DEV Community: UsamaKashif

I Shut Down My Startup After 100 Waitlist Signups. Here's What I Learned

UsamaKashif — Thu, 13 Aug 2026 15:06:06 +0000

I am shutting down Ravah, a startup I spent months designing, building, and trying to grow.

About 100 people joined the waitlist. Founders understood the problem. The product kept improving, and the vision became more ambitious.

But the evidence did not grow with it.

I had validated interest. I had not validated repeated use, willingness to pay, or product-market fit.

That distinction is the main reason I am closing Ravah.

TL;DR

A waitlist proves that your promise is interesting, not that your product is needed.
Shipping more features can look like progress while customer evidence remains unchanged.
Define the behavior that will validate a feature before building it.
Startups need explicit co-founder responsibilities and decision rights early.
When the roadmap grows faster than customer evidence, it is time to narrow, pivot, pause, or stop.

What I was trying to build

Ravah began with a focused idea.

Founders constantly create material worth sharing: product releases, customer lessons, pricing decisions, onboarding changes, mistakes, and milestones. Most of it never becomes useful content because converting product work into posts takes time and context.

I wanted Ravah to understand a product once, remember its audience and voice, and turn real product activity into useful content for channels such as LinkedIn and X.

The early response was encouraging. Around 100 people joined the waitlist, many after I shared the idea on Reddit. People requested access and told me they understood the problem.

At the time, that felt like validation.

It was—but only of the top of the funnel.

How a focused product became a platform

The first version generated content for founders.

Then the scope started expanding:

content generation
  -> coordinated campaigns
  -> product-aware growth
  -> Reddit and community distribution
  -> website, changelog, docs, and GitHub integrations
  -> scheduling and analytics

Each step made sense on its own.

If Ravah understood a product, why shouldn't it create a campaign? If it could create the content, why shouldn't it distribute it? If it distributed the content, why shouldn't it measure the results?

On paper, every version sounded better than the previous one.

That was the trap.

I kept asking:

What could Ravah become?

I should have been asking:

What narrow part of Ravah do people need badly enough to use repeatedly and pay for?

The first question creates a roadmap. The second creates evidence.

Building became a comfortable place to hide

As a developer, I know how to make progress visible.

I can improve onboarding, redesign a dashboard, tune a prompt, change a model, fix an edge case, or add an integration. Code gets committed. Screens change. Tasks move to “done.”

Customer validation is less comfortable.

It can produce ambiguous feedback. It can show that the feature you want to build is not important. It can force you to challenge the story you have been telling yourself about the product.

So I kept building.

The work was real, but I was using it to delay the harder business question:

Do enough people care enough to keep using this?

This is a dangerous failure mode for technical founders. Because we can build the next feature, building it feels like the responsible next step.

Sometimes it is just the most familiar next step.

The validation ladder I use now

Not all positive signals mean the same thing.

Signal	What it actually proves
Someone likes the idea	The promise is understandable
Someone joins the waitlist	They will exchange contact information for possible value
Someone completes onboarding	The promise created enough curiosity to try the product
Someone returns	The product may solve a recurring problem
Someone recommends it	The value is strong enough to attach their reputation to it
Someone pays and keeps paying	The product may be important enough to support a business

A waitlist is useful. It gives you a group of people to interview and observe.

It does not complete product validation.

Ravah’s 100 signups told me to investigate further. I treated them as permission to expand.

A practical rule before building the next feature

I now want every meaningful feature to begin with five written fields:

Hypothesis: What do I believe users need?
Behavior: What will users do if I am right?
Threshold: How much of that behavior is enough?
Deadline: When will I evaluate the result?
Decision: What will I do if the evidence is weak?

For example:

Hypothesis: Founders need product updates converted into social posts.
Behavior: They return after the first output and generate from a second update.
Threshold: 5 of 10 active testers return within 14 days.
Deadline: Two weeks after onboarding.
Decision: Interview non-returning users before expanding the workflow.

This does not make product decisions perfectly objective. It makes it harder to redefine success after seeing the results.

Without a predefined signal, almost any feedback can become a reason to keep building.

The co-founder lesson

I started Ravah with a co-founder. We later disagreed and went our separate ways.

