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Andreessen Horowitz is looking to pay $400K+ for a leader to build out a podcast network
Andreessen Horowitz is looking to pay $400K+ for a leader to build out a podcast network

Business Insider

time2 hours ago

  • Business
  • Business Insider

Andreessen Horowitz is looking to pay $400K+ for a leader to build out a podcast network

Andreessen Horowitz is on the hunt for a podcast leader, the latest step in the famous VC firm's longtime strategy to sidestep the mainstream press and create its own content. In a LinkedIn post, the firm, also called A16z, says it's looking for a podcast network lead to "drive the strategy, operations, and growth of a network of externally created but strategically aligned podcasts." The job involves recruiting independent hosts to Andreessen Horowitz's podcast platform, as well as helping them grow and monetize their audiences. The firm anticipates paying up to $424,000 in yearly salary. The firm didn't respond to requests for comment. Andreessen Horowitz was an early mover among VC firms in content marketing and has long had big ambitions when it comes to media. Its moves in this area tend to be closely watched in media and tech circles. The firm is best known for its flagship show, "The A16z Podcast." The show started in 2014 and taps engineers, founders, experts, and the firm's general partners to talk about where tech is headed. Newer shows include the year-old "The Ben and Marc Show" hosted by cofounders Marc Andreessen and Ben Horowitz, and a science-focused show, "Raising Health." In April, Andreessen Horowitz brought on Erik Torenberg as a general partner to help lead the firm's media and network initiatives. Torenberg is an established Silicon Valley figure who created Turpentine, a tech podcast network. The firm has also invested in media, including in Substack, a newsletter platform that's expanding into new areas like video, and Clubhouse, an audio-focused social network. Andreessen Horowitz's record in media has been mixed. In 2021, it started Future, a buzzed-about publication that put a hopeful lens on tech and society. The firm quietly shut down the publication after a year and a half. But it's stayed the course with podcasting. Under Sonal Chokshi, a former Wired editor who was brought on in 2014 to shepherd its media strategy, the firm expanded to new shows. It also announced a bigger emphasis on its flagship podcast. Over the years, the firm has expressed interest in investing in podcasting, citing the medium's rapid adoption and its ability to go beyond passive listening and become social in nature. Chokshi wrote about Andreessen Horowitz's podcast ambitions in a 2020 blog post, calling podcasts an intimate medium that was better at conveying nuance than text. "Just as great podcasts can come from non-media companies, so, too, will the next podcast networks," she wrote. 'The next stage of content is video' Other VCs like Kleiner Perkins and IVP have hired established journalists and commissioned long-form articles and even films. In this way, firms can set themselves apart, ensure their portfolio companies get press, and counter what they see as negative coverage of the tech industry by traditional news outlets. Ted Merz, who does content strategy for executives at Principals Media, said podcasting and video would allow the firm to better promote its portfolio companies, attract talent, and build visibility. "The next stage of content is video," Merz said. People are consuming more podcasts on YouTube, driving new attention to the medium as well as other personality-driven vehicles like Substack newsletters. Hosts in finance and tech have capitalized, with shows like "TBPN," which has recently hosted VCs like Keith Rabois and Alexis Ohanian. Harry Stebbings, host of "The Twenty Minute VC," parlayed his podcast profile into a $400 million fundraise. Edison Research said in October that YouTube had become the top podcast consumption platform. The platform itself said in February that more than 1 billion people listened to podcasts on the platform every month and that in 2024, viewers watched over 400 million hours of podcasts monthly on TVs. Companies are also trying to win the AI game as people increasingly use the tech for search. A new study by Muck Rack found that about 9% of the links cited by AI represent a brand's own content channels, and another 37% are links to content that features a company or brand. Longform writing still has its place, but podcasts are well suited to VC's media strategy, said Chantelle Darby, a longtime tech PR professional. "Audio and video interviews, in particular, make it easier to extract and package expertise from busy venture partners and founders," she said.

