# Trigger.dev’s Series A, Laptop-Scale DeepSeek, and the New AI Underwriting Tests

*By VC Tech Radar • May 10, 2026*

This brief tracks Trigger.dev’s Series A, several early teams showing traction or sharp adaptation, and technical signals from local inference, voice agents, and context-layer infrastructure. It also captures the current investing backdrop: AI infra remains the hottest seed category, diligence is tightening, and durability is becoming the key filter in AI underwriting.

## 1) Funding & Deals

- **Trigger.dev — $16M Series A led by Standard Capital.** Trigger.dev offers a simple SDK for adding AI agents to products while it handles execution, long-running workflows, and reliability; YC says more than 90% of current usage now comes from agent workflows. Co-founders Matt Aitken and Maverick David went through three product versions before product-market fit, after spending two years building async infrastructure that later put them in a strong position for the agent era. [^1]

- **PayWithLocus — YC-backed this year, beta opening.** PayWithLocus says it was backed by YC this year and is VC-backed, and is building an AI commercial layer for side projects that automates website creation, customer-specific copy, ads, lead generation, cold email, CRM/analytics, and checkout via Locus Checkout. It is opening 100 free beta spots this week. [^2]

## 2) Emerging Teams

- **18-year-old cybersecurity founder with an existing audience.** An 18-year-old founder from India with 479k followers in cybersecurity used Claude to build a tool for CVE analysis and Kali Linux error fixing in four days. The product includes multi-model routing, live ExploitDB integration across 46,000+ exploits, a credit system, and payments; it reached 37,897 users and more than ₹50,000 in sales at ₹499 lifetime pricing after launching to the founder's core audience, with Claude, Vercel, and Supabase keeping launch costs near zero. [^3]

- **AI-enabled operator-founder with GTM muscle.** A solo founder with 20+ years in tech marketing says AI helped them learn to code and launch two products in 12 months: a B2C community app with 1,600+ users, 75% Android retention, and zero paid acquisition, plus a B2B hiring platform with Stripe billing, press coverage, and first external signups. The founder's own takeaway is useful: AI made building possible, but revenue and distribution remain the real tests. [^4]

- **AIRankr — early wedge around AI search visibility.** AIRankr positions itself as an AEO tool that checks whether businesses appear in recommendations from ChatGPT, Perplexity, and Gemini, targeting local businesses and agencies that are starting to lose top-of-funnel traffic to AI search. The founder says the first paying customer came from a Reddit comment that drew 1.1k views. [^5]

## 3) AI & Tech Breakthroughs

- **ds4 adds concrete evidence for laptop-scale frontier inference.** Antirez released ds4, a native inference engine built for DeepSeek v4 Flash, which is described as a quasi-frontier model with a 1M context window. The key changes are 2-bit quantization and moving the KV cache from RAM to SSD; in one reported M3 Max 128GB test, ds4 delivered 14-15 tokens/sec at a 62K pre-filled coding context, held memory around 85GB during generation, used roughly 8GB of disk cache for a full 100K context window, and kept normal thermals. The main limits cited so far are fresh prefills after compaction at roughly one minute per 10K context, while multi-agent parallel performance is still unclear. [^6][^7][^8]

- **Voice agents are moving from cascades to native speech-to-speech.** cocall.ai says it built a near-0 latency, full-duplex phone-calling stack using a native speech-to-speech model rather than a slower speech-to-text, LLM, and text-to-speech chain, to the point that it added artificial delay to avoid interrupting humans. The product also supports contextual pausing, live transcripts with human takeover, verified caller ID, IVR navigation, and barge-in handling with only a few milliseconds of gap. [^9][^10]

- **The context layer is emerging as a defensible design point.** Jerry Liu argues that one of the few remaining moats in 2026 may be the context layer: as UI simplifies, agent abstractions stabilize, and users program more in English, agents still need reliable access to systems of record, the web, and documents. He argues the implementation is moving from naive RAG in 2023 toward file sandboxes in 2026, while open questions remain around the tool layer, the number of tools or subagents agents actually need, and whether SaaS companies can monetize end-to-end agents. His hedge is modular architecture rather than letting a single model vendor own the stack. [^11][^12][^11]