The important lesson is not that co-founders should never disagree. The mistake was that we did not define enough at the beginning.

Before building together, co-founders should explicitly answer:

Who owns product, engineering, growth, and operations?
What result is each person accountable for?
What level of contribution is expected?
How will disagreements be resolved?
Who has the final decision in each area?

These conversations can feel overly formal when everyone is excited.

That is exactly when they are easiest to have.

Clear roles do not make one founder more important. They prevent ambiguity from becoming an invisible third founder.

How I knew it was time to shut down

There is no universal metric that tells you when to shut down a startup.

For me, the clearest signal was the pattern of work:

I could explain the next feature more clearly than the retention behavior that justified it.
The product kept generating new versions of the vision, but not stronger evidence of recurring need.
Building another version was easier than staying with one narrow customer problem.

I still believe several ideas inside Ravah are valuable. AI products improve when they understand real product context. Founders do have useful stories hidden in their everyday work. Distribution is still difficult for small teams.

But believing in a thesis is not the same as having a product people need.

I could rebuild Ravah for another year and always imagine that the next version would be the one.

Closing it means choosing the available evidence over the imagined version.

The operating rules I am taking forward

Ravah changed how I intend to build future products:

Start with a narrower promise. Prove one recurring need before designing the platform around it.
Define evidence before features. Decide which user behavior would justify more investment.
Treat interest as the beginning of validation. A signup creates an opportunity to learn, not proof of product-market fit.
Stay with the problem longer. Understand its frequency, alternatives, and consequences before expanding the solution.
Make ownership explicit. Important areas need a responsible person and a decision process.
Schedule reassessment points. Regularly ask whether evidence or only the roadmap is growing.

The lesson is not to stop building ambitious products.

It is to make ambition earn its way into the product.

Frequently asked questions

Does a waitlist prove product-market fit?

No. A waitlist validates interest in a problem or promise. Product-market fit requires stronger behavior, including activation, repeated use, recommendations, and sustained willingness to pay.

How do you know when to shut down a startup?

There is no universal threshold. In my case, continued development was producing a larger vision without stronger evidence of recurring customer need. That pattern told me it was time to stop and redirect my effort.

Should technical founders stop building features?

No. Building is necessary, but every major feature should test a specific assumption. If you cannot describe the behavior that would validate the feature, more customer research may be a better next step than more code.

What I am building now

Closing Ravah does not mean I am done building.

I am currently working on focused products including CookThis, an AI cooking app that turns food photos and ingredients into practical recipes, and ScrollStop, an Android app blocker for protecting study, work, exam, and sleep sessions.

I am also open to selected contract work involving product engineering, frontend development, UX-focused implementation, and practical AI integrations.

Ravah failed to become the business I wanted it to become.

But it taught me the difference between shipping software and proving a business.

It also made me a better founder.

What signal do you use to distinguish product progress from engineering progress?

How to Create Action Items from Feedback Without Wasting Time

UsamaKashif — Mon, 11 Aug 2025 09:20:00 +0000

Transform raw feedback into meaningful tasks quickly with our proven 6-step framework that eliminates manual processing and speeds up your product cycles.

The Feedback-to-Action Gap Is Killing Your Productivity

Does this sound familiar? Your team just wrapped up a productive customer feedback session, everyone nodded enthusiastically during the meeting, notes were taken... and two weeks later, nothing has actually happened with those insights. You're not alone. According to a recent ProductPlan survey, teams spend an average of 6.5 hours per week processing feedback, yet 76% of that feedback never becomes actionable work.

The gap between collecting feedback and turning it into concrete action items is one of the most expensive inefficiencies in modern product development. Teams lose an estimated 20 days per year in "feedback limbo" — that wasteful period between receiving valuable input and actually doing something about it (Source: Productboard Research).

