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This week’s guest is Harsha Gaddipati, founder & CEO of Slashy (YC S25) — a company building one of the most practical bridges between AI reasoning and execution. With Slashy, users can turn natural language prompts like “Summarize this call and send it to my team” into fully automated workflows across tools like Gmail, Notion, and Slack.
Before Slashy, Harsha worked across Georgia Tech Research, AWS, and State Farm, where he saw how much human energy was lost to low-value, repetitive tasks. That frustration became the spark behind Slashy — a platform designed to help AI not just think, but do.
“Reasoning without execution is just text. The real power of AI comes when it can actually act — not just plan.”
This episode is for builders, product leaders, and anyone exploring the next wave of agentic AI — where software stops waiting for input and starts working alongside you.
Highlights
Harsha’s journey from AWS engineer to YC founder
Why reasoning without action is wasted potential
Designing for dependability over novelty
What makes onboarding work in AI-native tools
Why automation should live where users already work
Building trust and reliability in high-speed YC culture
GTM experiments — from demo videos to whiteboard formats
Measuring activation and retention for AI-native products
Balancing product speed with correctness and execution
Future of agentic products and the road beyond SF
Takeaways
Execution is the missing layer. AI that only reasons still needs humans to finish the job.
Dependability beats novelty. Real stickiness comes from products that just work.
Context-native automation wins. Meet users in Gmail, Notion, or Slack — not new interfaces.
Speed with discipline. YC founders run weekly GTM experiments, but only ship what works.
Product is the real distribution. No marketing can replace the gravity of a product that delivers.
Timestamps
00:00 – Intro: Meet Harsha & the vision behind Slashy.ai
02:05 – Why reasoning without execution is just text
03:57 – Lessons from AWS: building for reliability and trust
05:05 – The interface gap in AI adoption
05:37 – Creating products users can’t live without
06:16 – Onboarding that unfolds naturally inside chat
07:07 – Identifying use cases worth doubling down on
07:41 – Activation metrics for AI-native products
08:15 – Why automation must embed in existing workflows
09:01 – Balancing speed with reliability and credibility
09:50 – YC GTM lessons: run weekly GTM experiments
10:42 – Product as the foundation of distribution
11:55 – What separates enduring AI products from hype
13:30 – Bringing agentic AI to non-technical markets
14:06 – Rapid Fire: correctness vs speed, favorite tools, closing thoughts
Further Reading
Want to go deeper? Explore related GTM Vault essays and frameworks:
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Connect
Follow Harsha Gaddipati: LinkedIn // Slashy
Follow Rick Koleta: LinkedIn // RiteGTM
Slashy gives AI its missing ingredient — hands.
This episode reminds us that GTM teams win when technology stops waiting for input — and starts acting on intent.
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