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Good morning, afternoon, and good evening, investor! Scott Carson here, ready to tackle the burning questions in the note investing world. I went straight to the source – Google's Gemini AI – and asked for the 20 most frequently asked questions by note investors. And let me tell you, AI did not disappoint! Since so many new folks want to jump into the "sexy side of real estate," I'm breaking down these essential FAQs to help you act like the bank, not the pawn.If you've ever wondered how much cash you really need, whether you own the property (spoiler: you don't!), or how to avoid common pitfalls, this episode is your no-nonsense guide. As I always say, the pen is mightier than the hammer, and these insights are your ultimate toolkit for 2026.Here's your AI-powered cheat sheet to note investing:Note Investing 101: The Basics & Beyond: What's a real estate note? (It's an IOU, baby!). What's the difference between performing, non-performing, and "scratch & dent" loans? And seriously, how much money do you actually need to start? (Hint: it can be less than you think!).Yields, Values & Spreads (No, Not Butter): Unpack what constitutes a "good yield" for performing (9-12%!) and non-performing notes (20%+!). Learn about Investment-to-Value (ITV), Unpaid Principal Balance (UPB), and how to calculate your true return so you're not paying too much for the paper.Due Diligence Decoded (Without Owning the House!): Master the art of checking property condition (BPOs!), title (O&E reports!), and borrower payment history (servicing notes!). Plus, the absolute non-negotiables: collateral files and an unbroken chain of assignments – essential to avoid a "dud" deal.Operations & Management: Who Ya Gonna Call? (Not the Borrower!): Understand why you never call the borrower yourself (it's illegal, buddy!). Learn how servicers manage payments, what happens if a borrower stops paying (loan modifications, cash for keys, foreclosure!), and who's really on the hook for property taxes.Funding Your Future: IRAs & Beyond: Discover how Self-Directed IRAs are a game-changer for note investors, allowing tax-free or deferred growth. Learn about "cash for keys" as a smart exit strategy to avoid costly foreclosures, and why a clear plan beats wishful thinking every time.Whether you're a seasoned pro or just dipping your toes into the "paper investing" world, these 20 FAQs are fundamental. Don't be that person who learns the hard way because they didn't ask. Take action, get educated, and start acting like the bank. Because in the note world, being smart with your debt can make you a whole lot of dough!Want to learn more? Head over to weclosenotes.com, keep listening to the podcast, or sign up for our next workshop at notebuyingfordummies.com. Go out, take some action, everybody, and we'll see you at the top!#NoteInvesting #RealEstateInvesting #NoteInvestingFAQs #AIinRealEstate #PerformingNotes #NonPerformingNotes #DueDiligence #SelfDirectedIRA #CashForKeys #Foreclosure #InvestmentStrategy #RealEstateEducation #PodcastWatch the Original VIDEO HERE!Book a Call With Scott HERE!Sign up for the next FREE One-Day Note Class HERE!Sign up for the WCN Membership HERE!Sign up for the next Note Buying For Dummies Workshop HERE!Love the show? Subscribe, rate, review, and share!Here's How »Join the Note Closers Show community today:WeCloseNotes.comThe Note Closers Show FacebookThe Note Closers Show TwitterScott Carson LinkedInThe Note Closers Show YouTubeThe Note Closers Show VimeoThe Note Closers Show InstagramWe Close Notes Pinterest
What happens when voice AI stops being a demo — and becomes something contact centers can trust? In this episode, Hakob Astabatsyan, Co-Founder & CEO of Synthflow AI, breaks down how memory-enabled voice agents reduce AHT, lift FCR, and eliminate repetitive customer conversations. Synthflow now runs millions of calls with sub-second latency, a reliability engineering culture, and a memory framework built for regulated industries. We explore the point where voice AI transitions from novelty to enterprise infrastructure: real-time interruption handling, multi-turn context retention, deterministic guardrails, HIPAA/GDPR compliance, and the orchestration pipelines that make AI feel natural instead of artificial. Our sponsor:
Nick Jiwa is the founder and president of CustomerServ. He is based in Houston, Texas, USA. In this episode Nick talks to Peter Ryan about the importance of people in CX - in particular in BPOs. He asks why people have always been central to the customer experience, but now it sounds like everyone is just focused on AI and automation? It's time to refocus on people and culture because this is how brands connect with customers and this leads to the success they need - extra revenue, loyalty, retention etc... https://www.linkedin.com/in/nickjiwa/ https://www.customerserv.com/ The Call Center – Still a People Business (Nick Jiwa - Aug 12, 2025) https://www.linkedin.com/pulse/call-center-still-people-business-nick-jiwa-sn5lf/ Summary: Mark Hillary and Peter Ryan discuss the importance of human interaction in customer experience (CX) with Nick Jiwa, founder of CustomerServ. Jiwa emphasizes that despite technological advancements, CX remains a people-centric industry. He criticizes large BPOs for prioritizing tech over people, noting that many have an identity crisis. Jiwa highlights the resilience of the call center industry, projecting its growth from $300 billion to $500 billion by 2030. He argues that AI will enhance, not replace, human roles, particularly in emotional and complex interactions. The conversation underscores the need for a refocus on people, culture, and leadership in CX.
After 20+ years at some of the most important Silicon Valley tech companies like Yahoo, LinkedIn, Oracle, Informix and NerdWallet, Bhaskar today leads investment of enterprise infrastructure companies at 8 VC.Bhaskar Ghosh spent 20+ years at some of the most important Silicon Valley tech companies before moving into venture capital as a Partner at 8VC.After completing his PhD in computer science from Yale, he worked across Yahoo, LinkedIn, Oracle, Informix and NerdWallet. He brings this experience to founders building the next generation of enterprise infrastructure companies.In this episode Bhaskar explains how IT services are being reimagined for India, a country that over the last 25 years turned its skilled workforce into a global services engine. We discuss the shift happening inside workflows most people do not think about: mid-office ops, call centers, insurance, travel and HR. These are areas where thousands of people move information every day, and where AI is now good enough to take over entire workflows.Bhaskar talks about the founders already building in this space, including those buying traditional services companies and rebuilding them with AI at the core. He also explains why this new wave will not behave, scale or be valued like SaaS, because this is no longer pure software. It is the reinvention of services.If you are a founder making engineering decisions, someone curious about the less visible layers of software, or interested in people who move technology forward, this conversation with Bhaskar is for you.00:00 –Trailer03:03 – How India will reimagine IT services (TCS, Infosys)04:32 – “why now” of services06:07 – How unstructured data became easier to handle?07:53 – What LLMs can do today with high precision10:35 – Use of GenAI will increase margins in services11:54 – Front & mid offices will become more productive and lean14:30 – Will a pure services business scale anymore?15:55 – Legacy service businesses + AI-first software20:04 – Real challenge to operate and scale such businesses20:33 – 3 reasons on why SaaS companies get higher multiples?22:06 – Network-effect players win big in SaaS24:18 – Replacing software v/s replacing services26:16 – Business without inherent network effects (yet)28:22 – Is AI unlocking TAM larger than Software era?30:57 – How prosperity of a country influences growth of Co's32:50 – India's tech talent is key to India-US corridor39:36 – Deeply disruptive AI Co's will come from India43:04 – How new-age AI services companies of India should grow in US?44:39 – Current BPOs have an unfair advantage47:21 – Will older BPOs understand the importance of AI?49:22 – A Moat in outcome-based pricing can replace old businesses51:50 – Has the US ever been sensitive to cost?55:23 – The new AI-enabled services have a Palantir-risk flavour58:47 – Where to build when model Co's eat forward & backward revenue?01:06:10 – What type of founding teams are needed?01:08:10 – How founders think about GTM is changing-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonSend us a text
I see business owners make the same mistake over and over—they chase “cheap outsourcing” and end up paying way more than they should.