Why Most Feedback Never Becomes Action

The journey from raw feedback to prioritized action items is fraught with obstacles:

Feedback fragmentation: Critical insights are scattered across meeting notes, email threads, Slack channels, and support tickets
Context loss: The original nuance and urgency get diluted as feedback passes between team members
Manual processing: Someone has to manually translate vague comments into specific tasks
Prioritization paralysis: Without clear criteria, teams struggle to determine which feedback deserves immediate action

The True Cost of Slow Feedback Processing

The impact goes far beyond wasted time:

Market opportunity loss: While you're slowly processing feedback, competitors are responding to similar customer needs
Customer frustration: When customers don't see their feedback implemented, they assume you don't value their input
Team demoralization: Product teams feel perpetually behind when feedback piles up faster than they can address it
Decision fatigue: Constantly triaging unstructured feedback depletes your team's decision-making energy

Transform Your Feedback-to-Action Pipeline

Converting feedback into meaningful action doesn't have to be a manual, time-consuming process. The solution is creating a streamlined system that makes the transition from raw input to assigned tasks nearly automatic. Komentiq was designed specifically to solve this feedback-to-action gap by providing a structured pipeline for processing insights.

How Komentiq Streamlines the Feedback-to-Action Process

Universal collector that captures feedback from any source—Slack, email, Zendesk, user interviews, and more
Sentiment analysis and categorization that automatically organizes feedback by theme, urgency, and customer segment
AI-powered task generation that converts raw feedback into properly formatted user stories or work items
Priority scoring based on customer impact, frequency, and strategic alignment
Direct integration with task management tools like Jira, Asana, and Trello

6 Steps to Create Action Items from Feedback At Lightning Speed

Whether you're using a dedicated tool like Komentiq or building your own process, these steps will help you convert feedback into action faster:

1. Create a Single Feedback Collection Point

The first step to efficient feedback processing is consolidation. You can't act on what you can't see.

Create a designated feedback inbox that team members can forward customer insights to
Set up automation rules to pull feedback from support tickets, NPS surveys, and user testing sessions
Establish a consistent format for feedback collection to minimize preprocessing time

Pro tip: Even a simple shared spreadsheet is better than scattered feedback. The key is ensuring all team members know where to deposit insights.

2. Categorize and Tag Immediately

Don't wait to organize feedback—do it at the collection point to prevent backlog buildup.

Create a standardized tagging system for product areas, feature requests, bugs, and enhancements
Tag feedback by source importance (e.g., enterprise customer vs. free user)
Add contextual markers like "quick win" or "strategic opportunity"

3. Apply a Consistent Framework for Task Creation

Transform vague feedback into specific, actionable tasks using a consistent framework:

User story format: "As a [user type], I want [goal] so that [benefit]"
Job-to-be-done framework: "When [situation], I want to [motivation], so I can [expected outcome]"
Issue structure: "[Problem] is causing [impact]. Fixing it would [benefit]"

Pro tip: Create templates for different feedback types to ensure consistent task creation regardless of who processes the feedback.

4. Implement the "Touch Once" Principle

The efficiency killer in feedback processing is revisiting the same input multiple times. Instead:

Process each piece of feedback completely the first time you review it
Make an immediate decision: convert to task, archive, or escalate
Set clear criteria for what feedback deserves immediate action versus what can wait

Pro tip: Schedule dedicated feedback processing time blocks instead of constantly switching between feedback review and other work.

5. Automate the Connection to Your Task Management System

Manual copy-pasting between systems creates friction that slows down your feedback-to-action pipeline.

Use integrations to automatically push created tasks to your project management tool
Ensure crucial context transfers along with the basic task description
Maintain bidirectional links so status updates flow back to the feedback source

6. Close the Feedback Loop

The feedback-to-action cycle isn't complete until you inform stakeholders about what happened with their input.

Send automated status updates when feedback becomes a task
Notify contributors when their suggested improvements launch
Share aggregate insights about how feedback is shaping your roadmap

Pro tip: Closing the feedback loop dramatically increases the quality and quantity of future feedback, creating a virtuous cycle of improvement.

From Feedback Backlog to Action Machine

Converting feedback into action items doesn't have to be your team's bottleneck. By implementing the right processes and tools, you can transform from a team drowning in unprocessed insights to one that quickly distills customer feedback into meaningful improvements.

The most successful teams don't just collect more feedback—they process it more efficiently. With a streamlined feedback-to-action pipeline, you can respond to customer needs faster, build more impactful features, and create a product that truly reflects what your users want.

