Tejas Saraiya
Gaurav Nemade
Building Trust, Scaling Solutions Engineering, and AI in Sales with Tejas Saraiya
In this episode of The Inventor Podcast, we sit down with Tejas Saraiya, a seasoned leader in solutions engineering, pre-sales, and go-to-market strategy. With leadership roles at Google, InVision, and UiPath, Tas has led large-scale solutions teams and navigated the complexities of scaling sales engineering, customer engagement, and AI-driven sales transformation.
We explore why trust is the foundation of solutions engineering, how AI is reshaping sales processes, and the crucial role of psychological safety in sales teams. Tas also shares insights into proactive pre-sales strategies, optimizing the product-feedback loop, and the future of AI-driven sales enablement.
This episode is packed with strategies and real-world lessons for sales engineers, pre-sales leaders, and go-to-market professionals looking to improve sales execution, build better customer relationships, and navigate the evolving world of AI-driven sales.
- How Tas scaled solutions teams at UiPath, InVision, and Google
- Why psychological safety is critical in sales and solutions engineering
- The biggest challenges pre-sales teams face and how to overcome them
- The importance of customer trust, credibility, and transparent communication
- How AI is transforming sales demos, sales enablement, and pre-sales workflows
- The role of proactive pre-sales strategy in increasing deal velocity
- How Inventive AI is revolutionizing RFP response automation and streamlining sales processes
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Key Highlights with Actionable Takeaways
1. The Foundation of Sales: Trust and Psychological Safety
Key Insight: Trust takes time to build but can be lost in an instant. Solutions engineers and sales teams must prioritize credibility and transparency to build long-term customer relationships.
Actionable Takeaway:
- Never fake an answer—if you don’t know, be honest and find out.
- Establish psychological safety within sales teams so they feel comfortable admitting knowledge gaps.
- Create a culture of transparency and accountability to foster internal and external trust.
2. Scaling Solutions Engineering: Challenges and Best Practices
Key Insight: As organizations scale, solutions engineering teams must transition from reactive to proactive roles, engaging earlier in the sales cycle and aligning closely with product teams.
Actionable Takeaway:
- Shift from reactive firefighting to proactive account planning by engaging early in deals.
- Align solutions engineering teams with product strategy and roadmaps to ensure consistency.
- Sales engineers should be deeply involved in customer onboarding and product adoption to ensure long-term success.
3. The Role of AI in Pre-Sales and Sales Enablement
Key Insight: AI is transforming the way sales teams demo products, respond to RFPs, and gather insights, but credibility and accuracy remain essential.
Actionable Takeaway:
- AI-powered tools can automate demo environments and improve real-time sales support.
- Use AI for knowledge retrieval during live sales conversations, but validate responses to maintain credibility.
- AI-driven forecasting can improve deal prioritization and risk assessment in the sales pipeline.
4. The Product-Feedback Loop: Why Solutions Engineers Play a Crucial Role
Key Insight: Solutions teams have a unique perspective on why deals are lost, yet many organizations fail to use this information effectively.
Actionable Takeaway:
- Implement structured processes for capturing and relaying product feedback from sales interactions.
- Establish regular feedback loops between solutions teams and product teams to ensure alignment.
- Leverage data from lost deals to improve future positioning and sales messaging.
5. The Future of AI-Driven Sales and Pre-Sales
Key Insight: AI is rapidly evolving, but organizations must balance automation with human expertise to maintain trust and credibility.
Actionable Takeaway:
- Sales teams must experiment with AI in low-risk areas first, such as internal knowledge management and proposal automation.
- AI should enhance sales teams, not replace them—the best results come from combining human expertise with AI insights.
- AI-driven tools must be monitored for accuracy and consistency to avoid eroding trust with customers.
Conclusion: The Road Ahead for Sales Teams
The sales and pre-sales landscape is changing rapidly, with AI and automation playing an increasingly important role. However, as Tas emphasized, trust, credibility, and strategic alignment will remain the foundation of successful sales teams.
The key takeaways for sales leaders and solutions engineers are clear:
- Proactively engage in deals and align with product teams to improve customer success.
- Use AI strategically to enhance efficiency, not as a substitute for human expertise.
- Maintain psychological safety and transparency to build long-term trust with customers and internal teams.
For organizations looking to optimize pre-sales, improve RFP response management, and streamline go-to-market strategies, the future lies in combining AI-driven automation with human-driven expertise.