Gerry Brown is known as the customer lifeguard. His ambition is to save the world from poor customer service. Gerry is Canadian and based in the south of the UK. Gerry has written a book titled 'When a customer wins, nobody loses.' He has a podcast and he is a regular speaker and adviser, regularly hosting CX workshops. Mark called Gerry to ask about his book and the post-pandemic CX environment. In particular how can BPOs get more closely aligned with the needs of customers when AI is changing the entire industry? https://www.linkedin.com/in/gerryhbrown/ https://thecustomerlifeguard.co.uk/ https://www.amazon.co.uk/When-Customer-Wins-Nobody-Loses-ebook/dp/B07BFC83MZ/ Summary : Mark Hillary and Peter Ryan discuss the evolving landscape of customer experience (CX) with guest Gerry Brown, an independent consultant and author of "When a Customer Wins, Nobody Loses." They explore the shift from traditional customer service to more complex, multi-channel environments, including the rise of AI and automation. Brown highlights the importance of aligning customer needs with BPO services, noting that many organizations still handle customer service in-house. He emphasizes the need for BPOs to offer comprehensive solutions and the growing use of AI for efficiency and cost savings. The conversation also touches on the impact of the pandemic on remote work and the ongoing challenge of integrating legacy systems.
Paul O'Hara is the Executive Vice President of Business Development at TP EMEA. He is based in the Tyneside area of North-East England. Paul recently published an article on Customer Think magazine titled "AI Won't End BPO - It'll Supercharge It." Mark called Paul to ask Paul about the article. What was Paul trying to say? How does he believe that AI and human-focused customer service can be blended? How can smarter more value-driven CX be planned using AI? Paul outlined many of these ideas in his article, but Mark questioned him further on the reasons he felt the need to talk about AI in this way. Mark even mentioned this conversation with Paul in a SubStack article he published earlier this week. https://www.linkedin.com/in/pauloharateleperformance/ https://customerthink.com/ai-wont-end-bpo-itll-supercharge-it/ https://www.tp.com/ https://markhillarysp.substack.com/p/ai-in-customer-service-isnt-about Summary: Mark Hillary and Peter Ryan discuss the impact of AI on Business Process Outsourcing (BPO) with Paul O'Hara, EVP for Business Development at Teleperformance (TP). O'Hara argues that AI will enhance, rather than replace, BPO services. He emphasizes the importance of blending AI with human expertise to deliver smarter, scalable, and value-driven customer experiences. O'Hara highlights that BPOs, with their operational backbone and regulatory compliance, are better positioned to design and scale CX solutions. He predicts continued growth in the BPO industry, driven by automation and ethical outsourcing, and stresses the need for performance-based models over traditional metrics.
Outsourcing podcast Get the full show notes for this outsourcing podcast here: outsourceaccelerator.com/561 Monday.com In this episode of the Outsource Accelerator Podcast, Nir Yamin from monday.com shares how the platform has become a cornerstone for the modern BPO industry. From flexible workflows to AI-powered tools, Nir explains how monday.com helps outsourcing firms streamline operations, improve visibility, and prepare for the next era of tech-enabled outsourcing. References: Website: https://monday.com/lang/en-ph/?utm_source=outsourceaccelerator.com&utm_medium=article LinkedIn: https://www.linkedin.com/in/niryamin?originalSubdomain=au Start Outsourcing Outsource Accelerator can help you transform your business with outsourcing. Get in touch now, or use one of the resources below. Business Process Outsourcing Get a Free Quote - Connect with 3 verified outsourcing experts & see how outsourcing can transform your business Book a Discovery Call - See how Outsource Accelerator can help you enhance your company's innovation and growth with outsourcing The Top 40 BPOs - We have compiled this review of the most notable 40 Business Process Outsourcing companies in the Philippines Outsourcing Calculator - This tool provides you with invaluable insight into the potential savings outsourcing can do for your business Outsourcing Salary Guide - Access the comprehensive guide to payroll salary compensation, benefits, and allowances in the Philippines Outsourcing Accelerator Podcast - Subscribe and listen to the world's leading outsourcing podcast, hosted by Derek Gallimore Payoneer - The leading global B2B payment solution for the outsourcing industry About Outsource Accelerator Outsource Accelerator is the world's leading outsourcing marketplace and advisory. We offer the full spectrum of services, from light advisory and vendor brokerage, though to full implementation and fully-managed solutions. We service companies of all sectors, and all sizes, spanning all departmental verticals. Outsource Accelerator's unique approach to outsourcing enables our clients to build the best teams, access the most flexible solutions, and generate the best results possible. Our unrivaled sector knowledge and market reach mean that you get the best terms and results possible, at the best ALL-IN market-leading price - guaranteed.
This week Scott reviews another tape of assets from a new provider. Buckle up your boot straps and hold on tight for this thrill ride of reverse mortgage notes. Scott dives into the map and spreadsheet, outlining the positives and negatives of the assets, giving tips along the way!Illinois Foreclosure This state takes longer to foreclose on!Manufactured Homes with far comps: How accurate are BPOs with far comps?REO and foreclosure When do you fix up and when do you flip?Days on Market How can you get a good price for an asset in a slower market?Max Claim What exactly is the max claim?Redemption Period and Foreclosure in the same sentence! This one is for the pros that are the most patient of note investors that are prepared for some possible litigation with estate holders!Manufactured Homes at high BPO's These assets are out in the middle of nowhere with comps from 20 miles away.Elderly Owners: Reverse Mortgages require owners that are 65 years or older, you are potentially foreclosing on grandma!HUD Claims: What is the HUD Max Claim?The Seller. This is not Scott's usual seller, so expect surprises when working with a new provider.Whether you're a seasoned investor or new to real estate note investing, it can be a challenge so grab your education to get the right start.Watch the Original Video Here!Book a Call With Scott HERE!Sign up for the next FREE One-Day Note Class HERE!Sign up for the WCN Membership HERE!Sign up for the next Note Buying For Dummies Workshop HERE!Love the show? Subscribe, rate, review, and share!Here's How »Join the Note Closers Show community today:WeCloseNotes.comThe Note Closers Show FacebookThe Note Closers Show TwitterScott Carson LinkedInThe Note Closers Show YouTubeThe Note Closers Show VimeoThe Note Closers Show InstagramWe Close Notes PinterestGet signed up for the Next Virtual Note Buying Workshop Now!
