the funniest joke in history…
You could IMAGINE the next great novel, the blueprint for a world-changing invention, the cure cancer…
You may KNOW where you want to go — the perfect destination, the goal, the person to meet, the protest to join, the stage to walk onto…
But without your biological tools — your mouth, your eyes, your hands, your feet… without these things, you are as good as non-existent.
There will absolutely nothing you can DO. You are completely powerless as far as the outside world is concerned.
So are you getting it now? This is the problem we’ve had with LLMs.
Since 2022 they’ve wowed us with their insane creativity and coding and summarization ability and so much more.
But they couldn’t really DO anything.
All they did was provide us with information. Even when AI agents came along, all they could do was reason and think (“think”).
It was our brains that then used the information to manually make things happen in the world.
This is what MCP changes forever.
They can think and process information, and now also perform real world actions.
They can get crucial data from ANY external data source to do ANYTHING.
AI agents are now in absolute god mode.
With MCP Servers the possibilities are now literally endless.
MCP Server. That’s just the name for anything that provide tools to an AI agent.
The MCP Server provides the tools. MCP tells it HOW to provide the tools.
For example:
GitHub MCP Server: provides tools that let’s the AI agent search any GitHub repo.
WhatsApp MCP Server: provides tools that let you search WhatsApp chats.
You see the real game changer of MCP is NOT actually about what all these incredible MCP Servers let you do.
Before MCP it was already somewhat possible to make LLMs interact with external services. For example manipulate the prompt or fine-tuning the model to provide some sort of JSON response of tools to call.
This was what platforms like AutoGPT and BabyAGI tried to do. It’s also why OpenAI and Google added function calling support to their models.
The main problem with these different attempts is exactly that — they were different. Or private like for GPT and Gemini function calling.
There was no standard and open way to let anyone create an AI agent that could have external tools plugged into it. Or to create tools to plug into any AI agent.
But now MCP has changed all that.
Now anyone can create programs that provide tools to make AI agents more powerful — without knowing anything about the agents beforehand.
That’s why we’ve been calling MCP the USB-C of AI applications.
USB-C standardized how tons of devices that needs to send all sorts of data to each other communicate.
Now as a manufacturer you no longer need to worry about the specific devices your users have and could need to connect your product to.
Just make sure it comes with a USB-C port and you’re good.
They can connect it to all the other billions of devices in the world that connect to USB-C — to provide or receive power or any kind of data.
And not just existing devices but ALL future devices — as long as they also support it.
This is the same game-changing thing MCP lets us do.
No more need for prompt manipulation or model-specific function calling.
And anyone can create agentic apps to use these tools, without knowing anything about the tools beforehand.
As long as the AI agent creator and MCP Server maker abide by the protocol, they will work with each other.
So that why it is really major milestone for the AI revolution.
Anything you can write code to do — an AI agent can do now.
Search your files in the cloud, update databases, control smart switches…
It drastically makes your AI agents waaay way more powerful — making YOU more powerful.
Claude 4 Sonnet is now available in Windsurf with no API key! (No more BYOK in Cascade).
You no longer have to pay additional costs for the amazing model.
And the coding has been absolutely insane 👇
For a while now people have been pointing out how amazing they find Claude 4 Sonnet, especially compared to Gemini 2.5 Pro and GPT-4.1. And this isn’t just hype – the difference is showing up in real-world workflows, especially in long context tasks, clean refactoring, and deep architectural suggestions.
And remember this is the junior sibling of Claude 4 Opus — that incredible model that literally did all the coding by itself in a massive project for a full hour and a half…
That was 90 actual minutes of total hands-free autonomous coding genius with zero bugs. Opus 4 planned, coded, edited, and completed an entire full-stack project, and Claude 4 Sonnet shares a massive chunk of that DNA. In fact, for a lot of development tasks, especially within a controlled and optimized coding environment like Windsurf, the gap between Sonnet and Opus is surprisingly small.
What makes this even more monumental is the fact that Windsurf had previously been locked out of native Claude 4 support.
When Claude 4 launched back in May, Anthropic explicitly restricted direct Windsurf access, most likely due to the intense competitive landscape and the recent strategic moves surrounding Windsurf — including rumors of OpenAI acquiring the company and Google’s subsequent licensing deal for Windsurf’s code-generation platform.
Disgustingly verbose tho?
The workaround was BYOK — “bring your own key.” That meant if you wanted to use Sonnet or Opus in Windsurf, you had to sign up for the Claude API separately, manage your own usage, and copy-paste keys manually. It worked — but it broke the seamless, fluid experience Windsurf is known for. It was a turbulent journey for users and the platform alike.