AI tools won't get products out faster, but they'll solve 2 coding problems, says a16z partner
AI tools won't get products out faster, but they'll solve 2 coding problems, says a16z partner

Business Insider

time12 hours ago

  • Business
  • Business Insider

AI tools won't get products out faster, but they'll solve 2 coding problems, says a16z partner

AI isn't making software developers dramatically more productive, but it is solving two of their problems: code quality and morale, said a general partner at Andreessen Horowitz. Martin Casado, who leads the $1.25 billion infrastructure fund at a16z, said on an episode of the "Twenty Minute VC" podcast published Monday that AI coding tools like Cursor aren't supercharging development speed. "Every company I work with uses Cursor," said Casado, who is also an investor in the AI coding startup. "Has that increased the velocity of the products coming out? I don't think that much." "The things that are hard remain really hard," Casado said. This is especially so for infrastructure companies, where developers still need to make core architectural decisions and trade-offs that AI can't handle. Where AI shines, he said, is in eliminating the drudge work for developers: writing tests, generating documentation, and cleaning up messy code. AI can help create "more robust, maintainable code bases with less bugs," the longtime infrastructure investor said. "It could really help with the development process." Casado also said AI tools have made coding feel fun again, especially for longtime developers. The investor said he uses Cursor to handle finicky processes like setting up infrastructure or picking the right software packages, which lets him "focus on what I want and the logic." "It's almost like it's brought coding back," he said. "These old systems programmers, like, you know, vibe coding at night just because it's become pleasant again." Casado and a16z did not respond to a request for comment from Business Insider. AI empowering '100x engineers'? Agentic AI coding tools have taken over much of software engineering, writing code for developers, sometimes with minimal human editing necessary. Tech leaders have been vocal about the productivity boost. Surge AI's CEO, Edwin Chen, said the era of "100x engineers" is here. "Already you have a lot of these single-person startups that are already doing $10 million in revenue," Chen said on a recent episode of the "Twenty Minute VC" podcast. "If AI is adding all this efficiency, then yeah, I can definitely see this multiplying 100x to get to this $1 billion single-person company." "It often just removes a lot of the drudgery of your day-to-day work," Chen said. "I do think it disproportionately favors people who are already the '10x engineers.'" But some industry leaders said the AI coding hype comes with trade-offs. GitHub's CEO, Thomas Dohmke, said using AI coding tools might slow down experienced engineers. On a podcast episode released in June, he said a worst-case scenario is when a developer is forced to provide feedback in natural language when they already know how to do it in a programming language. That would be "basically replacing something that I can do in three seconds with something that might potentially take three minutes or even longer," Dohmke said. OpenAI's cofounder Greg Brockman also said using these tools has stuck humans with the less enjoyable parts of coding. He said the state of AI coding had left humans to review and deploy code, which is "not fun at all."

Exclusive: Loan servicing startup Salient raises $60M Series A
Exclusive: Loan servicing startup Salient raises $60M Series A

Axios

time19 hours ago

  • Business
  • Axios

Exclusive: Loan servicing startup Salient raises $60M Series A

Salient, a San Francisco-based platform for lenders to automate the post-loan origination process, raised $60 million in Series A funding, it tells Axios Pro exclusively. Why it matters: Loan servicing remains highly manual, but banks are increasingly doubling down on tech in the area. Andreessen Horowitz led the round, joined by Matrix Partners, Michael Ovitz and Y Combinator. By the numbers: The deal values Salient at $350 million, Axios has learned. The company's annualized run rate was north of $14 million as of June 2025, some 18 months after its launch. Context: This comes as U.S. household debt hit $18.2 trillion in the first quarter, with 4.3% of that delinquent — the highest level in five years, according to the New York Fed. How it works: Salient uses generative AI to automate collections, customer service, and compliance monitoring — acting as a dashboard for lenders to track all their loans. Currently, "[lenders] have huge outsource firms that run compliance functions or call centers," says CEO Ari Malik. "What we're trying to offer is a more transparent way of seeing what's happening. Because if you outsource this whole process, oftentimes, lenders have no idea what's going on." Salient uses voice recognition to monitor customer service calls and flag violations of complex state or federal lending rules. For example, active service members are entitled to interest rates of 6% or below, and customers who wish to no longer be called must be marked. Failures can lead to steep fines. In addition to customer service, Salient's AI agent, with additional information from the customer, can complete insurance claims and get necessary paperwork from the lender — cutting down on time and complexity. Salient counts Westlake Financial and AutoNation among its customers. Zoom out: Malik is betting this automation can improve lender and customer experiences. "[The AI agent] needs to be predictive as to what the customer wants," he says. "Success is: 'Can you predict what they actually want to interact with you about, as opposed to starting everything from scratch?'"

