Qi Zhang

Every fast-growing company expanding into new markets faces the same dilemma. Do we dedicate engineering months to integrate each local payment method 1:1, or do we slow down our launch until it is done? The truth is, these integrations drain bandwidth. - Engineers spend weeks building, testing, and maintaining each connection. - Finance teams then wrestle with reconciliation across multiple PSPs. - Meanwhile, go-to-market momentum is lost. This is where payment orchestration changes the equation. A single integration unlocks access to all local methods, reduces maintenance, and keeps engineering focused on core products. More importantly, it accelerates go-to-market and gives companies the flexibility to move into new regions without the hidden tax of endless integrations. For teams scaling globally, orchestration becomes a strategic advantage. #PortOne #PaymentOrchestration #FintechInnovation #GlobalPayments #PaymentProcessing #ScalingFinance

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Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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Reflections from 1 week in SF: - Dev tool space has never been hotter (emphasized by Figma's recent IPO!) - Agentic UIs and workflows are becoming the bare minimum - Fundraising is rarely a concern to founders in the Bay area. Founders are raising pre-seed with a Notion doc + hype (despite macro sentiment!) - Talent density is unparalleled (so much so that I met a cracked engineer living in his car just to be close to the Bay area) - Most founders I met were both extremely technical and could sell ice to eskimo - Vertical AI platforms could be huge disrupters to mom+pop shops….Think AI-native ERPs for niche markets: AI for insurance underwriting, AI-first factory optimization, AI enabled supply chain ordering for dentists etc. Verticalised solutions with a full-stack GTM, co-built by domain experts, with a network as a moat = 🔥 - Founders are truly pushing frontiers of innovation more than I've ever seen before. Everything from agentic deployment in <5 mins, agents working with agents, agentic browsers [see the trend?], fitness non (!) wearables, poop scanners, chat to 3D print & more - Tremendous long term efforts in bringing together the ecosystem for upskilling, knowledge sharing & connecting. Literally attended startup events held at a library, a community centre, a comedy club, an accelerator & the AWS's builders loft (shoutout Amazon Web Services (AWS) for all the free food 😂 ) - AI on billboards everywhere (see pic!)

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Tech professionals: Your values don't have to stop at your code. 💻🌱 As someone who works with Bay Area tech workers planning for early retirement, I see a growing trend: professionals want their investments to reflect their values, not just generate returns. Socially Responsible Investing (SRI) lets you align your portfolio with your principles using ESG criteria: ➡️ Environmental: Companies with low carbon footprints and green initiatives ➡️ Social: Organizations promoting diversity and fair labor practices ➡️ Governance: Transparent, ethically-run businesses The best part? A 2019 study showed SRI performance matches traditional investing approaches. You don't have to sacrifice returns for values. Whether you're focused on FIRE (Financial Independence, Retire Early) or building long-term wealth, SRI can be part of your strategy. The key is balancing your social impact goals with solid investment fundamentals like diversification and risk management. Ready to build a portfolio you can be proud of? Let's discuss how SRI fits into your early retirement plan. https://lnkd.in/gH6Vt-w5 #SociallyResponsibleInvesting #TechFinance #ESG #FIRE #BayAreaFinance

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Terminal Use (YC W26): Vercel for background agents. Terminal Use is hosting infrastructure for background agents that makes harness engineering easy. https://lnkd.in/gv99wN2t

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Today, MorFi Technologies open sourced more of its MISMO Typescript SDK and utilities functions to help others more effectively develop mortgage software applications. The Mortgage Industry Standards Membership Organization (MISMO) is a standards development body for the mortgage industry. MISMO develops a common language (XML/XSD) for exchanging information between participants in the mortgage finance industry (software vendors, originators, lenders, investors). Without an SDK, it's challenging to adopt the MISMO standard and utilize it as a deeply integrated part of your software application. As the most comprehensive data definition of a mortgage loan, MISMO is the best way to represent a mortgage in your software applications. If you're building a point of sale, loan origination system, pricing engine, customer relationship management system, or some other software for mortgage origination, a MISMO object constructed with our open-source SDK could be a great way to represent a mortgage in your software system. This SDK for MISMO will hopefully help others build mortgage software applications without needing to reinvent a data model that attempts to represent the enormous complexity of a mortgage loan. If you're a developer that would like to contribute, or someone that would like to use an SDK like this, please get in touch. Brian Vieaux, CMB Greg Sher Lance Yan Trent Hedge David Rogove James Kleimann Jonathan Kearns Chris T. Kaz Nejatian Taranjeet (TJ) Kaur https://lnkd.in/grtzywhj