That’s now over. As of July 17, Claude 4 Sonnet is directly integrated into Windsurf again. You open the app, click a dropdown, and Sonnet’s there — no more hacks, no more limits. This signifies a successful restoration of support and improved collaboration between Windsurf and Anthropic, much to the relief of the developer community. It’s clean, fast, and shockingly good.
In fact, this might just be the best Claude experience available anywhere right now. The way Sonnet integrates into Cascade — Windsurf’s multi-agent AI flow system — feels like watching the future unfold in real time. Cascade breaks your prompts into intelligent stages, keeps memory across actions, and even offers live suggestions while you type. Now, with the raw power of Sonnet 4 plugged into that, it feels like pair programming with an elite coder who has already thoroughly digested your entire codebase.
The 200K context window means it can see everything — not just your current file, but your whole project: imports, dependencies, comments, TODOs, legacy bugs. Sonnet reads all of it, understands it, and then acts on it with unparalleled precision. You can ask it to upgrade your framework, optimize a specific component, or redesign an entire backend architecture — and it doesn’t blink. It just does it.
Add to that multi-file refactoring, which is handled intelligently without you needing to manually stage files or explain how everything is connected. Just describe the goal, and Claude intelligently does the wiring, making complex changes feel effortless.
The code it writes doesn’t feel “AI-generated.” It feels like code written by someone experienced — it follows the tone and patterns of your project, names things sensibly, and almost never makes you stop and think, “Wait, what is this supposed to be?”
For Pro users, you get 250 calls/month, billed at 2× credits — but for the sheer quality and effectiveness of Sonnet, that’s a deal that quickly pays for itself. Claude’s output is so effective that it drastically cuts out a ton of trial and error, which ultimately saves more time (and more credits) than even faster models that often need constant babysitting and manual correction.
Windsurf’s focus on enterprise-grade security and compliance (SOC 2 Type 2, FedRAMP High, HIPAA) enhances its value even more to make it a powerful solution for organizations seeking both efficiency and peace of mind.
This is all part of a major new string of updates from Windsurf, solidifying its position at the cutting edge of AI-powered development. With Claude 4 Sonnet now fully native, there’s truly no friction. No switching tabs, no key juggling, no API rate worries. Just open your editor and build.
And we haven’t even seen what happens if Opus 4 gets native access next.
This isn’t just a good update — it’s a massive leap forward for developer productivity and the future of coding. If you’ve been sleeping on Claude and Windsurf, now’s the time to wake up and ship.
You just need something that generates enough income for you to own all your time and do what you love and live freely.
For most people out there $10,000 monthly recurring revenue from a SaaS is gonna be a fantastic way to achieve this.
It can take serious dedication and effort but it’s a perfectly achievable goal.
You just the right idea that actually solves a problem for the right audience, and proper marketing.
Five proven strategies with real-world examples to help you uncover a profitable SaaS idea that has the potential to hit that $10K MRR mark:
1. Solve your own pain points (or those of your network)
Look inwards.
What frustrations do you encounter in your daily work or personal life? Are there repetitive tasks you wish could be automated?
This person built a simple SaaS tool to save a major problem they had as a marketer:
Is there a process in your daily life that’s unnecessarily complex?
How it works:
Personal Experience: Think about tools you use regularly. What are their shortcomings? What features are missing? Have you ever thought, “There has to be a better way to do this?” That “better way” could be your SaaS idea.
Professional Network: Talk to colleagues, friends, and contacts in different industries. Ask them about their biggest headaches and inefficiencies. Often, people outside of tech don’t realize their problems can be solved with software, creating a prime opportunity for you.
Why it leads to $10K MRR: If you experience a pain point, chances are others do too. Solving a problem you deeply understand gives you an inherent advantage in building a truly useful product and marketing it effectively. Niche down from your broad experience. For example, if you find popular analytics tools too complex, you can build niche web analytics tool for small businesses.
2. Deep dive into niche communities and forums
The internet is a goldmine of unmet needs and frustrations, especially within online communities. People are constantly discussing problems, asking for solutions, and venting about inadequate tools.
This solo software engineer got the crucial initial audience for their app just by posting on Reddit:
How it works:
Reddit, Facebook Groups, Industry Forums: Join subreddits, Facebook groups, and specialized forums related to specific industries or hobbies. Look for recurring questions, complaints, and discussions around “what software would help with X?” or “I’m tired of using Y for Z.”
Product Review Sites: Sites like G2 and Capterra offer insights into existing software solutions. Look at negative reviews and identify common pain points users experience with current offerings. This can reveal gaps in the market.
Why it leads to $10K MRR: These communities represent an audience with a shared, urgent problem. By observing their discussions, you can pinpoint specific pain points and tailor a solution directly to their needs. A micro-SaaS targeting a niche audience that genuinely needs your solution is often more successful than a broad tool trying to serve everyone.
