Anant Bhardwaj

Key takeaways: - The core shift is economic, not hype. LLMs turn “AI” into a recurring operating cost, so pilots quickly become capacity planning, governance, and ownership. - Power and timelines show up because production inference needs sustained compute capacity. When usage increases across the org, you run into procurement, security review, integration work, and infrastructure readiness challenges. - The winners are not the teams with the flashiest demos. The winners are the teams that convert compute into measurable outcomes inside a workflow with traceability and controls. - In 2026, “AI strategy” that is not tied to a specific workflow, KPI, and operating model is mostly theater. If you are building the application layer on top of the datacenter buildout, execution systems, workflow automation, data-layer tooling, compliance automation, I want to see what you are shipping. Founder intro: www.axion.ventures

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The $20/Month Software Revolution Software development has operated within established boundaries for decades, with clear divisions between those who code & those who don’t. But what happens when those boundaries dissolve overnight, & anyone can build functional applications for the price of a monthly streaming subscription? For twenty years, professional software development meant specialized teams, lengthy sprints, & rigorous adherence to architectural best practices. Companies invested months in planning, weeks in development cycles, & substantial resources in quality assurance. The barrier to entry remained high, protecting established players & maintaining predictable market dynamics. AI coding tools have shattered this equilibrium. Cursor, Lovable, & similar platforms now enable non-technical founders to prototype working applications in hours rather than months. The result is an explosion of vibe coding: intuitive, rapid application development that bypasses traditional workflows entirely. This shift has created a fascinating paradox for founders & investors. The current landscape rewards speed over sophistication, with spaghetti-coded solutions often outpacing polished alternatives to users’ laptops. Yet this same accessibility threatens to commoditize software development itself, raising questions about where sustainable competitive advantages will emerge. The answer lies in recognizing this period as history’s largest distributed market research experiment. Thousands of individual users are discovering optimal AI-enhanced workflows through trial & error, essentially crowdsourcing the future of software development. Smart players should treat this chaos as intelligence gathering rather than noise. The strategic opportunity exists in two phases. First, embrace experimentation during this chaotic period because the cost is minimal, & the learning is invaluable. Second, prepare for consolidation by identifying workflow patterns that demonstrate real user adoption & commercial viability. The current vibe-coding era won’t last forever. Eventually, brilliant practitioners in each domain will distill optimal workflows from this experimentation, commercialize them, & establish new industry standards. The companies that recognize these emerging patterns earliest & build robust, scalable versions before the market standardizes will define the next generation of software development tools. The glee of solving problems with $20-per-month AI tools represents more than convenience; it signals a fundamental restructuring of how software gets built & who gets to build it.

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AI is replacing software engineers. So why are job postings accelerating? 🤔 Software engineer job postings are up 11% YoY ! That's the data point that made me pause when reading Citadel Securities' latest macro note this week. The dominant narrative right now: AI kills software jobs, #SaaS multiples collapse, the model is broken. Markets repriced sharply over the past two weeks. But what does the labor market actually say? Indeed job postings for software engineers bottomed in early 2025 and have been recovering since. Not a marginal uptick. A clear inflection. Citadel's argument is worth sitting with: - AI adoption at work is growing, but linearly, not exponentially - Recursive technology capability does not equal recursive economic deployment - Every prior productivity shock (electrification, computing) expanded demand, it didn't destroy it - Data center construction is actively creating new jobs in construction and adjacent sectors The SaaS valuation reset may reflect something real: margin pressure, AI-native competition, pricing risk. Those are legitimate. But conflating "AI changes software economics" with "software is finished" looks like the same pattern we've seen before. Fear outruns data. Markets price the tail scenario. Then reality mean-reverts. #Keynes predicted a 15-hour work week by 2000. He got the productivity right. He completely missed the elasticity of human wants. Worth asking: are we pricing a structural break, or a cyclical adjustment dressed up as a revolution? Below graph : Postings peaked, plunged, then pivoted. The 21-day moving average smoothing out the daily noise to reveal a clean recovery trend underneath Thank you Julien and Gaetano for the reference 🙏

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To my dear VC friends, We are all very excited about the growth rates of AI companies. But when you declare "Triple–Triple–Double–Double–Double (T2D3) is dead," you create chaos in your own firm and with your LPs. And your IR team pays the price. 𝗛𝗲𝗿𝗲'𝘀 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: IR teams just spent 24 months explaining LPs that albeit their portfolio lack liquidity, the fundamentals of their existing portfolio companies are solid, etc... LPs committed hundreds of millions based on that narrative. Now the partners, from the same firm, are saying that model is outdated.... 𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁? Confused LPs asking: - "So what are the paper returns marked at 3x MOIC on your Saas companies really worth ?" - "Why did you say that the existing portfolio companies were doing well?" - "Why should we trust the new narrative?" - "What else will change next quarter?" IR teams scrambling to explain: --> Why yesterday's pitch is today's problem --> How the new model is totally different (but also kind of the same) --> Why this pivot strengthens the strategy (somehow) 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗻𝗼 𝗼𝗻𝗲 𝘄𝗮𝗻𝘁𝘀 𝘁𝗼 𝗮𝗱𝗺𝗶𝘁: T2D3 isn't just a growth model. It's a framework LPs have internalized for 10 years on how to evaluate B2B Software companies. They use it to model returns. They use it to compare companies and portfolios. They use it to explain venture investing to their boards and ICs. When you suddenly declare it dead, you're not just changing metrics. You're breaking the narrative that built trust. 𝗧𝗵𝗲 𝗳𝗮𝗹𝗹𝗼𝘂𝘁: → Every fundraise gets harder → LPs hesitate on re-ups and do more due diligence on the portfolios → New LPs question your consistency → IR teams on calls with LPs 10 hours a day and burn out managing the confusion 𝗧𝗵𝗲 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵: Evolution, not revolution. Show how the market is expanding. Explain why multiple models can coexist. Build on what LPs understand, don't demolish it. Because here's what matters: LPs need clarity, not contradictions. They need consistency, not pivots. They need to trust your story won't change with the wind. The future of venture depends on this. You can celebrate new growth models without torching the frameworks that built LP confidence in the first place. Your IR team will thank you. Your LPs will trust you. And your next fundraise might actually be smoother. ❤️

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