By Nidhi Desai
May 9, 2026
Updated May 11, 2026
About Author
Nidhi Desai
Director Of Engineering
She is an AI product builder and systems thinker. She designs agent architectures, obsessed over prompt engineering, and turns complex AI capabilities into things people actually use.
You already know what you're trying to figure out. Type it. Rocket handles everything after that.
Table of contents
How does vibe solutioning differ from vibe coding?
Can a small group really get the same results as a company with a research department?
What types of projects work best with Rocket.new?
Why do most initiatives involving AI stall, and how does Rocket.new help?
Most AI projects fail because teams skip research and build without a clear direction. Rocket.new combines Solve, Build, and Intelligence into one vibe solutioning platform that keeps research, development, and competitor tracking connected. Teams of any size can generate research-grade insights, build production-ready apps, and monitor competitors without needing a dedicated research department.
What happens when a group starts building an AI app without answering the right questions first?
Honestly, most of the time, the project dies. Over 80% of AI projects fail, and the root cause is almost never the technology. It is the thinking, or the lack of it, that kills the idea before it ships.
So why do some people still ship with confidence while others get stuck? The answer lives in their process, and where they do their thinking before they begin building.
Various sources and polls indicate that 8 out of 10 IT projects and implementations fail, which is likely similar for AI projects due to human factors and lack of preparedness.
The numbers are interesting, and honestly a bit alarming. RAND Corporation found that more than 80% of initiatives involving AI stall before reaching production. That is twice the rate of non-AI IT projects.
MIT's research adds another layer. 95% of generative AI pilots fail to scale, not because the models are broken, but because companies built generic wrappers that did not integrate into workflows or learn over time.
So the point is not that AI is bad. It is that most people skip the preparation that makes their AI tools and projects work. The work is only as good as the thinking before it.
AI tools allow small teams to automate repetitive research tasks, enabling scalability of insights without increasing headcount. But what happens when a group tries to run research, building, and competitive analysis across separate tools?
This fragmentation is the default for most people running projects. And it is worse than just inconvenient. It leads to real failures.
| Problem | What Happens With Separate Tools | What Happens With One Platform |
|---|---|---|
| Market research | Manual, scattered across tabs | Automated, structured output |
| Decision to stakeholders | Slide decks built from scratch | Ready-to-present briefs |
| Building the product | Re-explain the context to a new tool | Context carries forward |
| Competitor tracking | Quarterly manual checks | Continuous daily monitoring |
| Alignment across people |
The worse the fragmentation gets, the more time people spend re-explaining instead of building. Projects stall. Progress stalls. And the whole organization slows down.
Vibe coding changed how people think about building software. Andrej Karpathy coined the term in early 2025, and within months, Collins Dictionary named it Word of the Year. The core idea: describe what you want in natural language, and let AI write code for you. You skip the manual coding entirely. You focus on intent, not syntax.
Vibe solutioning takes that same philosophy and pushes it further upstream.
Rocket.new is the world's first vibe solutioning platform. It covers the full arc: from the first question to a live product to continuous competitive monitoring.
On one platform, solve, build, and track what your competition does next. Solve, Build, and Intelligence work together so your decisions carry forward instead of starting fresh every time you open a different app.
Vibe solutioning is not vibe coding with extra steps. It is the thinking layer that makes vibe coding actually work for real projects.
Now find out why do teams without a dedicated research function get the same intelligence as teams that have one on Rocket.new?
Many companies that want deep research either hire an analyst or pay for expensive consulting engagements. Smaller organizations cannot afford that. They figure it out on their own, which means slower decisions, weaker insights, and more guesswork. The default is to wing it.
Solve on Rocket.new changes this.
Here is what that looks like in practice:
This is how groups without a dedicated research function get the same quality of answered output as companies that have a full research department. The system handles the research. The people focus on decisions.
You can use Solve for anything: a new product direction, a GTM strategy, a regulatory question, or background for the call with a potential investor. Provide links to any relevant resources, and the answered brief comes back sharper. Every question answered, every number sourced.
Once the research is done, most people hit a wall. They take their findings, open a completely different tool, and begin building from zero. The insights they gathered do not transfer. The decisions they made live in a Google Doc somewhere. The context evaporates.
Rocket.new does not work that way.
Projects built with context ship faster and fail less often. The research feeds directly into what gets built, and that connection is the difference between a product that matches the market and one that misses completely.
AI allows people to work faster. Studies show 16% faster idea generation for individuals and 13% faster for groups when AI handles repetitive research tasks. But speed without direction makes things worse. Context gives that direction.
Vibe coding has earned its place. Y Combinator reported that 25% of its Winter 2025 batch had codebases that were 95% AI-generated. Google's Sundar Pichai said over 30% of new code at Google comes from AI. Code generation at this scale is real, and the results speak for themselves.
But vibe coding alone does not solve the research problem.
Rocket.new connects both. You begin with vibe solutioning to figure out the right thing to build. Then you push into vibe coding where Rocket generates deployment-ready output in Flutter for mobile apps or Next.js for web apps. Rocket already understands the requirements because the research answered those questions first.
Vibe coding is the engine. Vibe solutioning is the capability that tells the engine where to go.
The shift toward AI-powered research for smaller organizations is not just theory. People building real companies post about it constantly.
"AI creates 'superagency,' the ability for individuals to punch far above their weight."- Reid Hoffman, LinkedIn Co-Founder, from Superagency (2025)
Hoffman's point matches what happens on Rocket.new every day. People in groups of two or three use the research layer to do market analysis that used to require a full-time dedicated analyst. They push that research into Build and ship polished web apps and mobile apps in days. Then they watch what competitors do next through the Intelligence tab, so they stay prepared without manual monitoring.
The gap between large and small organizations is closing. And the companies that close it fastest are the ones using a vibe solutioning platform where research, building, and tracking live together.
This is the core question answered. Because Rocket replaces the research function with a system that does the same work, faster, and keeps the results connected to everything that comes after.
Here is what Rocket brings to every user:
So here are use cases that connect research to building directly:
Put Rocket to work for your next project. You do not need a research hire to get research-grade insight.
One thing that makes Rocket different from using separate tools: the work accumulates and gets sharper over time.
This is how continuous monitoring works in practice. Instead of running a quarterly competitive review (which is already outdated by the time you present it), the platform provides daily strategic briefs. Competitor repositioned? Changed pricing? Shipped a new feature? You know about it the same day. The questions your stakeholders raise get answered before the next meeting.
High collective performance depends more on group dynamics and equal participation than on individual talent. Rocket's shared context makes sure every user and every collaborator has access to the same information, regardless of role. That changes how people inside the system make decisions together and helps everyone understand the full picture.
Why do teams without a dedicated research function get the same intelligence as teams that have one on Rocket.new?
Because the gap was never about headcount. It was about having a platform that connects research to building to tracking in one workflow.
Rocket.new closes that gap for any group, at any size, from the first idea to post-launch monitoring. The people who figure this out early will ship faster, build products that match their market, and stay ahead of competitors who are still juggling separate tools and losing context with every handoff.
Start your next AI project with Rocket.new and turn research, building, and competitive intelligence into one continuous workflow.
| Meetings to re-sync lost links |
| Everyone works from one workspace |
| Context loss | High, gets worse over time | None, the platform remembers |