This week, Scott reviews another tape of assets from a new provider. Buckle up your boot straps and hold on tight for this thrill ride of reverse mortgage notes. Scott dives into the map and spreadsheet, outlining the positives and negatives of the assets, giving tips along the way!Illinois Foreclosure This state takes longer to foreclose on!Manufactured Homes with far comps: How accurate are BPOs with far comps?REO and foreclosure When do you fix up and when do you flip?Days on Market How can you get a good price for an asset in a slower market?Max Claim What exactly is the max claim?Redemption Period and Foreclosure in the same sentence! This one is for the pros that are the most patient of note investors that are prepared for some possible litigation with estate holders!Manufactured Homes at high BPO's These assets are out in the middle of nowhere with comps from 20 miles away.Elderly Owners: Reverse Mortgages require owners that are 65 years or older, you are potentially foreclosing on grandma!HUD Claims: What is the HUD Max Claim?The Seller. This is not Scott's usual seller, so expect surprises when working with a new provider.Whether you're a seasoned investor or new to real estate note investing, it can be a challenge so grab your education to get the right start.Watch the Original Video Here!Love the show? Subscribe, rate, review, and share!Here's How »Join Note Night in America community today:WeCloseNotes.comScott Carson FacebookScott Carson TwitterScott Carson LinkedInNote Night in America YouTubeNote Night in America VimeoScott Carson InstagramWe Close Notes PinterestGet signed up for the Next Virtual Note Buying Workshop Now!
Most recruitment firms stall at $1M revenue. Greg Fischer broke through by building a high-retention offshore team, embedding himself inside client organizations with RPO, and using LinkedIn commenting as a smarter BD strategy. As Co-Owner of AMI Network, Greg scaled from $1M to $4.2M revenue and $1.4M profit sustaining 30–40% margins. His model: hire offshore staff directly, integrate them as equals, and use a 2:1 sourcer-to-recruiter ratio to free recruiters to bill more. Alongside that, he mastered RPO pricing, transforming a $30K placement into a $1.5M account. Today, as founder of Well Oiled Machine, Greg helps other firms replicate this approach. In this episode, he shares how to structure offshore teams for 85%+ retention, qualify RPO opportunities, and win clients through LinkedIn commenting. Episode Outline and Highlights 6:42 From solo founder's first hire to 40-person team. 7:40 Breaking the $1M ceiling with offshore hiring after failed BPOs. 12:37 Why sourcing was the first offshore function and how it lifted billings. 23:18 Landing a $50K/month RPO by reframing a client's hiring challenge. 28:07 How that grew into an $80K/month RPO account with 30–40% margins. 30:45 When to pitch RPO: the minimum job volume that makes it viable. 33:47 The “open + close” fee model that stabilized cash flow. 36:23 How a 2:1 sourcer-to-recruiter ratio frees recruiters to bill more. 39:08 Why most agencies fail with offshore—and how to do it right. 47:19 Choosing the right country: Mexico vs Philippines vs South Africa. 54:51 Greg's daily LinkedIn commenting routine that built an inbound pipeline. Key Takeaways Offshore Done Right Fuels Scale Greg's agency was stuck at $1M for four years. BPOs failed, freelancers flaked. The breakthrough came when he hired offshore staff directly, trained them thoroughly, and treated them as equals. Within three years, AMI scaled to $4M+ revenue with 30–40% profit margins and 85% retention. Offshore wasn't a cheap fix; it was the lever that freed recruiters to focus on revenue-driving work. The RPO Question That Unlocks Recurring Revenue A referral asked for an internal recruiter. Greg's partner asked: “Why now?” The answer—50 hires in six months—turned a $30K placement into a $50K/month retainer that ran three years, worth $1.5M. His rule: RPO only works with 5–10 requisitions/month and $15K+ revenue. Anything less is contingent search. Over time, he moved to an “open fee + closed fee” model that kept revenue flowing and profit margins at 30–40%. LinkedIn Strategic Commenting Works Greg built AMI Network through cold outbound. For Well Oiled Machine, he went another route: commenting daily on posts from 60 recruitment thought leaders. Thirty minutes before posting, thirty minutes after. The results? Comments hitting 20,000+ impressions—often outperforming original posts. On LinkedIn, comments are content, and for agency owners this is a repeatable, low-cost BD strategy that beats cold calling. Greg Fischer Bio and Contact Info Greg is the former Co-Owner of AMI Network, a healthcare recruitment agency that did $1.4M in Profit on just $4.2M in revenue. His secret? 18 of his 40 team members were Offshore high-performing employees, with annual retention over 85%. Now his firm, Well Oiled Machine recruits Offshore & Nearshore staff for Recruitment Firms & Staffing Agencies. Greg Fischer on LinkedIn Well Oiled Machine website link Connect with Mark Whitby Get your FREE 30-minute strategy call Mark on LinkedIn Mark on Facebook Mark on Instagram: @RecruitmentCoach Subscribe to The Resilient Recruiter
In this episode of Business Ninjas, host Andrew Lippman chats with Matt Seefeld, EVP at MedEvolve. Matt shares his journey from consulting to healthcare entrepreneurship and how MedEvolve helps medical providers survive and thrive in today's margin-crushing environment. From skyrocketing costs and declining reimbursements to the complexity of revenue cycle management, Matt breaks down the realities of running a healthcare practice in 2025—and why automation alone won't save the industry.
Wayne Butterfield, partner at Information Services Group (ISG), joins Gadi Shamia, CEO and Co-Founder of Replicant, to unpack why legacy outsourcing models are on borrowed time, what separates the winners from the walking dead, and how outcome-based contracts and AI-native partnerships are defining the next decade of CX. If you're betting your contact center strategy on “mess for less,” this episode is your wake-up call.In this episode:Why CX outsourcing is broken and how most companies are still getting it wrongThe 3 types of BPOs in today's market, and which ones are built to survive the AI eraHow Amazon rewrote the outsourcing playbook with outcome-based contractsWhy “mess for less” is a dead-end strategy, and what replaces itThe rise of agentic AI and what it means for Tier 1 automationWhat CEOs need to know before green-lighting another call center deal
Cheryl Paarwater is the Managing Director at Enerlytics & Call Lab BPO. She is based in Cape Town, South Africa. Cheryl has championed CX in South Africa for many years and is a board member of BPESA - the trade promotion agency for business process service companies in South Africa. In this conversation with Peter Ryan, Cheryl explores how BPO and CX has created many opportunities for employment in South Africa - and beyond - and this has created a very positive socio-economic ripple effect. People leaving informal jobs and entering contact centers pay tax, support their family, and help to support other businesses selling services to those working directly in BPOs. As AI is gradually introduced in many CX processes, there is a fear in the industry that entry-level positions may no longer be staffed by humans. The most immediate effect is a reduction in the number of jobs created, but what are the wider effects of thinking that we can just replace people with bots? https://www.linkedin.com/in/cheryl-paarwater/ https://call-lab.com/ SUMMARY: Mark Hillary and Peter Ryan discuss the impact of artificial intelligence (AI) on customer experience (CX) jobs, particularly in South Africa. Cheryl Paarwater, CEO of Call Lab, highlights concerns about AI replacing human roles, which could exacerbate unemployment and social issues. Despite AI's potential to automate 10-15% of roles, Peter notes that many AI projects fail, citing a 42% failure rate in 2020. Cheryl emphasizes the need for AI to enhance human roles rather than replace them, suggesting AI could improve education and support high-value interactions. They stress the importance of a balanced approach to AI implementation in CX.
