Work happens across Slack, Notion, Linear, GitHub, meetings, and the desktop. The problem is not a lack of tools. It is the context lost between them.

In this episode, Nik Singh sits down with Parris Khachi to explore Highlight's approach to proactive workplace AI. Parris explains why the next AI interface may not be a chat box and how Highlight uses screen, meeting, and integration context to make assistance more proactive.

The conversation also covers privacy and user control, individual versus team context, model economics, product-led adoption, competition with incumbents, and why teams should automate coordination without outsourcing judgment.

Highlight AI: https://highlightai.com/
Parris Khachi: https://www.linkedin.com/in/parris-k-7928b011/
Terminal Value: https://www.youtube.com/@Terminal-Value-Podcast

Chapters
00:00 Cold open
00:56 Introduction
01:31 Where context gets lost across work tools
05:03 Highlight's mission and the coordination tax
06:04 The AI intern that follows the work
13:01 Screen context, privacy, and user control
18:18 Choosing models across capability, speed, and cost
21:43 Ideal users, deployment, and adoption
27:28 How AI could change team structure
29:32 Competition and the interface after chat
33:51 Highlight's long-term vision
36:10 Closing takeaways

Disclaimer: For information and education only; not investment advice or a recommendation to buy or sell securities. Views are the speakers' own.

In this episode of Terminal Value, I'm joined by Cy Khormaee, founder and CEO of Aegis AI, an AI-native email security company that recently raised a $36 million Series A led by Battery Ventures, to discuss why email security is becoming an AI-versus-AI problem, how personalized threats are bypassing legacy rules, and what changes when AI begins handling the intelligence layer of cybersecurity.

We cover how email security evolved from reputation-based appliances to machine learning and rules, why LLM-based reasoning can investigate each message in context, how Aegis uses specialized multi-agent models instead of frontier APIs, why proprietary email data creates a compounding advantage, how automated incident response can shrink exposure from hours to milliseconds, what security buyers need to trust autonomous systems, why AI-native architecture can challenge incumbents, how the category could expand from protecting the corporate inbox to protecting the person, and why Cy hires for slope in an uncertain future.

0:00 Hook: Why email security is becoming AI versus AI
0:40 Intro to Cy Khormaee and Aegis AI
1:45 How email security evolved from reputation and rules to AI
4:55 How AI is making phishing attacks more personalized and harder to detect
9:35 How Aegis uses multi-agent reasoning to stop email threats
12:50 Why rule-based security breaks as threats change faster
15:45 How proprietary email data creates a compounding AI advantage
18:00 How automated response changes accountability and earns trust
25:10 Why Aegis builds specialized models instead of relying on frontier models
31:45 How AI-native architecture can overcome incumbent data advantages
39:25 From securing email to protecting the person
41:15 Why Cy hires for slope in an uncertain AI future
42:50 Closing takeaways

In this episode of Terminal Value, I'm joined by Dylan Robbins, founder and CEO of Lucra, which recently raised $20 million led by ARK Invest Venture Fund to build competitive loyalty infrastructure, to discuss why traditional points programs often struggle to drive adoption, how games and immediate rewards can make loyalty feel worth using, and why the real moat sits in the payments, identity, fraud, and compliance stack underneath the experience.

We cover Lucra's shift from a consumer app to an embedded B2B platform, how the company sells to venues and proves payback, why customers that try to build the stack themselves often come back, how Crown brings mobile games into the days between venue visits, how Bracketology extends the model into reality TV, what loyalty could look like when rewards are narrower and immediate, and why Dylan thinks the AI funding boom may be crowding out other kinds of innovation.

0:00 Hook: Why building loyalty in-house costs more than brands expect
0:45 Intro to Dylan Robbins and Lucra
1:43 Why traditional loyalty programs struggle to drive adoption
4:17 How Lucra replaces points with immediate rewards
6:23 From customer goals to integration, payback, and ROI
11:20 Market size, pricing, and the path to self-serve integration
15:22 Lucra’s three growth pillars: IRL, mobile games, and reality TV
17:26 Why brands eventually buy instead of build
21:12 How Crown connects physical venues to mobile games
25:27 How Bracketology expands Lucra into reality TV
30:09 What loyalty could look like in five years
31:54 Why the AI funding boom may be hurting startup innovation
34:05 Closing takeaways