Most people watching AI reshape the workplace fall into one of two camps: the ones selling fear, and the ones selling hype. Aditya Kachave picked a third, much harder path. He treated it as an engineering problem. Millions of capable professionals were about to be technically outdated through no fault of their own, and almost nobody was building the actual fix. So in 2021, an IIT Kharagpur graduate who had already built two eight-figure companies decided to build one more, except this time, the product wasn’t software. It was a way for ordinary working people to not get left behind.
That decision became be10x. This is the story of the problem he saw before anyone else was calling it a problem, and what he actually did about it.
The Moment the Problem Became Undeniable
Every founder story has an inciting moment. For Kachave and co-founder Aditya Goenka, it wasn’t a single dramatic event, it was a pattern they kept running into. Professionals across finance, marketing, and operations kept describing the same feeling: they knew AI was coming for parts of their job, they’d tried a free tutorial or two, and none of it actually changed what they did at their desk on Monday morning. The tools existed. The instructions didn’t.
At the time, the available options split into two useless extremes: academic AI courses built for people who wanted to become data scientists, and thin AI hype content that generated anxiety without giving anyone a next step. Nobody was building the thing in between, practical, job-specific, beginner-friendly AI training that assumed nothing except that you had a job you wanted to keep and grow. Kachave built that instead.
Why this matters: identifying the right problem is usually harder than solving it. Kachave’s real early insight wasn’t “AI is important”, everyone knew that by 2021. It was noticing that the actual bottleneck was translation, from AI capability to job-specific application, and building specifically for that gap.
The Villain Wasn’t AI. It Was the Skills Gap.
Kachave has been consistent and specific about this distinction in a way that separates his message from most AI commentary: AI itself was never framed as the enemy. His often-repeated line, that AI won’t take your job but someone who knows how to use AI well might, reframes the entire threat. It’s not a machine replacing you. It’s a colleague who learned six months before you did.
That reframing matters because it changes what the solution has to look like. If AI is the villain, the only response is fear or resistance. If the skills gap is the villain, the response is training, specific, fast, and accessible enough that the gap actually closes instead of just being discussed. Every design decision at be10x traces back to that second framing: live workshops instead of theory, real work tasks instead of toy examples, and pricing low enough that cost was never the excuse for staying behind.
Actionable takeaway: If you’ve been treating “AI might replace me” as a reason to freeze, try reframing it the way Kachave does: it’s not AI you’re competing with, it’s the version of your peers who already learned to use it well. That’s a solvable gap.
Proof the Fix Actually Works, One Person at a Time
A hero narrative is only as good as its evidence, and Kachave’s clearest evidence isn’t a company milestone, it’s what happened to individual people who were genuinely stuck. A professional who had just been laid off completed a be10x workshop, built fluency with tools like NotebookLM, and had two job offers above ₹20 lakh per annum within a month, a turnaround that would have been unimaginable through the traditional job-search timeline most laid-off professionals face.
An operations manager who’d spent ten years in the same kind of role, quietly assuming leadership positions weren’t for him, went through be10x’s Advanced AI Careers Accelerator Program and came out the other side with a 60% lighter reporting workload and, for the first time, the confidence to apply for roles he’d been avoiding. A school teacher in Kerala who wandered into a workshop out of curiosity, not ambition, ended up transforming how he prepared lessons entirely, using AI to build quizzes and lesson plans that used to eat his evenings.
None of these are hypothetical case studies written for a landing page. They’re the specific, textured outcomes of one founder’s decision to build the thing that was actually missing, over and over again, for people who had almost nowhere else to turn.
Actionable takeaway: The test of whether an AI training program is solving a real problem isn’t the size of its enrollment number. It’s whether you can point to a specific person whose specific week changed because of it.
Refusing to Let the Fix Become Exclusive
Solving a real problem for a small, well-resourced group is one kind of achievement. Kachave made a different, harder choice: insisting the fix be affordable enough to reach the people with the least room for error. be10x’s introductory workshop has been offered for as little as ₹9, a price that makes clear the point was never maximum extraction, it was maximum reach. A teacher in Kerala, an operations manager anxious about being replaced, a professional job-hunting after a layoff, none of them were priced out of the solution.
That choice is easy to overlook next to the more dramatic before-and-after stories, but it’s arguably the more important one. A hero who solves the problem only for people who can already afford the fix hasn’t really solved it. Kachave built the model so the fix could reach the people who needed it most, not just the people who could pay the most.
Actionable takeaway: When judging whether any company genuinely wants to solve a stated problem, check whether their pricing and access decisions match that stated mission, or contradict it.
The Problem Isn’t Solved Once. It Has to Keep Being Solved.
The most recent chapter of this story is less dramatic but arguably more telling. Kachave hasn’t treated be10x as a finished product. As AI tools multiplied and workflows kept shifting through 2026, be10x’s own content shifted with them, breaking down emerging shifts like the Model Context Protocol standard connecting AI agents to external tools, and pushing learners who thought they already “knew AI” to look again at how much of a platform like Claude they were actually using.
That’s the quieter, less cinematic part of being a genuine problem-solver: the willingness to keep re-solving the same problem as it changes shape, instead of declaring victory once the first version works.
Actionable takeaway: Treat your own AI skills the same way. The training that mattered a year ago may already be incomplete. Re-check your workflows against what’s changed, not what you learned once.
Final Takeaway
There’s no single dramatic rescue in this story, no headline moment where Aditya Kachave saved a company or a country from AI disruption single-handedly. What there is instead is a founder who correctly identified a real, underserved problem, the gap between AI’s potential and ordinary people’s ability to actually use it, and then built, priced, and kept rebuilding a solution to close that gap for as many people as possible. Multiply that across a laid-off professional’s two job offers, an operations manager’s reclaimed confidence, and a teacher’s rebuilt evenings, and the “hero” framing stops being a marketing metaphor. It’s just an accurate description of what solving a real problem, repeatedly, at scale, actually looks like.
Frequently Asked Questions
What specific problem did Aditya Kachave set out to solve?
The gap between AI’s growing capability and most professionals’ ability to apply it directly to their own jobs, at a time when academic AI courses and generic hype content both failed to close that gap.
How is Kachave’s approach different from typical AI fear-based messaging?
He frames the real competitor as the skills gap, not AI itself, arguing that AI won’t replace people, but people who’ve learned to use it well will outperform those who haven’t.
What evidence supports that be10x’s approach actually works?
Documented individual outcomes, including a laid-off professional receiving two job offers above ₹20 LPA within a month of training, and an operations manager reporting a 60% workload reduction after completing an advanced program.
Why does be10x’s pricing matter to this story?
Pricing the introductory workshop as low as ₹9 reflects a deliberate choice to prioritize reach over maximum revenue extraction, ensuring the people most affected by the skills gap weren’t priced out of the solution.
