AI After Dark

Hunter Honnessy from Unlimited.ai

Alex Gras — Tue, 21 Apr 2026 07:33:40 -0700

Hunter Honnessy, CTO and Co-Founder at Unlimited.ai, gets into what defensibility actually looks like when anyone can vibe code a SaaS over a weekend. Conversation runs through building moats with data plus intelligence layers, why finance software doesn't have to suck, forward deployed engineering, where vibe coding leaves junior devs, a grounded take on AI fear mongering, and why 2026 is the year agentic workflows stop being primitive.

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0:00:00 Defensibility in an AI-native world
0:04:00 User delight and the wow factor as a moat
0:07:00 Who Unlimited serves and finance's legacy problem
0:11:00 Why business-minded CTOs ship faster
0:15:00 Monthly releases and cutting prototypes to hours
0:21:00 Forward deployed engineering and what keeps Hunter up at night
0:26:00 Vibe coding and the future of junior engineers
0:33:00 Painkillers vs vitamins and how Unlimited came together
0:39:00 Hiring cracked engineers and the Jim Simons lesson
0:45:00 AI as augmentation, not replacement
0:46:30 2026 as the year of agentic workflows
0:52:45 What's next for Hunter and Unlimited
0:57:00 AI fear mongering vs the good news nobody reports

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Gustavo Herrera from Knowme Global

Alex Gras — Tue, 07 Apr 2026 05:00:00 -0700

Alex Gras sits down with Gustavo Herrera, Founder and CTO of Knowme Global, to talk through why recruiting still sucks and how AI might actually fix it by doing the one thing everyone avoids, sitting down and talking to people for two hours. Gustavo breaks down why LLMs are just glorified averaging, how he picked Llama Index over LangChain by keeping it simple, and why the industry's obsession with automation is backwards when the hardest part is capturing who someone actually is. They dig into prompt versus context engineering, why philosophy matters more than people think, and how AI is forcing everyone back to the most human things we do.

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0:00 - Why Gustavo went back to school to learn AI for recruiting
4:30 - Choosing tech stacks and avoiding bleeding edge tools
9:15 - How Knowme ingests long-format interviews to build candidate profiles
14:45 - Prompt engineering versus context engineering
19:00 - Why LLMs will never be truly intelligent
24:20 - Philosophy's role in shaping AI and society
30:45 - How employers don't actually know what they want
36:15 - Speeding up the 42-day hiring process with AI interviews
42:00 - Why Knowme does the unscalable thing nobody wants to do
47:30 - Preventing AI from embellishing candidate answers
54:10 - Training interviewers to strike the right conversational tone
58:45 - When to use deterministic solutions versus agentic AI
1:01:40 - AI bringing us back to our humanity

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Bowden Kelly from Nutiliti

Alex Gras — Tue, 24 Mar 2026 05:00:00 -0700

Bowden Kelly from Nutiliti joins Alex on AI After Dark to explain why being a fast follower beats bleeding-edge adoption, particularly when your customers just want accurate utility bills paid on time and don't care about your tech stack. He breaks down why AI native companies often confuse magic demos with production reality, why replacing his entire engineering team with agents would be insane, and how the paradigm shift isn't about chat interfaces but building artifacts that make high school interns into experienced employees. The conversation reveals why Nutiliti spent years building PDF parsers only to discover LLMs weren't good enough yet, his controversial take that the agentic AI wave is overhyped, and how the hiring equation is flipping from one PM managing ten engineers to five PMs with two engineers because code execution is getting commoditized while business reasoning stays expensive.

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00:00 Fast follower versus bleeding edge adoption philosophy
07:38 Paradigm shifts from blockchain to mobile to AI
13:29 Tech debt concerns and why Google engineer stories mislead
21:10 Cloud Code improvements and managing context windows
28:04 MCP servers and the actual problem of data access
34:47 Why non-technical users aren't ready for AI interfaces
39:07 Building artifacts versus executing tasks as organizational design
46:17 High school intern analogy for training agentic AI
51:18 Controversial take on AI being overhyped despite being valuable
55:02 Hiring shift from programmers to business-minded builders
01;06;05 Fundraising strategy for non-unicorn companies
01;08;05 Why companies force AI into products for the story