Ready to transform how your team handles the feedback-to-action process? Try Komentiq free and experience how much faster your team can move when the path from insight to action is automated.

Key Takeaways

Teams waste up to 20 days per year in "feedback limbo" between collecting insights and taking action
A structured feedback-to-action pipeline can reduce processing time by up to 80%
Consolidation, immediate categorization, and consistent formatting are essential for efficient feedback processing
The "touch once" principle prevents feedback from being repeatedly reviewed without action
Automation between feedback collection and task management systems eliminates manual transfer friction
Closing the feedback loop with stakeholders increases future feedback quality and quantity

Looking to speed up your design feedback even more? Try Komentiq to streamline your feedback, collaborate better, and iterate faster.

How to Turn Figma Feedback into Action Without Losing Your Mind

UsamaKashif — Sun, 10 Aug 2025 17:40:31 +0000

Transform chaotic design reviews into streamlined workflows with Komentiq's Figma integration

Learn how to cut feedback cycles by 60%, automate task creation from comments, and keep your design team focused on creating, not managing feedback.

Introduction: The Figma Feedback Paradox

How many hours has your design team lost this month deciphering conflicting feedback scattered across Slack threads, Zoom calls, and endless comment chains in Figma files? What begins as a simple design review quickly descends into a labyrinth of opinions without resolution.

According to the Design Process Efficiency Report 2025, design teams lose a staggering 26 working days per year navigating disjointed feedback loops. That's over a month of productivity evaporating into the digital ether.

The disconnect is clear: Figma revolutionized design creation but left a gap in feedback management. Teams need a way to transform scattered comments into structured actions without the mental overhead.

That's exactly why we built Komentiq's Figma integration - to create the missing link between brilliant design work and swift, decisive action.

The Problem: When Design Feedback Becomes Quicksand

The Invisible Productivity Killer in Design Reviews

Design tools like Figma excel at creative collaboration, but when it comes to structured feedback collection and implementation, most teams are still stuck in the dark ages:

Important comments get buried under layers of iterations and versions
Critical feedback fragments across Figma, Slack, email, and meeting notes
Design decisions lack clear ownership and accountability
The context behind feedback gets lost in translation

The result? Decision paralysis, implementation delays, and talented designers spending more time as feedback archaeologists than creators.

The Measurable Impact of Fractured Feedback

This broken feedback loop isn't just frustrating—it's expensive:

Product launch delays of 2-4 weeks per major feature
40% increase in unnecessary sync meetings just to clarify comments
Decision fatigue leading to 3x higher revision cycles
Critical stakeholder insights falling through the cracks

In a recent survey of design teams, 82% reported that feedback management—not the design work itself—was their biggest source of timeline slippage.

The Solution: Feedback That Flows Into Action

Introducing Komentiq's Seamless Figma Integration

Komentiq now transforms the way design teams handle feedback with our native Figma integration. The process couldn't be simpler:

Simple Integration Process:

Paste any Figma file URL into Komentiq
Select specific frames or entire pages that need feedback
Watch as Komentiq automatically:
1. Imports existing comments directly from Figma
2. Creates a centralized feedback hub for additional input
3. Generates AI-powered action items from conversation threads
4. Maps feedback to specific design elements with visual context

Actionable Steps: Implement the Perfect Design Feedback Loop

1. Centralize All Design Feedback in One Source of Truth

The Context Principle

Design feedback without context is nearly worthless. Komentiq preserves the visual relationship between comments and design elements, eliminating the "which version were we talking about?" problem.

Implementation Strategy

Connect your Figma workspace to Komentiq in under a minute. Once linked, all team members can view and contribute to feedback without switching between tools.

2. Curate What Needs Review

The Focus Method

Design reviews frequently suffer from scope creep. By selecting only specific frames for feedback, you focus attention on what matters most in the current iteration.

Implementation Strategy

Use Komentiq's frame selection tool to highlight exactly which designs need attention, reducing cognitive load on reviewers and increasing the quality of feedback.

3. Transform Comments into Action with AI

The Automation Advantage

The biggest gap in most design processes is the manual effort required to translate abstract feedback into concrete tasks.

