START

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START is a business podcast hosted by Fondo, with 115 episodes on record and a Required Pod Score of 80.

Fondo hosts START, a business show with 115 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #173

  START: Sam Mathew, CTO & Co-Founder, twentyfour26: "On Demand CNC Prototyping"

  Oct 2, 202610 min

  Wait two weeks to find out a part doesn’t work. Then wait two more weeks to try again. Sam Mathew knows what that does to a builder. He started in hardware. During COVID, he switched to software because he couldn’t get parts. Slow iteration wasn’t just costing him time. It was discouraging him from building hardware. Now he’s back, making parts for other builders. twentyfour26 manufactures metal parts in San Francisco for robotics and consumer hardware startups. But it didn’t start as a machine shop. Sam and his co-founder, Hemant Mahendru, were building software for manufacturers. Selling it was hard. So on the first day of Founders Inc., they changed the business: instead of selling software to manufacturers, they became one and started taking orders themselves. Their approach is deliberately focused. Rather than trying to manufacture everything, they standardize the machine, materials, tools and workholding around a narrower set of parts. Their software handles quoting and programming, and they run production themselves. Upload a STEP file. The software checks whether the design fits their setup, flags anything that needs changing, and turns accepted designs into a quote and machining plan. When the part fits and capacity allows, they can cut it the same day. For a hardware team, that’s more than a shorter delivery time. It changes how often they can test a design, learn what’s wrong and try again. The obvious cost of waiting is a delayed prototype. The less obvious cost is a builder deciding to work on something else. Sam’s building for the people who want to stay in hardware. "Send CAD. Get metal." ️ Sam Mathew , CTO & Co-Founder, twentyfour26 on Fondo START 01:57 Making new toys from old ones 02:22 Dropping out in 10th grade to build an edtech startup 04:05 The outdated spreadsheet that sparked the company 04:43 Lessons from their first YC interview 05:18 Pivoting from manufacturing software to making parts 06:00 Turning CAD files into metal parts 06:28 Why faster access to parts matters for hardware builders 06:52 The cost of waiting between prototypes 07:35 The practical reason Sam shaved his head 07:48 How a seed-round joke became a viral video ‍ Check out twentyfour26.com

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  Episode #156

  START: Dekai Li, CTO & Co-Founder, Trident "Autonomous offensive security agents."

  Oct 1, 202612 min

  ️ Dekai Li Co-Founder & CTO, Trident on Fondo START ‍ Check out tridentsecurity.io

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  Episode #176

  START: Ryan Nowicki Stewart, CEO & Co-Founder, Pennant: "The Corporate Governance OS for Public Markets"

  Sep 30, 202611 min

  The earnings call gets the headlines. The shareholder vote can change the company. CEO compensation. Board control. Major corporate transactions. Some of the biggest decisions at public companies are shaped through shareholder votes - but most people never see the work behind them. Ryan Nowicki Stewart spent years inside that process. At State Street, he met with boards and C-suites and helped the firm arrive at voting decisions as a major institutional shareholder. Later, at PJT, he sat on the other side of the table, advising companies navigating those same investors. And behind a single decision could be thousands of pages of SEC filings, third-party research and years of internal notes. Ryan describes the workflow as “a total patchwork.” So he and his co-founder Tommy - who he’s known since undergrad and started alongside at BlackRock - built Pennant. Pennant is building the corporate governance OS for institutional investors. The platform brings meetings, filings, proposals, voting policies and decision records into one place - helping teams analyze and coordinate proxy voting, apply their own principles at scale and maintain a clear record of how decisions were made. And because Ryan and Tommy spent years working with the exact people they’re now building for, their product bar is simple: Would our former bosses and teammates use this day in and day out? That mindset has shaped how they build. Instead of guessing what customers need, the Pennant team spends time on the desk with institutional investors, starts with their biggest problem and builds from there. Know the workflow deeply enough, and your former job can become your startup’s unfair advantage. ‍ ️ Ryan Nowicki Stewart , CEO & Co-Founder, Pennant on Fondo START ‍ 00:57 From BlackRock and State Street to building Pennant 01:27 The hidden governance layer behind public companies 02:05 Meeting Tim Cook as Nike’s compensation committee chair 03:47 How boards think about CEO pay and incentives 05:42 Why shareholder voting matters to institutional investors 06:08 The thousands-of-pages “patchwork” Pennant is replacing 07:18 Building software their former teammates would actually use 08:17 Why Pennant starts with each client’s biggest problem ‍ Check out getpennant.ai

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  Episode #168

  START: Sky Yang, CEO & Co-Founder, Imagine AI "Reverse engineer B2B growth, starting with LinkedIn.