4Why RIAs Signal a New Era
4Why RIAs Signal a New Era

Int'l Business Times

timea day ago

  • Business
  • Int'l Business Times

4Why RIAs Signal a New Era

In the last few years, several marquee venture firms have quietly rewritten their charters by registering as investment advisers. Lightspeed, which now oversees about $31 billion, completed the switch in May 2025, following Andreessen Horowitz, General Catalyst, and others. The change looks technical, but its effect is anything but. An RIA designation liberates firms from the classic venture mandate of "Series A or bust," letting them buy public shares, participate in secondaries, and structure full buyouts. Andrew Medjuck, head of the alternative investment division at the Medjuck Family Office, calls it "a reset on what venture capital can actually do," replacing the wait-and-see posture with an ability to shape outcomes directly. The timing is no accident. AI is outpacing the decade-long venture clock. Product cycles are collapsing, incumbents are vulnerable, and the best returns now sit where software and operating control meet. By adopting the RIA playbook, top firms can chase value wherever it emerges—whether that is a minority position in a fast-growing SaaS platform or outright ownership of a 50-year-old services business calling for an AI retrofit. From Passive Bets to Active Builders Traditional VC portfolios live or die by a few outliers. In 2024, investors closed roughly 15,260 deals, yet only a small fraction delivered consequential exit. The hybrid model flips that risk curve. Instead of scattering seed checks, investors hunt for profitable companies with sticky customers, durable cash flow, and rich data exhaust—elements private equity has prized for decades. Medjuck argues that buying control and injecting AI into workflows "isn't just faster adoption, it's expanding the total addressable market from software spend to labor spend." Evidence is already visible. General Catalyst's proposed acquisition of a regional hospital network is designed to rebuild back-office functions with AI triage and revenue-cycle automation. Thrive Capital, meanwhile, raised a vehicle aimed exclusively at roll-ups where language models can compress compliance or claims-processing headcount by double digits. These moves mirror a broader trend: global secondary transaction volume hit a record $162 billion in 2024, a 45 percent jump year over year, as investors sought larger, more complex slices of mature assets. Operationally, the hybrid strategy borrows private equity's rigor—90-day integration plans, KPI dashboards, and incentive structures—but keeps the venture taste for asymmetry. By owning the whole stack, firms can refactor pricing, swap fixed labor for elastic compute, and capture margin expansion that a minority stake could never access. AI, Data, and the New Economics of Value Why is this model surfacing now? First, labor is the single largest line item in knowledge industries. Legal services alone represent an estimated $890 billion global market, most of it tied to billable hours. Replace even 15 percent of that work with AI drafting and review, and the savings dwarf the entire annual spend on legal software. Second, proprietary datasets inside legacy firms create moats that generic AI tools cannot match. A compliance shop with decades of transaction logs can fine-tune models its rivals cannot replicate. The prize is huge. PwC pegs private equity's current overhang of unsold assets at around $1 trillion. Much of that capital is sitting in companies where revenues are solid but margins are thin. Overlaying AI to remove manual reconciliation, underwriting, or intake work can double or triple free cash flow without a single new customer. That uplift is why Medjuck sees AI "resetting the economics" in labor-heavy fields like healthcare, insurance, and accounting. Crucially, defensibility in a commoditizing tech stack now relies less on code complexity and more on distribution rights, regulatory licenses, and exclusive data rights. Owning the corporate entity secures all three simultaneously. Where software-only startups struggle to unseat entrenched vendors, a buy-and-transform approach lets investors control pricing, embed AI deeply, and pocket the full delta between pre- and post-transformation margins. Benchmark partner Sarah Tavel sums up the shift in her essay "AI Startups Sell Work, Not Software," arguing that language models are already selling finished tasks and progressively climbing the value chain of knowledge work. LLM-powered startups begin at the low end—simple transcription, basic copyediting—but every new model release lets them automate more complex tasks, eating into the higher end of professional services. Investors that own operating assets instead of mere software licenses can capture that compounding efficiency directly, rather than ceding it to customers or vendors. What Leaders Should Watch For executives running incumbent businesses, the message is clear. The capital knocking on your door is no longer just looking to buy a minority stake; it wants to reinvent your operating model. That can feel threatening, yet it also offers a path to leapfrog slower rivals. Leaders should ask three questions: Where can AI substitute knowledge work within 12 to 24 months? Early wins in claims triage, document review, or patient scheduling can fund broader change. What proprietary data or regulatory positions make our company uniquely valuable? These assets grow in importance as AI commoditizes surface-level capabilities. Are we prepared for an owner who will measure success in margin points, not just revenue multiples? PE-style governance brings weekly dashboards and a bias for decisive action. For investors, the opportunity is still in its early innings. The secondary market's rapid growth signals mounting appetite for liquidity inside long-held private assets, providing elegant entry points without auction-level pricing. At the same time, the number of SEC-registered advisers climbed to nearly 15,900 in 2024, underscoring how quickly capital allocators are embracing a multistrategy posture. Medjuck predicts the biggest economic shift will be a realignment of labor and capital. "Capital will flow more actively into operational assets, not just ideas. Labor will shift from human-executed to AI-orchestrated." In practice, that means fewer nine-figure funding rounds for pre-revenue apps and more eight-figure buyouts of profitable service providers ripe for automation. The winners will be the firms—and the management teams—willing to own infrastructure and rebuild it from within. The hybrid PE-VC model is not a fad. It is the logical answer to shorter innovation cycles, surging secondary liquidity, and AI's insatiable appetite for data and control. For leaders deciding whether to partner, sell, or compete, the clock is already ticking. The smartest money has raised the stakes, and the next decade's most compelling returns will come from those who take the entire table, not merely a seat.

