Vamsi Narla

A few years ago I developed EFQ, a prioritization framework for deciding what to build. It stands for Effort, Frequency, Quality risk. I’ve been applying it to automation and agentic builds. It translates directly. What is EFQ? EFQ is modeled on the ICE scoring approach where you score ideas to quantitatively determine which to pursue. The difference: all three factors come from the customer’s perspective, not yours. Effort — How much time does this task take the customer? Minutes = 1, hours = 3, a full day = 5. ...

As a leader of a portfolio of products and areas, director or VP, the breath and depth of what you lead and with the team size you lead it is important to have the right structure in place to support the team(s) and the business. While right team structures are not a guarantee to success getting this part wrong can definitely create obstacles towards success. Recently adopted this model framework and thought it’s worth sharing. ...

There’s something that happens when the microphone turns on. You’ve read the articles. Watched the videos. You “know” what to say. Then the interviewer asks “Tell me about yourself” and your mind goes blank. That’s the gap between knowing and doing. Between theory and pressure. Here’s what actually builds confidence Practice 1: Rambling. Forgetting half your points. Realizing reading about STAR method ≠ using STAR method. Practice 5: Starting to structure answers. Still second-guessing. But at least finishing thoughts. ...

This NPR episode on AI job interviewers had one finding that stopped me cold. When given a choice between a human interviewer or AI, 78% of candidates chose AI. The economist running the study said he was “quite shocked.” Here’s what they measured Candidates interviewed by AI: ✓ 12% more likely to get job offers ✓ 18% more likely to start and stay in the job ✓ Half as likely to report feeling discriminated against Why the better outcomes? The candidates performed differently. More interactive responses. Richer vocabulary. Fewer filler words like “um” and “uh-huh.” ...

I’ve been watching a quiet movement against subscription software. The cost of building new products is approaching zero. AI tools, no-code platforms, and cloud infrastructure mean a solo founder can ship production-grade software in weeks. Competition for every utility category is exploding. And something interesting is happening with pricing models. My frugality mindset made me seek out lifetime alternatives for tools I knew I’d need long-term. When you’re cost-conscious, you do the math: $15/month = $180/year. For a social posting tool, a screenshot tool, a voice dictation? ...

After a talk I gave at NewTech NorthWest, someone asked: “Why interview prep? Why this problem?” Fair question. There are a lot of problems to solve. I had 5-6 different ideas that were energizing to solve. So I pulled up Maslow’s hierarchy and started mapping where each would sit. Most products optimize for one or two levels. Fitness apps touch physiological needs and esteem. Social apps hit belonging. Then I looked at jobs and careers. ...

AI coding has 10x my ship velocity. I’ve crossed a threshold where the bottleneck isn’t writing code, it’s knowing what code to write. This changes my job to be a reviewer and architect, for the most part. The new skill: iterative interrogation until you reach the simplest working solution. Here’s what I’m seeing in practice An agent’s first solution typically optimizes for completeness. It builds the general case. New tables, abstraction layers, API endpoints—all “technically correct.” ...

I picked up work on Revarta’s organic traffic strategy in the last few days and got a solid reminder and learning on early product development. Here’s what I discovered while implementing a sustainable, cost-effective approach to content generation and keyword research. Effective SEO doesn’t require expensive tools or complex workflows — especially in the early stages. The Sophistication Trap I started by looking at the “standard” SEO toolkit. The reality hit quickly: quality SEO tools easily run $250+ per month just for data and insights, before you even think about content generation. For an early-stage product like Revarta, that’s a significant investment with uncertain returns. They also didn’t seem to get me all the way there and left the execution bits out. ...

After speaking with dozens of founders building AI-powered products, I’ve noticed a pattern. They’ll complain about model quality, debate between GPT-4 and Claude, or worry about hallucinations — but when I dig deeper, the real issue is simpler: they’re not controlling the temperature parameter. This single setting can dramatically change your results, yet most builders treat it as an afterthought or ignore it entirely. Understanding Temperature: The Technical Reality Temperature controls randomness in text generation. Here’s how it works: ...

It’s January. Everyone’s thinking about the “1% better every day = 37x improvement in a year” math. It’s inspiring. It’s also not how improvement actually works. The math assumes every gain stacks on the previous one. But most improvements don’t compound. They reset. You get better, then you lose the thread. You make progress, then you can’t tell what’s working. You ship something, learn nothing, and start over. James Clear said it well this week: “New goals don’t deliver new results. New lifestyles do.” ...