Looking to grow your career in customer service? Now could be a great time to explore new opportunities in Mohali's expanding job market.More information is available at https://www.ttecjobs.com/en/job/mohali/healthcare-customer-service-representative-english-voice/44028/81874690016 TTEC City: Austin Address: 100 Congress Avenue Website: https://www.ttecjobs.com/en
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What happens when AI meets the chaos of real-world customer support? In this episode of Eye on AI, we sit down with Ryan Wang, co-founder and CEO of Assembled, to unpack how AI is transforming the future of customer service, without replacing humans. Ryan reveals how Assembled went from a workforce scheduling tool to a full-stack AI support platform used by companies like Stripe, Robinhood, and Honeylove. You'll learn how conversational AI agents are handling up to 75% of support inquiries, why voice is the next big frontier, and how AI copilots are helping human agents become 15% more productive. But this isn't just hype. Ryan shares the hard economic truths behind automation—why humans aren't going away, how companies are navigating global workforce optimization, and why hybrid AI + human systems are here to stay. This episode gives you a front-row seat into how the smartest companies are rethinking support at scale. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Preview and Intro (01:37) Ryan Wang's Journey from Stripe to Assembled (04:55) Launching Assembled (09:49) From Scheduling Tool to AI-Powered Support (12:11) Who Uses Assembled: Companies vs. BPOs (14:57) Building Conversational and Voice AI Agents (21:10) Competing with Zendesk, Salesforce & Crescendo (23:07) How Assembled Integrates with Customer Support Stacks (25:40) The Niche Power of Workforce Management Tech (31:16) Why the Customer Support Market Is Ripe for Disruption (33:47) How Assembled Swaps Between OpenAI, Claude & Others (37:56) Evaluating LLMs with Golden Datasets and 'Vibe Checks' (41:20) Multilingual Support and the Challenge of Europe (45:11) Industry Focus vs. Complexity Focus (47:43) Voice AI: The Next Big Frontier? (50:18) The Truth About AI Replacing Jobs in Support (54:39) The Automation Paradox: Why Labor Isn't Shrinking
Amanda Quinn is the Founder and Principal of Quinn Growth Advisors. She is based in Raleigh, North Carolina, USA. In this conversation with Peter Ryan, Amanda talks about her work advising BPOs on how to build growth and develop a sales pipeline. Amanda advises focusing on deep expertise and specialization, rather than claiming to offer every single service and excelling at none of them. How can BPOs compete and leverage technology to improve what they offer to clients? https://www.linkedin.com/in/amandaquinnmalach/ https://quinngrowthadvisors.com/ SUMMARY: Mark Hillary and Peter Ryan discuss the challenges faced by BPOs (Business Process Outsourcing) in the market, emphasizing the need for specialization over generalism. They highlight the inefficiencies of BPOs claiming to offer a wide range of services without excelling in any. Amanda Quinn, founder of Quinn Growth Advisors, is introduced as a guest who advocates for BPOs to focus on niche markets and develop deep expertise. Quinn advises BPOs to identify their strengths through internal stakeholder meetings and client feedback, and to expand by adding related services or industries. She also stresses the importance of charging for value-added services and leveraging technology to enhance service delivery.
Tune into our weekly LIVE Mastermind Q+A Podcast for expert advice, peer collaboration, and actionable insights on success in the Probate, Divorce, Late Mortgage/Pre-Foreclosure and Aged Expired niches!In today's episode of the All The Leads Mastermind podcast the spotlight was on short sales, how they work, when to use them, and why they're making a comeback as late mortgage and distressed property leads rise. Special guest Pam shared insights from over 2,000 short sale transactions, explaining how agents can partner with experts to handle the complex back-end process while staying focused on listing and selling. The discussion covered key documentation, timelines, lender criteria, and how short sales differ from traditional negotiations, emphasizing that banks aren't looking for lowball offers but complete well-documented packages. The team walked through scenarios including probate, divorce, reverse mortgages, and foreclosure, highlighting how short sales can be a solution even weeks before a sale date. Listeners learned how Pam is compensated through buyer-side closing costs, how MLS listing requirements affect investor offers, and why acting early gives agents a huge advantage. The episode closed with a strong call-to-action: use the new submission form at alltheleads.com/shortsale to turn tough leads into closable deals with expert support.
Jon Florence is the SVP of Industry Solutions at Xima Software. He is based in South Jordan, Utah. Xima is a contact center software company that is focused on AI solutions. Peter Ryan called Jon to discuss AI in CX. Beyond the hype, how can companies managing their own CX and BPOs all benefit from the use of AI in the contact center? What are the genuine and practical use cases that move the dial and which claims are just hype? What can you really do with AI today? https://www.linkedin.com/in/jon-florence-67019a79/ https://ximasoftware.com/ SUMMARY: Mark Hillary and Peter Ryan introduce Jon Florence, SVP of Industry Solutions at Xima Software. Jon explains his role in integrating AI into customer experience solutions. They delve into the hype cycle of AI, comparing it to the VoIP boom, and emphasize the importance of understanding business needs before implementing AI. Jon advises starting with simple AI tools like speech analytics and messaging bots, and stresses the need for certified integrations. He also highlights the importance of testing AI capabilities and ensuring long-term vendor stability to avoid future consolidation issues.
In this episode of VUX World, we chat with Kellin Sjoerds and Ricky Wekker, Conversational AI Engineers at Essent - the Netherlands' largest utility provider and part of the E.ON Group to uncover the story behind their groundbreaking agent assist tool, Bolt.Bolt is an AI-powered agent copilot that has transformed Essent's call centre operations, shaving an average of 60 seconds off every call and delivering over €1.8 million in savings, not through layoffs, but by reducing dependence on BPOs.We unpack the full journey behind Essent's AI copilot, Bolt, starting with a simple observation during a team shadowing session that sparked its creation. What began as a hackathon MVP quickly turned heads, prompting leadership to ask, “How fast can we launch this?” From there, we uncover how the team tackled complex challenges like cleaning and restructuring their knowledge base, implementing a smart chunking system, and fine-tuning prompts to ensure accurate, reliable outputs. And through a carefully staged rollout, they struck the right balance between innovation and safety, navigating compliance hurdles while delivering impressive business value.Shownotes:Subscribe to VUX World: https://vuxworld.typeform.com/to/Qlo5aaeWSubscribe to The AI Ultimatum Substack: https://open.substack.com/pub/kanesimmsGet in touch with Kane on LinkedIn: https://www.linkedin.com/in/kanesimms Hosted on Acast. See acast.com/privacy for more information.
In this episode of Business Ninjas, host Andrew Lippman chats with Michael McGuire, Chief Revenue Officer at NobelBiz, a leader in omnichannel contact center solutions and carrier services. With over 30 years of experience running and fixing call centers, Michael shares why NobelBiz stands out in a crowded tech space: it's built by people who've actually lived the contact center life. From telecom cost savings and spam-call suppression to AI innovation and crisis-proof infrastructure, they unpack how NobelBiz helps companies future-proof customer experience and stay compliant in a fast-evolving landscape.