Regulated But Not Restricted: Software Transformation Despite Compliance Barriers
Regulated But Not Restricted: Software Transformation Despite Compliance Barriers

Forbes

time5 days ago

  • Business
  • Forbes

Regulated But Not Restricted: Software Transformation Despite Compliance Barriers

In highly regulated industries, innovation is stuck in the past, running on 1990s-era technology wrapped in a 2020s coat of paint. In 2011, Marc Andreessen declared that software is eating the world. By 2023, Shyam Sankar observed that software had already eaten the world. But now, the question is: Is the world eating software? Software has become ubiquitous, as cloud, mobile, data, artificial intelligence (AI), and the Internet of Things (IoT) have fused into everyday life. But while software transformation is advancing at a breakneck pace when it comes to the mundane, it's stalling out in highly regulated industries like healthcare and finance, those that could benefit from progress the most. The average American interacts with software daily, almost hourly. Fitness trackers have evolved into medical devices, self-driving cars are rewriting mobility, and AI copilots are reshaping how we work. Software is no longer just eating the world—it is being consumed, regulated, and embedded into critical, real-world infrastructure. Yet, in highly regulated industries, innovation remains stuck in the past, running on 1990s-era technology wrapped in a 2020s coat of paint. Compliance constraints have slowed adoption, leaving industries like defense, finance, and healthcare struggling to integrate modern software-driven value into their core operations. Finding a productive way forward requires keeping the intent of regulation alive while making adjustments as needed. Enabling Software Transformation in Regulated Industries When faced with compliance barriers, most organizations take one of two counterproductive approaches: They either give up, assuming regulations make modern software practices impossible, or they try to shoehorn modern practices into legacy compliance frameworks. Instead of settling for 'no,' it can be beneficial to reframe the problem as 'yes, if.' What has to change for the desired outcome to be achieved? When it comes to outdated policies, it's sometimes possible to identify strategic modifications that maintain the intent of compliance while enabling progress. Regulatory frameworks are designed to protect against specific risks—for example, data protection laws safeguard consumer privacy. They're not meant to stifle innovation. If it's possible to make a business case for an exception, it may be possible to make a change. By addressing underlying concerns instead of mindlessly following outdated rules, transformation may be possible. Of course, there are limitations. While regulatory structures can be reframed, they can't be ignored completely. If you're an auto manufacturer, you build your cars to fit existing infrastructure—the roads and highways already available. You don't build a car that's so big and unwieldy, it doesn't fit on the road, and then insist to the government that the roads should be wider. In the same way, regulated industries must focus on being fit for purpose as they innovate, rather than innovating for innovation's sake. Small Changes Can Mean Big Impact Ultimately, the question isn't whether software can transform highly regulated industries—it undoubtedly can. It's whether these industries, given their regulatory constraints, can consume and adapt to software at the speed of relevance. The world demands trustworthy, scalable, and compliant platforms, but are we truly prepared for the next wave of software-driven transformation? Until we find ways for highly regulated industries to innovate more freely, software transformation will stagnate in these areas, meaning untapped potential and missed opportunities for security, efficiency, and potentially life-saving innovations.

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