3. Improve upon existing (but flawed) solutions
You don’t always need to invent something entirely new. Sometimes, the most profitable ideas come from taking an existing product and making it significantly better for a specific segment, or addressing its major flaws.
How it works:
Competitor Analysis: Identify successful SaaS products in various categories. Then, analyze their weaknesses. Are they too expensive? Too complex? Lacking a crucial feature? Do they serve a broad audience but miss the specific needs of a smaller, valuable niche?
“Niche Down” the Giants: Large SaaS companies often cater to a wide audience, which means they can’t perfectly serve every niche. You can build a more specialized, user-friendly, or cost-effective alternative for a particular segment. For example, instead of a general website builder, create one specifically for wedding photographers or local bakeries.
Why it leads to $10K MRR: Competition validates a market exists. By offering a superior experience or a more tailored solution to an existing demand, you can capture a portion of that market and quickly gain traction. Focus on solving one problem exceptionally well for a defined audience.
4. Leverage emerging technologies (especially AI)
Every now and then a major technology breakthrough happens that opens up a world of opportunity for new IT tools including apps and software.
It happened with the Internet, mobile and app store, and recently it’s been happening with AI.
Not only do you get to build AI-powered tools, you get use AI in your development and ship your MVP much faster.
How it works:
AI Integration: The rise of AI and machine learning presents immense opportunities. How can AI automate tedious tasks, provide predictive insights, or personalize experiences within a specific industry? Think about AI-powered content optimization tools, AI SEO generators, or AI for video creation.
No-Code/Low-Code Tools: The increasing accessibility of no-code and low-code platforms means you can build and test SaaS ideas much faster and with less technical expertise. This significantly lowers the barrier to entry and allows for rapid iteration.
Why it leads to $10K MRR: Early adoption of emerging technologies can give you a significant competitive advantage. If you can build a solution that leverages these advancements to provide unique value, you’ll be well-positioned to attract early adopters and grow quickly.
5. Look for manual workarounds and “frankenstein” solutions
When people are solving a problem using a combination of spreadsheets, manual processes, and disparate tools, it’s a strong indicator of an unmet need that software could address.
This is what drove the creation of tools like Notion and ClickUp
How it works:
Observe Inefficiencies: Pay attention to situations where businesses or individuals are using clunky, manual workarounds to accomplish a task. This could be anything from managing orders with paper slips to using multiple free tools to cobble together a “solution.”
Identify Integration Gaps: Are people manually transferring data between different software programs? Are they performing repetitive copy-pasting tasks? A SaaS that integrates these disparate workflows or automates data transfer can be incredibly valuable.
Why it leads to $10K MRR: These “Frankenstein” solutions highlight a painful problem for which people are already expending time, effort, or even money.
Your SaaS can offer a streamlined, efficient, and often more affordable alternative, providing clear ROI and a strong incentive for adoption.
Beyond the Idea: Validation is Key
Once you have an idea, the next crucial step is rigorous validation. Talk to at least 5-10 potential customers in your target niche. Ask them about their current workflow, their biggest challenges, and what they would pay for a solution.
Don’t just ask if they “like” your idea; ask if they would pay for it and how much. Pre-selling before you build can be a powerful way to validate demand and secure initial revenue.
By focusing on real problems, understanding your niche deeply, and validating your assumptions, you’ll significantly increase your chances of building a SaaS that not only serves its users but also generates a healthy $10,000 per month.
Google is getting dead serious about dev tooling — their new Firebase Studio is going to be absolutely insane for the future of software development.
A brand new IDE packed with incredible and free AI coding features to build full-stack apps faster than ever before.
Look at how it was intelligently prototyping my AI app with lightning speed — simply stunning.
AI is literally everywhere in Firebase Studio — right from the very start of even creating your project.
Lightning-fast cloud-based IDE
Genius agentic AI
Dangerous Firebase integration and instant deployment…
And it looks like they’re going with light theme this time.
Before even opening any project Gemini is there to instantly scaffold whatever you have in mind.
Firebase Studio uses Gemini 2.5 Flash — the thinking model that’s been seriously challenging Claude and Grok for some months now.
For free.
And you can choose among their most recent models — but only Gemini (sorry).
Although looks like there could be a workaround with the Custom model ID stuff.
For project creation there’s still dozens of templates to choose from — including no template at all.
Everything runs on the cloud in Firebase Studio.
No more wasting time setting up anything locally — build and preview and deploy right from your IDE.
Open up a project and loading happens instantly.
Because all the processing is no longer happening in a weak everyday PC — but now in a massively powerful data center with unbelievable speeds.
You can instantly preview every change in a live environment — Android emulators load instantly.
You’ll automatically get a link for every preview to make it easy to test and share your work before publishing.