Summary In this conversation, Amas Tenumah and Bob Furniss discuss the intersection of sports fandom and the business of contact centers, particularly focusing on business process outsourcing (BPO). They explore the reasons companies choose to outsource their customer service operations, the challenges involved, and the evolving landscape of the BPO industry. The discussion emphasizes the importance of understanding core competencies, cost savings, and the need for competent consultants in the BPO space. Takeaways The NBA Finals can evoke strong emotions and rivalries. BPOs are third-party services handling customer interactions. Cost savings is the primary reason for outsourcing. Companies often outsource to focus on their core competencies. Successful outsourcing requires understanding what to delegate. BPOs can leverage scale and technology for efficiency. Choosing the right outsourcing partner is crucial. AI is changing the landscape of customer service. Consultants with deep contact center experience are valuable. The BPO industry is evolving to include more tech services. Chapters 00:00 NBA Finals and Personal Rivalries 01:15 Understanding BPOs and Contact Centers 02:26 The Decision to Outsource 03:35 Implementing Outsourcing Strategies 06:25 The BPO Industry's Shift to AI 08:07 Core Competencies in Outsourcing 10:52 Final Thoughts on BPO and Customer Care
If you live in Barranquilla, its business scene is changing fast and there is a wealth of new job openings coming up for sales development representatives that can speak English as well as Spanish.More information is available at https://www.ttecjobs.com/en/search-jobs/Barranquilla%2C%20Atl%C3%A1ntico/44028/4/3686110-3689436-3689152-3689147/10x96854/-74x78132/50/0 TTEC City: Greenwood Village Address: 6312 S. Fiddler's Green Circle Website: https://www.ttecjobs.com/en
Ishmael Quiroz reflects on Belize's record-breaking tourism year, explains how BELTRAIDE's programs support local businesses, and shares why sectors like BPOs are outpacing tourism in attracting talent. He also discusses what it would take to industrialize around tourism—and why packaging, branding, and policy reform matter more than we think. Belize Tourism Futures S2E4 | Presented by BELTRAIDE
Owen Campbell is the operations director at Kura. He is based in Glasgow, Scotland. Kura is a BPO based in the UK, but also with operations in South Africa. They have a number of clients from various regulated industries and Owen talked to Mark Hillary about the differences between a client that has complete control over all their services and a client from a more regulated environment. What needs to be considered when working to design CX for a regulated industry? https://www.linkedin.com/in/owen-campbell-a4602b173/ https://www.wearekura.com/ SUMMARY Mark Hillary and Peter Ryan discuss the complexities of customer experience (CX) in regulated industries with Owen Campbell, Operations Director at Kura, a BPO focused on culture and people development. Campbell highlights Kura's work with heavily regulated sectors like healthcare, utilities, and financial services, emphasizing the importance of compliance and agent training. He notes that while innovation may take longer in regulated environments, it is still possible. Campbell also discusses Kura's strategic planning sessions, the importance of data security, and the shift towards outcome-based models for advisors. He predicts increased use of AI and automated compliance in the coming years.
Hey, Note Closers! In this episode of The Note Closer Show, Scott Carson dives deep into the world of reverse mortgages and how to potentially profit from them! Scott walks through the process of evaluating a tape of 52 reverse mortgages, offering insights into identifying deals, assessing property values, and understanding the foreclosure process in different states. Learn how to analyze potential profits, estimate rehab costs, and navigate the complexities of HUD and BPOs. Whether you're a seasoned note investor or just starting out, this episode is packed with actionable information to help you make informed decisions.Here's What You'll Discover:Reverse Mortgage Overview: Understand the basics of reverse mortgages, including how they work, why they default, and the potential equity involved.Tape Analysis: Learn how to analyze a tape of reverse mortgages, including key data points like BPO, estimated full payoff, and foreclosure status.State-Specific Foreclosure Processes: Discover the differences in foreclosure timelines between states like Oklahoma and North Carolina and how that impacts your investment strategy.Valuation & Rehab: Strategies for evaluating property values, estimating rehab costs, and determining if a property is worth foreclosing on vs. selling as-is.BPO & Due Diligence: The importance of obtaining Broker Price Opinions (BPOs) and conducting thorough due diligence, including title reports and interior inspections.Profit Calculation: Walk through calculating potential profits, considering factors like money costs, closing costs, and potential returns at foreclosure auctions.Property Examples: Review of real property examples, including analysis of estimated values and rehab estimatesThe 8-9 reverse mortgages that look attractive.Don't forget to like, subscribe, and hit the notification bell so that you are the first to know about new episodes and note investing strategies!Conclusion:Evaluating reverse mortgages can be overwhelming. In this episode, Scott breaks it all down to make it manageable. Make sure to perform the due diligence to determine a property's real potential!Map of the NotesWatch the Original VIDEO HERE!Book a Call With Scott HERE!Sign up for the next FREE One-Day Note Class HERE!Sign up for the WCN Membership HERE!Sign up for the next Note Buying For Dummies Workshop HERE!Love the show? Subscribe, rate, review, and share!Here's How »Join the Note Closers Show community today:WeCloseNotes.comThe Note Closers Show FacebookThe Note Closers Show TwitterScott Carson LinkedInThe Note Closers Show YouTubeThe Note Closers Show VimeoThe Note Closers Show InstagramWe Close Notes Pinterest
David Neale is the Founder and CEO of GBPO Solutions. He is based in the UK. David has experience as a buyer of BPO services and as a representative of BPOs. With this insight he decided that one of the missing ingredients in the BPO sales process is transparency - how does anyone know that what a BPO says about their services is really true? David founded GBPO Solutions to provide accreditation to BPOs, so if they do make claims about their capabilities then they can point to the accreditation to show that their claims can be verified. David talked to Mark Hillary about why he started GBPO Solutions and why he explored this idea of transparency rather than measuring processes and delivery capabilities... David also publishes the popular David's Diaries podcast - focused on the biography of his guests. You can find both Mark and Peter in the back catalogue - both interviewed in 2024. https://www.linkedin.com/in/david-neale-08b80011b/ https://www.linkedin.com/company/gbpo-solutions/ https://podcasts.apple.com/us/podcast/davids-diaries/id1766136430 Mark and Peter on David's Diaries https://podcasts.apple.com/us/podcast/mark-hillary/id1766136430?i=1000668074006 https://podcasts.apple.com/us/podcast/peter-ryan/id1766136430?i=1000668073926 Podcast Summary In this episode, David Neale introduces his new venture, GBPO Solutions, and discusses a novel approach to BPO accreditation. Unlike traditional certifications focused on operational standards (like ISO or HIPAA), David's accreditation model emphasizes truthfulness, transparency, and independent validation of how BPOs present themselves to the market. David Neale's accreditation model for BPOs aims to inject much-needed transparency and accountability into a market still relying on legacy procurement methods. By focusing on honesty over hype, GBPO Solutions wants to reshape the buyer-supplier dynamic in outsourcing for the better.