- **Some teams are redesigning software components to be easier for agents to work with.** LyteNyte Grid argues legacy grid libraries break AI agents because of imperative APIs and mapping layers; its answer is a 40kb React grid with a declarative, fully stateless, prop-driven architecture that it says has already let Claude Code produce 30+ advanced grid instances. In parallel, Garry Tan amplified a practical rule for agent-written codebases: prioritize top-level architecture first, patterns and abstractions second, and file-level code third, while keeping living diagrams so the system stays understandable over time. [^13][^14][^15]

## 4) Market Signals

- **Durability is becoming the central underwriting question.** Elad Gil argues that 90-95% of AI companies will fail, as in prior tech cycles, and says founders should ask whether their company is genuinely durable or whether the next 12-18 months is the best window to sell before commoditization or direct lab competition hits. His durable buckets are core labs—OpenAI, Anthropic, and Google, with Meta and xAI as additional possible oligopoly players—and vertical applications that improve as models improve, embed deeply into workflows, and make use of proprietary or system-of-record data. He also sees exit paths ranging from labs and hyperscalers to giant tech companies, vertical incumbents, and mergers between close competitors. [^16]

> "So most companies are not going to make it." [^16]

- **Seed AI infra is still the hottest pocket of venture, and diligence is getting harder.** Elizabeth Yin says AI infra is the "white hot center of venture capital" at seed and notes that valuations are highly sector dependent. Sarah Guo adds that fundraising now involves more FUD and "shenanigans" than she has ever seen, making diligence more important. [^17][^18][^19]

- **Access to frontier capability remains extremely uneven.** Elad Gil estimates people at major AI labs using internal models are 3-4 months ahead of Silicon Valley startup engineers, who are 3-6 months ahead of New York, which is 6-12 months ahead of the rest of the world; he says most people are still 1-2 years behind SOTA, and Marc Andreessen co-signs that distribution gap. Separately, a16z says Codex installs spiked last week. [^20][^21][^20][^22]

- **There is also a plateau/regression counter-signal in model releases.** Bindu Reddy says Opus 4.7 is worse than 4.6, Gemini 3.1 worse than 2.5, and Sonnet 4.6 buggier than 4.5, concluding that some SOTA models may be "running around in circles." [^23]

- **Website generation is already showing signs of commoditization.** Neural Draft's founder says continued investment in AI website generation no longer made sense once Claude CLI, Claude Design, and Lovable became the preferred tools—even for the builder—so the company shifted toward backend tools such as CMS, forms, SEO content, booking, e-commerce, and social management. [^24]

## 5) Worth Your Time

### Elad Gil on durability and exits

[Watch](https://www.youtube.com/watch?v=hmIFkwbDYE8) for a concentrated discussion of why most AI companies fail, what makes vertical apps durable, and how to think about exit timing and buyers. [^16]


[![Most AI Companies Won’t Survive (Tech Investor Explains)](https://img.youtube.com/vi/hmIFkwbDYE8/hqdefault.jpg)](https://youtube.com/watch?v=hmIFkwbDYE8&t=38)
*Most AI Companies Won’t Survive (Tech Investor Explains) (0:38)*


### Trigger.dev Founder Firesides

[Watch](https://youtu.be/_y7siiS-V5A) for the founders' account of three product versions before product-market fit, why two years of async infrastructure unexpectedly positioned them for the agent era, and how they think about programmatic checkpoint and restore. [^1][^25]

### Jerry Liu on modular agent stacks

[Watch](https://www.youtube.com/watch?v=HbXvX-KtkSs) for the argument that the context layer may be one of the few durable moats left, and that modular architecture is the cleanest hedge in the agent era. [^12][^11]

### Cliff Weitzman on profitable voice AI

[Watch](https://www.youtube.com/watch?v=HLmo450GSPA) for a rare operator breakdown of a consumer AI business at scale: 50M+ users, more than $10M/month, multi-year profitability, and inference costs pushed down to roughly single-digit dollars per million characters. [^26]


[![Cliff Weitzman: What I Learned from 100 of the World’s Top CEOs & Why Tokens Will Outspend Salaries](https://img.youtube.com/vi/HLmo450GSPA/hqdefault.jpg)](https://youtube.com/watch?v=HLmo450GSPA&t=5895)
*Cliff Weitzman: What I Learned from 100 of the World’s Top CEOs & Why Tokens Will Outspend Salaries (98:15)*


