Gadi Eliashiv

This is truly the best time to build. Ben Broca proves you can build anything you can imagine with just 1 person. - New companies should be at least 80% driven by AI (marketing, ops, engineering) to move as fast as possible. - The last 20% is all taste/creativity/direction: you're still selling to humans even if AI drives the company. You still need to delight them - When you believe there's something you can't do, try solving it with AI even if it seems hard so you can learn and automate most of the processes. - Limitations: models will become more generalist but still need to have narrow scope to perform well today. Polsia itself has agents that report bugs/feature requests when talking with customers, then a PM agent that decides priorities, then an engineering agent that builds it. No excuses. Time to lock in. Awesome podcast Julian Weisser Solo Founders

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A problem every AI company is wrestling with Why is testing LLMs so frustrating for developers? Because even a perfect release won’t hit 100%. You’re not writing unit tests, you’re managing probabilities. From my latest Agents at Work interview with Nimrod Kor CTO Baz Watch the full episode in Youtube: https://lnkd.in/eDYMx8RJ Listen to the full episode in Spotify: https://lnkd.in/evq5Vd4s

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This week, we shipped a predictive route detector and stabilized Tycho execution flows, inviting a few partners for short onboarding calls. This week, our team shipped a focused, production-oriented step toward private, safe MEV routing. We integrated an FMD-based profitable-route detector into the execution stack, refined Tycho route encoding and Permit2 flows, and stabilized our canonical two-hop example, enabling contributors to reproduce realistic simulations locally. These changes aren’t just code. They cut down wasted simulations, surface higher-quality candidate routes, and make private execution paths more deterministic and auditable. Quick technical highlights: - FMD detector: physics-inspired prediction (TPS/committor) ranks route candidates before expensive REVM validation. - Safe execution: Tycho-encoded solutions + Permit2 user-transfer flow — never broadcast to the public mempool. - Developer flow: fixed example stability and clearer env checks, so onboard cycles are shorter. Why it matters: Extracting value from fragmented DEX liquidity is both an engineering and research problem. Predictive filtering reduces noise, and deterministic encoders reduce execution risk; that’s what moves this from lab experiments to usable tooling for desks, wallets, and integrators. We’re inviting a small set of partners for a brief 20 to 30-minute onboarding call to walk through our approach, discuss integration pathways, and gather feedback on our docs and APIs. If you’re building MEV-safe routing, wallet integrations, or execution infrastructure and would like a private walkthrough, message me or email joshua.davidson@orkidlabs.com, and we’ll schedule a quick call. If you're interested, please preview our new whitepaper below. DM for a copy if you surf chaos like Paul Atriedes rides the sandworm. Negentropy I'll send you the version properly processed with LaTeX. I promise. 🙏 — JC, ORKID Labs p.s. Beta Version of ORKID's Uniswap V4 hook deployed: https://lnkd.in/gTn46y6Q #MEV #MEVProtection #DeFi #Web3Infrastructure #Rust

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SaaS founders: don’t wait for off-the-shelf AI solutions to catch up. Build what your team actually needs. At Arkeo AI, we built a custom coding agent in under 2 weeks. It now powers project planning, documentation, and code intelligence across our stack. Why? Because speed and context win. Here’s how we did it, and how you can too: https://lnkd.in/gjYfG5C4 #SaaSFounders #AIproductivity #LLMintegration #DeveloperExperience #BuildInPublic

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EVERYONE is responsible for sales at your startup! This picture is actually of my CTO/Co-Founder, Gregory Steckel, a Georgia Tech grad student studying Data Analytics. While he may hold the title of CTO at our startup, everyone is responsible for sales, even him. This idea of sales culture is ingrained in all of us, so much so that my co-founder literally called a potential-customer SEVEN TIMES before actually closing the deal and getting a meeting on the calendar. Now, for most people, that would sound ridiculous. I honestly was begging him to stop calling the guy after the call number 3 (that went to a voicemail). He continued anyway, and on the 7th call the potential customer finally picked up! The call went so well that the customer sold our software for us! We didn't even have to sell our offering. The product-market fit was so amazing; it was literally out of this world, and it just showcases what happens when you really empower everyone on your team to do sales and have belief in themselves. If you're building a startup and you have two co-founders and VCs are asking you who's in charge of what: Yes, you guys may have responsibilities and titles, but just know that at a startup, every single person is responsible for sales. Versaunt