In this insightful episode of the Note Closers Show, Scott Carson discusses how to be a smart note investor in today's rapidly evolving market. With the rise of AI and the constant shifts in the real estate landscape, it's crucial to stay updated and adapt your strategies. Scott shares key insights on what smart note investors are doing to thrive in 2025 and what outdated practices to avoid.Key Discussion Points:Avoiding Outdated Strategies: Discover why buying lists of newly originated mortgage notes is often a waste of time and money. Learn why these lists are often dead leads and why sellers are unable to offer discounts.Leveraging Modern Tools and Technologies: Understand the importance of using the internet, AI, and other smart tools to work more efficiently. Scott emphasizes the need to evolve with the times and avoid relying on outdated methods.Building Direct Relationships: Learn why smart investors go directly to banks, hedge funds, and servicing companies instead of relying on third-party websites or seller's reps. Building these relationships leads to better deals and access to more opportunities.Creating and Sharing Content: Discover the power of creating your own content through videos, podcasts, and newsletters. Sharing your knowledge and deals helps build confidence and attract potential investors.Making Multiple Offers and Conducting Due Diligence: Understand the importance of making multiple offers to increase your chances of acceptance. Scott stresses the need to perform thorough due diligence, including ordering BPOs, getting eyes on the property, and conducting title work.Closing:Tune in to learn how to revolutionize your note investing strategy and thrive in 2025. By avoiding common pitfalls and embracing modern tools and techniques, you can become a successful and smart note investor.Watch the Original VIDEO HERE!Book a Call With Scott HERE!Sign up for the next FREE One-Day Note Class HERE!Sign up for the WCN Membership HERE!Sign up for the next Note Buying For Dummies Workshop HERE!Love the show? Subscribe, rate, review, and share!Here's How »Join the Note Closers Show community today:WeCloseNotes.comThe Note Closers Show FacebookThe Note Closers Show TwitterScott Carson LinkedInThe Note Closers Show YouTubeThe Note Closers Show VimeoThe Note Closers Show InstagramWe Close Notes PinterestGet Signed Up For the WCN Membership HERE!
How to Truly Know the Value of your Collateral - #270 Knowing the true value of your collateral is one of the most critical parts of being a successful private or hard money lender. In this episode, Jason and Chris break down exactly how they determine property values beyond just appraisals and third-party reports.
“We're not just building AI for call centers — we're building AI with call centers in mind.” — Justin Massey, Relay Hawk At the vCon Spring 2025 Conference, Justin Massey of Relay Hawk brought both a technologist's vision and a contact center veteran's intuition to the main stage. In a conversation with Technology Reseller News publisher Doug Green, Massey unpacked how his team is building next-generation AI voice agents — with human-first design and real-world BPO pain points at the forefront. Contact Center Roots, Tech-Forward Vision Massey isn't your typical AI founder. With a family background spanning nearly five decades in call center operations, he was answering phones at 16 to fuel his Ford Explorer. “Some people theorize about customer experience. I lived it,” he shared. That lived experience directly informs Relay Hawk's core solution: AI agents that know when to get out of the way. When the AI hits a wall, Relay Hawk's "escape hatch" hands the conversation off to a live agent — armed with the full context, so customers don't have to repeat themselves. AI Meets Authentication One of the major challenges in today's communication landscape? Verifying identity without collecting sensitive information. Massey proposes a modern approach: linking voice calls to identity providers like Google or Microsoft, much like how we authenticate via email or social platforms. “Why not use that same concept for phone calls?” he asked. Instead of collecting sensitive data during a call — a liability for BPOs — customers could validate via external credentials and receive a verified claim. Tackling “Dependency Problems” in AI Integration Relay Hawk is also focused on solving integration hurdles — what Massey called “dependency problems.” “Everyone wants their AI to plug into CRMs, ticketing platforms, schedulers — but every API is different,” he said. The goal: simplify third-party integration and leverage protocols like MCP to make AI deployment more seamless. Warning: Transcription May Be Hazardous to Your AI Another overlooked challenge: bad transcription = bad data = bad AI. Massey highlighted that many call recordings are mono, making it hard to distinguish between caller and agent. RelayHawk recommends stereo recordings, ensuring the data feeding AI engines is clean, clear, and actionable. “If your transcription is off, your entire AI analysis goes off the rails.” Relay Hawk Is Looking for Design Partners Still in its early stages, Relay Hawk is working with design partners to refine its offering. “If you're an early adopter and want to help shape a solution that actually works for your use case — we want to talk,” Massey said. Learn more: RelayHawk.com or find them on LinkedIn by searching RelayHawk #AIinCallCenters #VoiceAI #RelayHawk #vCon2025 #ContactCenterTech #IdentityValidation #TranscriptionAI #CXInnovation #BPOsolutions #CallCenterAutomation #ConversationalAI #DougGreen #TechnologyResellerNews
If you're in SF: Join us for the Claude Plays Pokemon hackathon this Sunday!If you're not: Fill out the 2025 State of AI Eng survey for $250 in Amazon cards!Unsupervised Learning is a podcast that interviews the sharpest minds in AI about what's real today, what will be real in the future and what it means for businesses and the world - helping builders, researchers and founders deconstruct and understand the biggest breakthroughs. Top guests: Noam Shazeer, Bob McGrew, Noam Brown, Dylan Patel, Percy Liang, David LuanFull Episode on Their YouTubeTimestamps* 00:00 Introduction and Excitement for Collaboration* 00:27 Reflecting on Surprises in AI Over the Past Year* 01:44 Open Source Models and Their Adoption* 06:01 The Rise of GPT Wrappers* 06:55 AI Builders and Low-Code Platforms* 09:35 Overhyped and Underhyped AI Trends* 22:17 Product Market Fit in AI* 28:23 Google's Current Momentum* 28:33 Customer Support and AI* 29:54 AI's Impact on Cost and Growth* 31:05 Voice AI and Scheduling* 32:59 Emerging AI Applications* 34:12 Education and AI* 36:34 Defensibility in AI Applications* 40:10 Infrastructure and AI* 47:08 Challenges and Future of AI* 52:15 Quick Fire Round and Closing RemarksTranscript[00:00:00] Introduction and Podcast Overview[00:00:00] Jacob: well, thanks so much for doing this, guys. I feel like we've we've been excited to do a collab for a while. I[00:00:13] swyx: love crossovers. Yeah. Yeah. This, this is great. Like the ultimate meta about just podcasters talking to other podcasters. Yeah. It's a lot. Podcasts all the way up.[00:00:21] Jacob: I figured we'd have a pretty free ranging conversation today but brought a few conversation starters to, to, to kick us off.[00:00:27] Reflecting on AI Surprises and Trends[00:00:27] Jacob: And so I figured one interesting place to start is you know, obviously it feels that this world is changing like every few months. Wondering as you guys reflect path on the past year, like what surprised you the most?[00:00:36] Alessio: I think definitely recently models we kinda on the, on the right here. Like, oh, that, well, I, I I think there's, there's like the, what surprised us in a good way.[00:00:44] May maybe in a, in a bad way. I would say in a good way. Recently models and I think the release of them right after the new reps scaling instead talked by Ilia. I think there was maybe like a, a little. It's so over and then we're so back. I'm like such a short, short period. It was really [00:01:00] fortuitous[00:01:00] Jacob: timing though, like right.