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Just submitted MAM: Maker Auction Markets to https://lnkd.in/gdfEhNhH (Designing Defi) MAM eliminates entire classes of MEV by shifting from reactive pricing to time bound collateralized commitments and user constraints/intents. Im curious do you think the way things are currently are the way things always have to be? We are what? 12-15 years into this industry? Innovation has only just begun.

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CRV Security: Request for Startups I never know if this actually works for our friends over at YC but figured we'd try. Here's what we want to fund in 2026! 1. Golden Artifacts: Think Chainguard but more broad. Artifact attestation exists for open source. Almost nothing exists for internal software — especially the vibe-coded tooling now running in production. We want the company building cryptographic proof of secure software delivered from secure artifacts: who built it, how, and whether it was reviewed. If more things are being yeeted into the world via Claude Code (myself included), this feels like an issue. 2. MCP & Agentic Security: Agents are getting real credentials and taking real actions. The security posture of most orgs around this is basically zero. That changes fast. You'd never give an employee hardcoded API keys or write access to your email without supervision/trust. Why give it to agents? 3. AI Governance: Boards are asking CISOs to account for AI risk. CISOs have no good answer other than "Palo has a module" 4. Next-Gen Endpoint: CrowdStrike was built for a world of static binaries and human operators. AI workloads, cloud-native infra, and AI-assisted attackers need a new architecture. The category is ready to be reinvented. 5. Networking in the AI Era: Zero trust was designed for humans. What does network security look like when the entity requesting access is an agent? Nobody's really solved this. 6. Email Security + Next-Gen Phishing: LLMs have made spear phishing infinitely scalable. I've never truly understood why Abnormal and KnowBe4 aren't one company. Maybe this time it's different. 7. Frontier Security Lab: We'd back a credible, well-staffed lab focused entirely on red-teaming models and setting the evidentiary standard the industry needs as LLM built apps become the norm. 8. Dependency Security: That Actually Remediates Malicious and vulnerable dependencies are a top attack vector. The tooling is mostly noise — scanners that don't close the loop. The winner here ships fixes, not just alerts. 9. Critical Infrastructure Cyber: Data centers, satellites, power grids, undersea cables. The physical backbone of the internet is increasingly exposed and wildly under-defended. We have data centers in space, for God's sake. Surely we need better cyber for critical infrastructure? 10. PAM for the Modern Era Legacy: PAM was built for static roles, human users, on-prem directories. Cyberark was founded in 1999.....Agents, ephemeral workloads, and cloud-native infra have broken all of those assumptions. Is anyone rebuilding this from scratch? If you're building in any of these areas — or something we haven't thought of — reach out. james@crv.com

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Their mortgage is their biggest expense. Even a 0.5% reduction in rate would more than double their savings each month. Whether your employees are working professionals or frontline workers, Multiply Mortgage's free employee benefit can make homeownership more accessible and affordable via discounted mortgage rates, expert guidance, and homebuying education and tools.

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The infrastructure cost of starting a company has collapsed so dramatically that credit programs have become a form of shadow funding. In the last months, we've accumulated ~$125k in credits from Google, ElevenLabs, Auth0, PostHog, and Retool, some even without asking. From their POV, it's straightforward customer acquisition math. These companies know a percentage of startups will grow into six-figure contracts, so they subsidise everyone and harvest the survivors. The danger is that it starts to feel like validation. I've seen founders more preoccupied with which grant programs they've gotten into than how much revenue they're generating. The number one reason startups fail is they run out of money. None of this replaces revenue, but it at least buys you the runway to find it.