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Matt Robillard from SmartAC

Alex Gras — Tue, 10 Mar 2026 05:00:00 -0700

Matt Robillard from SmartAC joins Alex on AI After Dark to explain why he walked into a company with product-market fit but antiquated tech stack and immediately started rewriting everything with AI at its core. He breaks down the difference between horizontal process automation that Service Titan can eventually replicate versus vertical intelligence modeling the actual thermodynamics of HVAC systems that nobody else can touch, why clean energy is magical thinking constrained by the Shockley-Queisser limit and Betz limit, and how hiring the best AI talent in HVAC meant recruiting from SpaceX, Databricks and Perplexity by selling real-world impact over another CRM with AI slapped on. The conversation reveals why OEMs surprisingly embrace their solution instead of fearing disruption, his controversial take that LLMs are stochastic parrots not true intelligence, and how the marginal cost of code going to zero is pure hype when production systems at scale still require senior engineers who deeply understand customer pain points.

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00:00 CES takeaways and hardware semiconductor relationships
01:53 Joining SmartAC post product-market fit with legacy tech
07:15 Data platform challenges and ML model development
12:14 Vertical AI defensibility versus horizontal automation
18:26 Alignment with Josh and commercial-product pairing
24:17 Replatforming effort and organizational design overhaul
29:27 Recruiting top AI talent from SpaceX and Databricks
36:03 Development velocity changes and junior engineer growth
41:01 AGI possibility and stochastic parrots debate
48:21 Controversial clean energy physics constraints opinion
56:42 Smart home promises and Tesla-style behavioral nudges
01;01;10 VC organizational design mistakes over two years
01;05;13 Who else should be on AI After Dark

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Akhil Mantripragada from Pie

Alex Gras — Tue, 24 Feb 2026 05:00:00 -0800

Akhil Mantripragada from Pie joins Alex on AI After Dark to trace his journey from coding without a computer in eighth grade India to building a $100M+ revenue AI-native marketing platform for SMBs. He shares how changing seven schools growing up forced him to become adaptable, why he spent hours writing multiple code versions on paper with only one hour per week at a computer lab, and how selling his first ed-tech company to UTSA funded grad school at Columbia. The conversation reveals why Pi's first three hires were designers instead of engineers, his controversial belief that chat is the "lousiest way to interact with AI," and how meeting users where they're at - not where you want them to be - became the core design philosophy that lets three engineers do what used to take thirty. Plus, the framework for building modular systems where perfection lies in the architecture's inputs and outputs, not the code inside the black box.

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00:00 Growing up moving between seven schools in India
01:39 Learning to code without a computer access
07:13 Starting an events management company as an introvert
12:18 The arrogance and humility combination that drives builders
15:12 First website job at UTSA and learning by doing
18:01 Building quantitative literacy tracking system for professors
24:17 Why school being too easy created entrepreneurial opportunities
26:45 Columbia grad school and starting Edu Link collaboration tool
35:14 The two acquisition experiences and MIT licensing lessons
40:56 Blockchain land registry in India and creator platform experiments
43:35 Why education will become skill-based not credit-based
46:15 Joining Toast's New Ventures program and building benchmarking
56:07 Recruiting A-players through bias for action and ownership
01;02;40 Why Pi hired three designers before the first engineer
01;06;54 Meeting users where they're at versus forcing chat interfaces
01;12;48 The black box modularity philosophy for AI-native startups

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Canisius Rozario from collide.

Alex Gras — Tue, 17 Feb 2026 18:56:26 -0800

In this kickoff to a new series, AI After Dark, Alex Gras (VC @ Mercury Fund) talks with Canisius Rozario (CTO @ Collide) about how he built a top-tier AI team in oil & gas without any industry background. It’s a sharp, candid look at hiring, learning fast, and building AI-first systems, packed with practical takeaways for founders, CTOs, and early builders working in high-stakes, data-heavy industries.

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0:00 Introduction and series kickoff
1:50 Canisius career background and journey through tech
9:30 Joining Collide and the decision to go AI-native
20:00 First 90 days as CTO and the "sniff test"
33:00 Why senior engineers beat junior hires in AI builds
37:00 Incorporating oil and gas experts into AI model training
41:45 The Forward Deploy Engineer model and how it works
46:00 Prioritization process for POCs and customer feedback
52:50 What to look for in the next generation of AI CTOs
56:30 What does "AI native" actually mean and audience Q&A

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