[00:01:01] As pre-training died, I mean, obviously I'm sure within the labs they knew pre-training was dying and had to find something. But you know, from the outside it was it, it felt like one right into the other.[00:01:09] Alessio: Yeah. Yeah, exactly. So that, that was a good surprise,[00:01:12] swyx: I would say, if you wanna make that comment about timing, I think it's suspiciously neat that like, because we know that Strawberry was being worked on for like two years-ish.[00:01:20] Like, and we know exactly when Nome joined OpenAI, and that was obviously a big strategic bet by OpenAI. So like, for it to transition, so transition so nicely when like, pre-training is kind of tapped out to, into like, oh, now inference time is, is the new scaling law is like conv very convenient. I, I, I like if there were an Illuminati, this would be what they planned.[00:01:41] Or if we're living in a simulation or something. Yeah.[00:01:44] Open Source Models and Their Impact[00:01:44] swyx: Then you said open source[00:01:45] Alessio: as well? Yeah. Well, no, I, I think like open source. Yeah. We're discussing this on the negative. I would say the relevance of open source. I would specifically open models. Yeah, I was surprised the lack, like the llamas of the world by the lack of adoption.[00:01:56] And I mean, people use it obviously, but I would say nobody's [00:02:00] really like a huge fanboy, you know, I think the local llama community and some of the more obvious use cases really like it. But when we talk to like enterprise folks, it's like, it's cool, you know? And I think people love to argue about licenses and all of that, but the reality is that it doesn't really change the adoption path of, of ai.[00:02:18] So[00:02:19] swyx: yeah, the specific stat that I got from on anchor from Braintrust mm-hmm. In one of the episodes that we did was I think he estimated that open source model usage in work in enterprises is that like 5% and going down.[00:02:31] Jacob: And it feels like you're basically all these enterprises are in like use case discovery mode, where it's like, let's just take what we think is the most powerful model and figure out if we can find anything that works.[00:02:39] And, you know, so much of, of, of it feels like discovery of that. And then, right, as you've discovered something, a new generation of models are out and so you have to go do discovery with those. And you know, I think obviously we're probably optimistic that the that the open source models increase in uptake.[00:02:50] It's funny, I was gonna say my biggest surprise in the last year was open source related, but it was just how Fast Open Source caught up on the reasoning models. It was kind of unclear to me, like over time whether there would be, you know, [00:03:00] a compounding advantage for some of the closed source models where in the, okay, in the early days of, of scaling you know, there was a, a tight time loop, but over time, you know, would would the gap increase?[00:03:08] And if anything it feels like a trunk. You know, and I think deep seek specifically was just really surprising in how, you know, in many ways if the value of these model companies is like you have a model for a period of time and you're the only one that can build products on top of that model while you have it.[00:03:21] Like, God, that time period is a lot shorter than a, than I thought it was gonna be a year ago.[00:03:25] swyx: Yeah. I mean, again, I I, I don't like this label of how Fast Open Source caught up because it's really how Fast Deepsea caught up. Right. And now we have, like, I think some of it is that Deepsea is basically gonna stop open sourcing models.[00:03:36] Yeah. So like there, there's no team open source, there's just different companies and they choose to open source or not. And we got lucky with deep seek releasing something and then everyone else is basically distilling from deep seek and those are distillations. Catching up is such an easier lower bar than like actually catching up, which is like you, you are like from scratch.[00:03:56] You're training something that like is competitive on that front. I don't know if [00:04:00] that's happening. Like basically the only player right now is we're waiting for LA four.[00:04:03] Jordan: I mean, it's always an order of magnitude cheaper to replicate what's already been done than to create something fundamentally new.[00:04:09] And so that's why I think deep seek overall was overhyped. Right? I mean obviously it's a good open source, new entrant, but at the same time there's nothing new fundamentally there other than sort of doing it executing what's already been done really well.[00:04:21] Alessio: Yeah,[00:04:21] Jordan: right.[00:04:21] Alessio: So Well, but I think the traces is like maybe the biggest thing, I think most previous open models is like the same model, just a little worse and cheaper.[00:04:30] Yeah. Like R one is like the first model that had the full traces. So I think that's like a net unique thing in fair, open source. But yeah, I, I think like we talked about deep seek in the our n of year 2023 recap, and we're mostly focused on cheaper inference. Like we didn't really have deep, see, deep CV three[00:04:47] swyx: was out then, and we were like, that was already like talking about fine green mixture of experts and all that.[00:04:51] Like that's a great receipt to[00:04:52] Jacob: have[00:04:52] swyx: to be like, yeah.[00:04:52] Jacob: End[00:04:53] swyx: of year 20. Yeah. That's a,[00:04:54] Jacob: that's a, that's, that's an[00:04:55] swyx: impressive one. You follow the right whale believers in Twitter. It's, it's like [00:05:00] pretty obvious. I actually had like so, you know, I used to be in finance and, and a lot, a lot of my hedge fund and PE friends called me up.[00:05:06] They were like, why didn't you tip us off on deep seek? And I'm like, well, I mean, it's been there. It's, it's actually like kind of surprising that like, Nvidia like fell like what, 15% in one day? Yeah. Because deep seek and I, I think it's just like whatever the market, public market narrative decides is a story, becomes the story, but really like the technical movements are usually.[00:05:26] One to two years in the making. Before that,[00:05:27] Jacob: basically these people were telling on themselves that they didn't listen to your podcast. They've been on the end of year 22, 3. No, no,[00:05:32] swyx: no. Like yeah, we weren't, we weren't like banging the drum. So like it's also on us to be like, no, like this. This is an actual tipping point.[00:05:38] And I think I like as people who are like, our function as podcasters and industry analysts is to raise the bar or focus attention on things that you think matter. And sometimes we're too passive about it. And I think I was too passive there. I'd be, I'd be happy to own up on that.[00:05:52] Jacob: No, I feel like over time you guys have moved into this margin general role of like taking stances of things that are or aren't important and, you know I feel like you've done that with MCP of [00:06:00] late and a bunch of[00:06:00] swyx: things.[00:06:00] Yeah.[00:06:01] Challenges and Opportunities in AI Engineering[00:06:01] swyx: So like the, the general pushes is AI engineering, you know, like it's gotta, gotta wrap the shirt. And MCP is part of that, but like the, the general movement is what can engineers do above the model layer to augment model capabilities. And it turns out it's a lot. And turns out we went from like, making fun of GPT rappers to now I think the overwhelming consensus GPT wrappers is the only thing that's interesting.[00:06:20] Yeah.[00:06:21] Jacob: I remember like, Arvin from Perplexity came on our podcast and he was like, I'm proudly a rapper. Like, you know, it's like anyone that's like talking about like, you know, differentiation, like pre-product market fit is like a ridiculous thing to, to say, like, build something people want and then yeah.[00:06:33] Over time you can kind of worry about that.[00:06:35] swyx: Yeah. I, I interviewed him in 2023 and I think he may have been the first person on our podcast to like, probably be a GBT rapper. Yeah. And yeah, and obviously he's built a huge business on that. Totally. Now, now we now we all can't get enough of it. I have another one for, Oh, nice.