### Hunter Walk on AI and elderly care

[Read](https://hunterwalk.com/2026/05/09/when-your-vc-quits-is-the-founder-screwed-dads-are-doing-more-dadding-than-ever-vc-who-founded-multibillion-firm-thinks-employees-need-more-equity-ai-for-old-people-link-post) for a concise case that AI-assisted senior care is becoming a real investment theme, highlighted by South Korea's bot-based wellness checks that reportedly helped locate a woman with mild dementia and intentionally use a slightly mechanical voice to reduce scam confusion. [^27]

---

### Sources

[^1]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2053150215272857672)
[^2]: [r/SideProject post by u/IAmDreTheKid](https://www.reddit.com/r/SideProject/comments/1t8nj5f/)
[^3]: [r/EntrepreneurRideAlong post by u/adarshverma07](https://www.reddit.com/r/EntrepreneurRideAlong/comments/1t88ky8/)
[^4]: [r/SaaS post by u/Ok_Condition5988](https://www.reddit.com/r/SaaS/comments/1t7yx9h/)
[^5]: [r/SideProject post by u/Efficient_Comfort359](https://www.reddit.com/r/SideProject/comments/1t8frwj/)
[^6]: [𝕏 post by @bindureddy](https://x.com/bindureddy/status/2052982206344409242)
[^7]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2052996810226962846)
[^8]: [𝕏 post by @pradeep24](https://x.com/pradeep24/status/2053173787160609230)
[^9]: [r/SideProject post by u/Burner_123_123_123](https://www.reddit.com/r/SideProject/comments/1t8crds/)
[^10]: [r/SideProject comment by u/IsN4n](https://www.reddit.com/r/SideProject/comments/1t8crds/comment/okvcn30/)
[^11]: [𝕏 post by @jerryjliu0](https://x.com/jerryjliu0/status/2053178322495152261)
[^12]: [𝕏 post by @VentureBeat](https://x.com/VentureBeat/status/2051404500385112334)
[^13]: [r/SideProject post by u/After_Medicine8859](https://www.reddit.com/r/SideProject/comments/1t8q4ts/)
[^14]: [𝕏 post by @chrysb](https://x.com/chrysb/status/2053179291530326462)
[^15]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2053191327181865376)
[^16]: [Most AI Companies Won’t Survive \(Tech Investor Explains\)](https://www.youtube.com/watch?v=hmIFkwbDYE8)
[^17]: [𝕏 post by @PeterJ_Walker](https://x.com/PeterJ_Walker/status/2052827487483154895)
[^18]: [𝕏 post by @dunkhippo33](https://x.com/dunkhippo33/status/2053107857558782113)
[^19]: [𝕏 post by @saranormous](https://x.com/saranormous/status/2053278607896908220)
[^20]: [𝕏 post by @eladgil](https://x.com/eladgil/status/2053206351158091819)
[^21]: [𝕏 post by @pmarca](https://x.com/pmarca/status/2053232513938870420)
[^22]: [𝕏 post by @a16z](https://x.com/a16z/status/2053159332230181245)
[^23]: [𝕏 post by @bindureddy](https://x.com/bindureddy/status/2053287286524309611)
[^24]: [r/SaaS post by u/Ok_Cucumber_131](https://www.reddit.com/r/SaaS/comments/1t8xrx1/)
[^25]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2053150218808697111)
[^26]: [Cliff Weitzman: What I Learned from 100 of the World’s Top CEOs & Why Tokens Will Outspend Salaries](https://www.youtube.com/watch?v=HLmo450GSPA)
[^27]: [When Your VC Quits, Is The Founder Screwed?, Dads Are Doing More Dadding Than Ever, VC Who Founded Multibillion Firm Thinks Employees Need More Equity, AI for Old People +++ \[link post\]](https://hunterwalk.com/2026/05/09/when-your-vc-quits-is-the-founder-screwed-dads-are-doing-more-dadding-than-ever-vc-who-founded-multibillion-firm-thinks-employees-need-more-equity-ai-for-old-people-link-post)