Implementation Strategy

Activate Komentiq's AI assistant to analyze feedback threads and automatically generate suggested action items, cutting the feedback-to-task conversion time by up to 70%.

Conclusion: From Feedback Chaos to Design Flow

The difference between good design teams and great ones isn't just talent—it's process. When feedback flows seamlessly from insight to implementation, iteration cycles accelerate, quality improves, and team burnout disappears.

Komentiq's Figma integration bridges the gap between creative collaboration and structured execution, transforming the most painful part of the design process into a competitive advantage.

Ready to cut your design feedback cycle time in half while improving output quality? Try Komentiq's Figma integration free for 14 days and experience the difference a streamlined feedback loop makes.

Start For Free →

Key Takeaways

Design teams lose 26 working days yearly to inefficient feedback processes
Komentiq's Figma integration creates a bidirectional sync between design files and actionable tasks
AI-powered task generation converts vague feedback into clear action items automatically
Smart feedback classification helps teams prioritize what matters most
Structured ownership and verification close the feedback loop completely

Looking to speed up your design feedback even more? Try Komentiq to streamline your feedback, collaborate better, and iterate faster.

Komentiq: Revolutionizing Design Feedback with AI-Powered Solutions

UsamaKashif — Tue, 08 Apr 2025 20:38:10 +0000

In the fast-paced world of design, effective feedback is crucial for refining ideas and delivering exceptional results. However, traditional feedback methods often fall short, leading to miscommunications, delays, and subpar outcomes. Enter Komentiq, an innovative platform poised to transform the design feedback landscape through the power of Artificial Intelligence (AI).

The Challenge of Traditional Design Feedback

Navigating design feedback can be cumbersome:

Disjointed Communication: Feedback dispersed across emails, chats, and documents complicates tracking and implementation.
Ambiguity: Vague comments like "Make it pop" lack actionable clarity.
Time Delays: Waiting for consolidated feedback from multiple stakeholders can stall project momentum.

Komentiq's AI-Driven Solution

Komentiq addresses these issues with:

Centralized Feedback Hub: A unified platform where all design feedback is collected and organized, ensuring clarity and accessibility.
AI-Powered Insights: Utilizing artificial intelligence, Komentiq offers actionable suggestions, enhancing the quality and efficiency of design revisions.
Real-Time Collaboration: Team members can provide and view feedback instantly, fostering seamless communication and swift decision-making.

Upcoming AI Features

Komentiq is set to introduce advanced AI capabilities:

Predictive Feedback: Anticipates potential design issues before they arise, allowing proactive adjustments.
Automated Recommendations: Suggests design improvements based on industry best practices and current trends.

Join the Komentiq Waitlist

Be among the first to experience Komentiq's innovative features by joining our waitlist. Early access members will receive exclusive benefits and have the opportunity to shape the platform with their feedback.

Embrace the future of design collaboration with Komentiq—where AI meets creativity.

Todo List App

UsamaKashif — Sat, 07 May 2022 13:34:05 +0000

Overview of My Submission

This is a TodoList webapp. The frontend is made with tailwind CSS, Next JS. Appwrite is used for the backend

Submission Category:

Web2 Wizards

Link to Code

UsamaKashif / appwrite-todolist

TodoList app made with Next Js and appwrite.

The frontend is made with Tailwind css and Next JS. Appwrite is used for the backend

Features

Authentication
Adding Todos
Deleting Todos
Updating the complete state of Todo
Deleting Account

Screenshots

View on GitHub

Additional Resources / Info

StudenTutor.online

UsamaKashif — Wed, 20 Jan 2021 10:11:28 +0000

Open Sourced my website which I started back in May 2020. StudenTutor.online is a platform for students and tutors to connect together.
This website is made using Python and Django.

Feel free to contribute to this repository, and if you find the work interesting don’t forget to leave a star.

Github repo: https://github.com/UsamaKashif/studentutor
Live Website: https://studentutor.online/
Facebook Page: https://www.facebook.com/StudenTutorOfficial
Discord: https://discord.gg/kp6BEETp
Medium Story: https://usamakashif1.medium.com/studentutor-online-b7730ab4c660