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Mike Merrill and I are excited to announce the next chapter of Terminal-Bench with two releases: 1. Harbor, a new package for running sandboxed agent rollouts at scale 2. Terminal-Bench 2.0, a harder version of Terminal-Bench with increased verification Harbor is the package we wish we had had while making Terminal-Bench. It’s for agent, model, and benchmark developers and researchers who want to evaluate and improve agents and models. Just a few of the features I love about Harbor: - Evaluate any agent that can be installed and run autonomously - Scale up to thousands of concurrent containers using providers like Daytona and Modal - Generate rollouts for SFT data gen and RL - Create your own benchmarks or use existing ones like SWE-Bench Verified Harbor is also the official harness for Terminal-Bench 2.0. We used it to run tens of thousands of experiments in containerized environments while developing the latest version of the benchmark So why Terminal-Bench 2.0? We always knew that as model capabilities increased, we’d need to keep Terminal-Bench up to date with frontier capabilities. Terminal-Bench 2.0 consists of 89 hard tasks to test these capabilities. We aim to push the frontier with an increased emphasis on task quality. Each task received several hours of human and LM-assisted verification to ensure that tasks are (1) solvable, (2) realistic, and (3) well-specified. We’ll share more on how we did this in our upcoming preprint. At present, Codex CLI with GPT-5 sits at the top of our new leaderboard. Astute Terminal-Bench fans may notice that SOTA performance is comparable to TB1.0 despite our claim that TB2.0 is harder. We believe that this is because task quality is substantially higher in the new benchmark. We have removed several misspecified or impossible tasks – increasing difficulty while maintaining raw performance. Interested in using Terminal-Bench-2.0 or submitting to our new leaderboard? Check out the Harbor docs for more information. It's been a pleasure working alongside our advisors, Ludwig Schmidt, who seeded the idea and guided our development, and Andy Konwinski, who gave us the Laude Institute mandate to "ship your research." Additionally, Terminal-Bench wouldn’t be possible without its community. We’re so thankful to the over 1k members of our Discord who contributed and audited tasks, helped build and beta test Harbor, and made this such a fun project for everyone involved. https://lnkd.in/guZXbPVn https://lnkd.in/g7xqkjK8 https://lnkd.in/gETM-wkx

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We've raised a $10M Series A for Depot from Felicis, Y Combinator, and Pioneer Fund 🚀 I talk to folks every week who are exhausted and blocked by the existing status quo — not just the delivery pipeline, but the software development platform as a whole. We're in a new world of software engineering. One where an idea can become working code in minutes. But the existing tools simply can't keep up. They're crumbling under the load. The bottleneck has shifted. Writing code is no longer the bottleneck. Integrating it is. Everything that comes after the code is written is now the problem: - Source control that's slow and unreliable - CI pipelines that are slow, flaky, and can't handle agent workloads - Code review designed for a pace of engineering that no longer exists - Context trapped in silos, inaccessible to agents and engineers alike The current providers aren't working for this world. So what are we building in the short term? Depot CI. The CI systems we have today weren't built for this moment. GitHub Actions, CircleCI, Buildkite — designed for a world where humans batch up code, push it, and wait. A 15-minute pipeline was annoying but survivable. That world is gone. A team of 10 engineers with agents can now move like a team of 100. The volume of code entering CI has never been higher. The old systems aren't just slow — they're architecturally wrong for this moment. Depot CI is a programmable CI engine with performance as a first-class citizen — fast orchestration, composable compute, and an API-first design that works for engineers at a terminal and agents running autonomously. Already on GitHub Actions? Bring your workflows directly — we run them faster and more reliably. But Actions compatibility is just one frontend. We're building something new underneath. Depot CI is the bridge, not the destination. We're building toward a software delivery platform where source control, CI, builds, and validation are all designed from the ground up for the pace engineers and agents are working at today. We started by making builds 40x faster. Now we're building what comes after GitHub. Full post: https://lnkd.in/d_FGCThm

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Most startups die from moving too fast. But plenty die from moving too slow. So how do you actually balance speed vs. technical debt? I sat down with Shuzhi Huang, former Engineering Leader at Google, someone who's seen this play out at massive scale, and got a remarkably honest answer. The insight that hit hardest: technical debt isn't the enemy. Unacknowledged technical debt is. If you're a founder scaling your engineering team right now, or a hiring manager trying to decide when to prioritize velocity over quality — this one's for you. What's your take? The full episode is live. Link in the comments 👇 #Engineering #TechnicalDebt #StartupFounders #EngineeringLeadership #Hiring #BotifySessions #BotifyTech #TechLeadership #Founders

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