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Deal of the Week https://lnkd.in/dbwycUFN Augmented Intelligence Inc. — $20M at $750M valuation https://aui.io Investors: eGateway Ventures (lead), New Era Capital investor group, strategic partners AUI's Stealth Play for the Post-Transformer Era AUI continues to operate under deep stealth while charting a bold path beyond the transformer paradigm — a contrarian stance in an AI landscape dominated by compute-heavy scaling wars led by OpenAI, Anthropic, and Google DeepMind. The company's recently closed $20M bridge SAFE at a $750M valuation cap underscores deep investor conviction that the next wave of AI breakthroughs won't come from bigger GPUs, but from smarter architectures. While the broader market remains fixated on model size and synthetic data pipelines, AUI's research focus lies in neuro-symbolic reasoning, blending the statistical power of deep learning with the logical rigor of symbolic systems. This hybrid approach promises greater reasoning reliability, interpretability, and energy efficiency — three attributes that address growing skepticism around current foundation models' opacity and cost of scaling. The raise brings AUI's total capital to nearly $60M, fueling the quiet development of its Apollo-1 reasoning engine, rumored to be a foundation-model architecture that fuses symbolic logic modules with dynamic neural representations. Insiders describe Apollo-1 as a potential step-change in "grounded AI" — one capable of multi-hop reasoning and factual traceability without massive compute budgets. Within New York's fast-emerging AI corridor, AUI is becoming one of the most closely watched under-the-radar companies, blending research sophistication with enterprise-grade product discipline. Its investor syndicate — composed largely of deep-tech and frontier-AI specialists — sees this as an early bet on the post-transformer paradigm: leaner, more explainable AI that could redefine how intelligence is modeled, trained, and deployed. Deal Significance AUI's bridge round reflects a broader inflection point in AI investing — where capital is shifting from pure scale bets to architecture differentiation and reasoning fidelity. The company represents a hedge against the saturation of transformer economics, where model improvements deliver diminishing returns on exponentially higher costs. If Apollo-1 delivers on its promise of interpretable, low-energy reasoning, it could position AUI as a strategic acquisition target for hyperscalers seeking new compute-efficient architectures, or as the foundation for a new class of hybrid AI platforms capable of combining symbolic logic with generative fluency. For investors, this deal underscores rising conviction that the next "OpenAI-moment" may emerge not from scale, but from structure — and AUI's stealth trajectory gives it the mystique and momentum to be one of the few serious contenders for that title.

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POS systems come and go. Some don’t last long. We’ve seen it all - flashy launches, big promises, and then… they vanish. Because building a reliable POS system isn’t just about writing code. It’s about understanding how businesses actually run: - Day-to-day reliability - Clear and simple interfaces - Ongoing updates and real support - Compliance with local laws and payments Some products don’t make it past the first wave of issues. Others slowly fade when they stop evolving. But we’re still here - improving every week, listening to users, and solving real problems.

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This is a long-awaited release of a new product in our family, built on the foundation of Toloka technologies and our expert community: welcome Tendem, a hybrid agent that is able to solve complex tasks where AI-only solutions fail. The "AI vs. Human" debate is a distraction. The real future is Human + AI. The human provides the strategic judgment; the AI provides the tactical speed. It wasn’t easy, but we have finally learned how to automate the decomposition of long-horizon tasks into steps and the delegation of each part to the best executor - whether that is another AI, or a specialised domain human expert - followed by an automated Quality Control mechanism to ensure every delivery is business-ready. The backbone AI-only part of our hybrid agent provides the highest possible level of automation: it operates on par with the best solutions in the industry. This helps human experts execute tasks faster and with higher quality compared to human-only environments, and allows users to remove the overhead and save time associated with finding, vetting and managing individual freelancers on classic platforms. For us, this is an organic step in the development of Toloka, that leverages our team's unique expertise and provides more opportunities for human experts community. Read more details in our blog and whitepaper in the comments! https://lnkd.in/e7spJtZN

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That first big win taught Devster Labs LLC something fundamental: success in tech projects isn't about having the most skilled people on paper. It's about understanding the less visible dimensions, the working styles, communication rhythms, and context fit that make or break teamwork under pressure. This insight reshaped our entire 2025 strategy. We stopped treating hiring as a checklist of skills and started viewing it as the foundation for lasting collaboration and agility. Our focus expanded from just recruitment to team chemistry, ongoing feedback, and rapid adaptability. Today, it drives how we build, train, and support every project team, because your people processes are as critical as your tech stack. What early lesson changed the way you approach building or leading your teams? #Leadership #Teamwork #Collaboration #Adaptability #WorkplaceCulture #TechLeadership #BusinessStrategy #TeamBuilding #ProfessionalGrowth #FutureOfWork

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