  Sep 29, 202615 min

  Most companies ask what they should post on LinkedIn. Sky Yang is focused on a more valuable question: How does all that activity actually translate into growth? At Imagine AI, his team is treating LinkedIn less like a content calendar and more like a measurable growth system. They study how content performs, who it reaches, and how those interactions connect back to prospects and the deal cycle—then use that data to help companies make better decisions about what to say and who should say it. It starts before a post is ever written. Imagine AI works with companies to define their strategy, positioning, audience, differentiation, and KPIs. That becomes context the agent can use to create content grounded in what the company is actually trying to accomplish. Then Sky looks at distribution differently. A founder, company account, and growth leader each have their own network. Imagine AI uses that to help companies reach more of the people they actually want to reach instead of relying on a single account to carry the entire strategy. And it doesn’t stop at engagement. Imagine AI integrates with CRM data so teams can map content interactions to prospects and follow those touchpoints through different stages of the deal cycle. With enough data, the goal is to build a clearer picture of which content decisions are contributing to revenue. His team has studied how LinkedIn engagement is distributed and is building around the parts companies can make more intelligent. Imagine AI is taking LinkedIn from “we should probably post more” to a data-driven growth system companies can actually learn from. ‍ ️ Sky Yang , CEO & Co-Founder, Imagine AI on Fondo START ‍ 01:12 Imagine AI’s data-driven approach to LinkedIn 01:43 The data behind why some LinkedIn posts take off 02:37 Building content from strategy and positioning 04:08 Reaching more of the right audience through your team 06:18 Connecting content engagement to CRM and revenue 08:47 Why Imagine AI is going deep on LinkedIn 10:42 Using AI to surface the DMs that actually matter 11:54 Relationship data, repeated touchpoints, and smarter outreach 14:03 Sky’s advice for growing on LinkedIn Check out at imagineai.me

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  Episode #175

  START: Silen Naihin, CTO & Co-Founder, Experiential Labs: "Open source AI gateway that turns your traffic into a model you own"

  Sep 28, 202614 min

  Every AI model. One key. Zero markup. That’s the starting point. The bigger ambition: help companies turn their AI traffic into better models they own Silen Naihin helped grow AutoGPT to 160,000 GitHub stars. Now, at Experiential Labs, he’s working to bring model access, evaluation and training into one unified experience. The open-source gateway gives companies control over model access. From there, the team is building simulations around their traffic to understand different workloads and recommend models based on three things: cost, quality and speed. The goal goes beyond choosing a model. It’s helping companies evaluate performance and train specialized models around their own work when they need them. Silen expects agents to do most of the work. So the product has to serve both: humans who need to understand what’s happening and agents that need to use it. Start with access. Build toward ownership. "The open source AI gateway. Hosted providers, your own keys, and your own GPUs behind one endpoint, at the provider's price." ‍ ️ Silen Naihin , CTO & Co-Founder, Experiential Labs on Fondo START 02:51 Going off the beaten path: TKS, Minerva & dropping out 03:37 Getting into YC & the research behind Experiential Labs 05:00 From 8 H100s and continual learning to building a company 05:58 Why every company will become an AI company 06:42 Cost, quality & speed: the “holy trinity” of AI models 07:00 When fine-tuning beats prompting 08:14 What happens when powerful AI gets incredibly cheap 09:00 Why the future could be a model—or LoRA—per customer 10:00 Open-source models get the tokens; closed models get the spend 10:27 Jevons paradox, DeepSeek & exploding AI usage 11:06 Why OpenAI and Anthropic aren’t the next Yahoo 13:05 Experiential Labs’ bigger vision beyond the AI gateway 13:45 Building AI infrastructure for humans and agents 14:01 Optimizing models across cost, quality & speed Check out experientiallabs.ai

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