The dangerous Firebase integration will be one of the biggest selling points of Firebase.
All the free, juicy, powerful Firebase services they’ve had for years — now here comes a home-grown IDE to tie them together in such a deadly way.
Authentication for managing users
Firestore for real-time databases
Cloud Storage for handling file uploads
Cloud Functions for server-side logic All of these are available directly from the Studio interface.
And that’s why deployment is literally one click away once you’re happy with your app.
Built-in Firebase Hosting integration to push your apps live to production or preview environments effortlessly.
Who is Firebase Studio great for?
Solo developers who want to quickly build and launch products
Teams prototyping new ideas
Hackathon participants
Educators teaching fullstack development
Anyone who wants a low-friction, high-speed way to build real-world apps
It especially shines for developers who already love Firebase but want a more integrated coding and deployment flow.
You can start using Firebase Studio by visiting firebase.studio. You’ll need a Google account. Once inside, you can create new projects, connect to existing Firebase apps, and start coding immediately. No downloads, no complex setup.
So this is definitely something to consider — you might start seeing local coding as old-school.
But whether you’re building your next startup or just hacking together a side project, Firebase Studio is an fast integrated way to bring your app to life.
This open-source coding agent is looking really promising.
Meet Roo Code: the incredible open-source alternative to GitHub Copilot and Cursor Composer…
Just look at how it effortlessly ran this app and fixed several errors in the code:
No monthly subscription like Windsurf and Copilot — pay only for what you use.
Multiple personalities/modes for every kind of coding task you do — Code Mode, Architect Mode…
A fully autonomous agent that lives inside your IDE — designed to think, plan, and build alongside you.
Understands your workspace, navigates your files, runs terminal commands, and can even automate browser tasks.
Your full-stack teammate to:
Pair program
Debug
Document
Architect your entire system based on your input.
Built by Roo Code Inc. — small but forward-thinking company focused on supercharging the creative and technical abilities of developers through AI autonomy.
Not just a coding assistant — a whole system
Roo Code operates on a flexible innovative multi-mode system:
Code Mode for hands-on coding tasks
Architect Mode for system-level thinking and planning
Ask Mode for direct Q&A or tool lookups
Debug Mode to trace bugs and propose fixes
Custom Modes for anything you define — QA, security audit, code review, etc.
Each mode is essentially a persona — and you can create as many as you like. Want a test-driven dev partner? A performance profiler? A security scanner? You can spin them up in seconds.
Total workspace awareness
Roo Code’s biggest advantage is its ability to see and act across your entire environment:
Reads and writes any file in your workspace
Executes terminal commands
Automates browser-based workflows
Interfaces with REST APIs and external tools via the Model Context Protocol (MCP)
If you can do it, Roo probably can too — and often faster.
💸 Pay-as-you-go pricing
Roo Code is free to install and use — but it runs on top of whatever AI model you connect it to.
That means the only cost is your API usage.
No subscriptions
No locked features
No hidden charges
You choose the model (OpenAI, Claude, Gemini, etc.) and only pay for the tokens consumed. Light users can spend less than a dollar a day, while heavy users running multi-step agents might spend more depending on the complexity and volume of tasks.
Roo even gives you real-time visibility into your context size and token usage, so you’re always in control.
This model keeps Roo Code accessible to indie devs, teams, and startups — scaling with you only when you need more power.
Extendable and interoperable
Roo Code plays well with others. Using services like Requesty, it can connect to 150+ different AI models with a single API key. You can load balance between providers or assign different models to different tasks.
Its extensibility also means you can connect Roo with tools like:
CodeRabbit for formal code reviews
MakeHub for model marketplace access
TimeWarp Flow for time-aware development
Roo Scheduler for recurring tasks
Roo Executor to trigger commands via URI
These plugins and forks turn Roo Code into an entire operating system for AI-assisted software development.
Open source & cloud friendly
Roo Code is completely free and open-source under Apache-2.0. You can run it locally, or use Roo Code Cloud to manage tasks, collaborate, and view history across projects. It’s not just a tool — it’s an ecosystem.
Installation is easy
Install the “Roo Code” extension from the VS Code Marketplace.
Connect your API key from OpenAI or another provider.
Start typing natural-language commands or invoke a mode. Roo does the rest.
You can also install forks like Kilo Code (Roo + Cline hybrid with built-in models) for even more features out of the box.
The future of development is agentic
We’re now fully in an era where developers won’t just write code — they’ll manage intelligent systems that write, test, and evolve code with them. Roo Code is one of the most advanced and developer-focused efforts in that direction.
Try it out
Install Roo Code in VS Code today and start working with an AI agent that feels like a real teammate. Explore it further at roocode.com or dive into the docs at docs.roocode.com.
