Michael Bloch

I’ve known David Meister for years and backed him at Sydecar, so I’ve seen his ability to build through complexity. Axiom Trust is taking on one of the most outdated parts of wealth infrastructure, trust administration, by pairing a regulated trust company with AI-native workflows. We're proud to invest again and congrats to the team on the launch!

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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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Today Isembard announced a $50m Series A fundraise led by Union Square Ventures, less than a year after Notion Capital led their Seed round. 💥This is a company right at the intersection of AI & supply chain sovereignty & they’re exceeding even our most optimistic expectations. By the end of the year they will have 25 factories across the UK, US, Germany, France & Ukraine. 💥Isembard is rapidly scaling its network of AI-first factories for precision manufacturing at the same time as market demand is accelerating. Macro forces (reshoring, rising defence spend, concentration risk in Asia, and the growth of neo-primes) are structurally increasing demand for fast, local, flexible manufacturing that the current industry is unable to deliver on. 💥The innovation is in the way the company builds and franchises factories as a product with tightly integrated units of machines, software, robotics, & process intelligence that turn design files into certified components with speed & reliability. 💥Their AI software platform, MasonOS, connects all sites into a single operating system, replacing fragmented shops with standardised, high-performance industrial nodes & enabling real-time quoting, predictable delivery, & low defect rates. By owning the full production stack, Isembard delivers premium manufacturing performance with the scalability & flexibility of a software platform. 💥We are at the top of the AI hype cycle and there are understandable concerns about the ROI on the vast sums of money being invested into this new super-cycle. But, the ROI for Isembard is both clear and compelling. They will deliver components 10x faster and at 50% of the cost of current suppliers. They will also build a de-centralised, global network of factories to meet the growing demand for national or regional sovereignty. 💥This is a company with a clear vision to disrupt a massive, fragmented $1.8tn component manufacturing market. Today marks another huge stride towards that vision. And they are only just getting started. We’re thrilled to be on this journey with Alexander Fitzgerald & the team & we’re also excited to welcome Rebecca Kaden & USV into the investor base. Notion Capital Union Square Ventures Alexander Fitzgerald Rebecca Kaden Maximilian Eichler Stephen Millard Britt Mulder

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Every #VentureStudio GP knows some portfolio bets won’t hit. That's expected - and it's one of the reasons studios are such a powerful vehicle for innovation. And while a venture's failure might be what's visible to the outsider, what keeps them up at night isn’t failure at the venture level — it’s failure at the systemic level within the studio. One bad entity design. One IP misstep. One governance gap. That’s how studio operations fall apart. We break down how to spot (and fix) these cracks before they turn into fault lines in our latest paper, "The GP Dilemma" - DM me and I'll send you a copy!

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"Build the event you wish existed" That's what we at Monadical did last week at #NYTW. We wanted an AI Engineers discussion for Engineers. There's always a lot of events out there for VCs to network, or for startups to learn about G2M, but very little on lessons learned from actual engineers in the field. So that's the event we hosted. Big thank yous to our awesome panel, Roy Pereira, Ben Cohen and Corey J. Gallon. Here's the key takeaways and the AI tools we're using. 🚀 All three panelists independently called AI Agents the most transformative LLM application they’ve used. They specifically called out Claude 3.5 Sonnet for its accuracy and reliability. 🪨 We dug into how LLMs are “jagged”, not general. They can be shockingly good at some tasks and completely fail at others. Everyone agreed: good evaluations are critical (and hard.) 🧪 Corey noted how public benchmarks and reality are two different things. Most public evals are saturated or gamed. ♊ Ben emphasized that AI projects are actually two projects: building the tool and building the evaluation process. 🧱 We explored how falling dev costs may impact startup defensibility and labor demand. Roy shared that founders are already shifting strategies in response. ⚒️ In a world of daily AI launches, the panel discussed how they decide what’s worth attention, and what’s just noise. They called out tools like Goose, Aider, Claude Code, and Monadical’s own Cubbi, which helps run agentic workflows safely in dev environments. (links in the comments). CTA: What would you want to hear in an AI Applied Engineering talk you attended?

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Thrilled for OVNI Capital to be backing RIFT in a pre-seed round led by AlleyCorp (Luc Ryan-Schreiber). Rift is building the first real-time aerial intelligence network, a new layer of infrastructure for persistent, on-demand visibility where it matters most. This funding will scale production of their autonomous stations, accelerate deployment in high-stakes environments, and expand the team leading the next phase. 🗞️ Explore the full story: - StartupMafia: https://lnkd.in/dARrg25N - BFM Business (FR): https://lnkd.in/eADSUsn7 - Les Échos (FR): https://lnkd.in/eFG3zAy5 👨‍🚀 Join the mission → https://lnkd.in/erm_SrTG

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With RL techniques like GRPO, it’s become easy to fine-tune small models to outperform foundation models on vertical tasks. We’re open sourcing Osmosis-Apply-1.7B: a small model that merges code (similar to Cursor’s instant apply) better than foundation models. Links in comments! Using foundation models for high specificity, low complexity tasks like code merging can be overkill - instead, it’s better to use a specialized model instead for higher performance and latency. We fine-tuned the model on 100K real-world code commits where the model needs to merge a code edit snippet into an original code snippet. On the test dataset (subset of CommitPackFT), foundation model performance ranged between 0.77-0.93 reward score. In comparison, Osmosis-Apply-1.7B achieved a 0.98 reward score - while also being 3X-5X more affordable than the next cheaper model AND ~10X faster! Why this matters: the best AI agents use multiple models to ensure task specialization and reliability at scale - on top of cost and latency benefits as well. Links to the model and full write-up (with reward function, hyperparameters, etc.) are in the comments - reach out if you’re interested in using reinforcement learning!

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While there has never been a more exciting time to be a founder building dev tooling or next-gen infra, it has also never been less investable at seed/pre-seed. I'm either really missing something or a lot of my peers are lost. As someone who has not just written, but also SHIPPED, about 75k lines of code in the past 6 months I can tell you that the evolution of how to build products has changed as much in the past year as it did in the entirety of 2007-2017. The complete rise and fail of frameworks, platforms, methodologies, etc... paved over and forgotten... that is of course except for the 1 company that gets a 1000x return from a wildly overvalued hyper-scaler or drunken growth stage investor obsessed with compounding at scale. Imagine a world where any seed investor in trends like Openstack, Hadoop, PaaS, etc all took a full loss on their investment. That's what we're looking at right now. I personally know of over a dozen well-funded seed-stage companies building in these spaces, with years of runway, scrambling to get acquired for a return of capital + several million personally while they're still relevant. If you're not seeing this unfold in front of you, you either aren't paying attention or you're satisfied playing the lottery instead of investing.

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Thrilled to share the launch of Criticality, a $65M fund built to back founders solving hard, high-leverage problems at the intersection of technical complexity and real-world urgency. Criticality builds on the foundation we’ve laid at Antler - applying our conviction-driven approach to companies at Seed & Series A. The fund is sector-flexible but applies a deep tech lens to each opportunity, targeting non-obvious, high-leverage problems from the earliest stages of company formation. Grateful to the New Mexico State Investment Council for their support in anchoring Criticality. More to come soon from Cash Allred & I.

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