[00:06:47] That was Alessia's one and we, we perhaps individual answers just to be interesting in the same Uber on the way up. Yeah. You just like in the, in different Oh, I was driving too. Oh, you were driving. So I actually, I mean, it was a Tesla mostly drove mine was [00:07:00] actually, it is interesting that low-code builders did not capture the AI builder market.[00:07:04] Right. AI builders being bought lovable, low-code builders being Zapier, Airtable, retool notion. Any of those, like you're not technical. You can build software.[00:07:14] misc: Yeah.[00:07:14] swyx: Somehow not all them missed it. Why? It's bizarre. Like they should have the DNA, I don't know. They should have. They already have the reach, they already have the, the distribution.[00:07:25] Like why? I I have no idea. The ability to[00:07:27] Jacob: fast follow too. Like I'm surprised there's Yeah. There's just[00:07:29] swyx: nothing. Yeah. What do you make of that? I, it seems and you know, not to come back to the AI engineering future, like it takes a, a certain kind of. Founder mindset or AI engineer mindset to be like, we will build this from whole cloth and not be tied to existing paradigms.[00:07:45] I think, 'cause I like, if I was, if I'm to, you know, you know, Wade or who's, who's, who's the Zapier person than, you know, Mike. Mike who has left the Zapier. Yeah. What's the, yeah. Like you know, Zapier, when they decided to do Zapier ai, they [00:08:00] were like, oh, you can use natural language to make Zap actions, right?[00:08:03] When Notion decided to do Notion ai, they were like, oh, you can like, you know write documents or, you know, fill in tables with, with ai. Like, they didn't do the, the, the, the next step because they already had their base and they were like, let's improve our baseline. And the other people who actually tried for to, to create a phone cloth were like, we, we got no prior preconceptions.[00:08:24] Like, let's see what we can, what kinda software people can build with like from scratch, basically. I don't know that, that's my explanation. I dunno if you guys have any retros on the AI builders?[00:08:33] Jacob: Yeah. Or, or, or did they kind of get lucky getting, you know starting that product journey? Like right as the models were reaching the inflection point?[00:08:39] There's the timing[00:08:40] swyx: issue. Yeah. Yeah, yeah. Yeah. Yeah, I don't know. Like I, I, to some extent, I think the only reason you and I are talking about it is that they, both of them have reported like ridiculous numbers. Like zero to 20 million in three months, basically, both of them. Jordan, did you have a, a big surprise?[00:08:55] Jordan: Yeah, I mean, some of what's already been discussed. I guess the only other thing would be on the Apple side in particular, I [00:09:00] think, I think you know, for the last text message summary, like, but they're[00:09:04] Jacob: funny. They're funny at how bad they had, how off they're, they're viral. Yeah.[00:09:08] Jordan: I mean, so like for the last couple years we've seen so many companies that are trying to do personal assistance, like all these various consumer things, and one of the things we've always asked is, well, apple is in prime position to do all this.[00:09:18] And then with Apple Intelligence, they just. Totally messed up in so many different ways. And then the whole BBC thing saying that the guy shot himself when he didn't. And just like, there's just so many things at this point that I would've thought that they would've ironed up their, their AI products better, but just didn't really catch on,[00:09:35] Jacob: you know, second on this list of, of generally overly broad opening questions would be anything that you guys think is kind of like overhyped or under hyped in the AI world right now?[00:09:43] Alessio: Overhyped agents framework. Sorry. Not naming any particular ones. I'm sorry. Not, not not, yeah, exactly. It's not, I, I would say they're just overall a chase to try and be the framework when the workloads are like in such flux. Yeah. That I just think is like so [00:10:00] hard to reconcile the two. I think what Harrison and Link Chain has done so amazingly, it's like product velocity.[00:10:05] Like, you know, the initial obstructions were maybe not the ending obstruction, but like they were just releasing stuff every day trying to be on top of it. But I think now we're like past that, like what people are looking for now. It's like something that they can actually build on mm-hmm. And stay on for the next couple of years.[00:10:23] And we talked about this with Brett Taylor on our episode, and it feels like, it's like the jQuery era Yeah. Of like agents and lms. It's like, it's kinda like, you know, single file, big frameworks, kinda like a lot of players, but maybe we need React. And I think people are just trying to build still Jake Barry.[00:10:39] Like, I don't really see a lot of people doing react like,[00:10:43] swyx: yeah. Maybe the, the only modification I made about that is maybe it's too early even for frameworks at all. And the thing that, and do you think[00:10:50] Jacob: there's enough stability in the underlying model layer and, and patterns to, to have this,[00:10:54] swyx: the thing is the protocol and not the framework?[00:10:56] Jacob: Yeah.[00:10:56] swyx: Because frameworks inherently embed protocols, but if you just focus on a protocol, maybe that [00:11:00] works. And obviously MCP is. The current leading mm-hmm. Area. And you know, I think the comparison there would be, instead of just jQuery, it is XML HTB requests, which is like the, the thing that enabled Ajax.[00:11:10] And that was the, the, the, the, the sort of inciting incident for JavaScripts being popular as a language.[00:11:16] Jordan: I would largely agree with that. I mean, I think on the, the react side of things, I think we're starting to see more frameworks sort of go after more of that, I guess like master is sort of like on the TypeScript side and more of like a sort of master.[00:11:28] Yeah, yeah, yeah, yeah. The traction is really impressive there. And so I think we're starting to see more surface there, but I think there's still a big opportunity. What do you have for for an over or under hyped on the under hype side? You know, I actually, I, I know I mentioned Apple already, but I think the private cloud compute side with PCC, I actually think that could be really big.[00:11:45] It's under the radar right now. Mm-hmm. But in terms of basically bringing. The on device sort of security to the cloud. They've done a lot of architecturally interesting things there. Who's they? Apple. Oh, okay. On the PCC side. And so I actually think of that.[00:11:58] swyx: So you're negative on Apple [00:12:00] Intelligence, but also on Apple Cloud,[00:12:01] Jordan: on the more of the local device.[00:12:04] Sort of, I think there'll be a lot of workloads still on device, but when you need to speak to the cloud for larger LLMs, I think that Apple has done really interesting thing on the privacy side.[00:12:13] Alessio: Yeah. We did the seed of a company that does that, so Yeah. Especially as things become more co that you set 'em up on purpose.[00:12:18] So that felt like a perfect Yeah, no, I was like, let's go Jordan, you guys concluding before this episode? Tell me about that company after. We'll chat after, but, but yes, I, I think that's like the unique the thing about LLM workflows is like you just cannot have everything be single tenant, right?[00:12:35] Because you just cannot get enough GPUs. Like even like large enterprises are used to having VPCs and like everything runs privately. But now you just cannot get enough GPUs to run in a VPC. So I think you're gonna need to be in a multi-tenant architecture, and you need, like you said, like single tenant guarantees in multi-tenant environment.[00:12:52] So yeah, it's a interesting space.[00:12:55] swyx: Yeah. What about you, Swiss? Under hypes, I want to say [00:13:00] memory. Just like stateful ai. As part of my keynote on, on for just like every, every conference I do, I do a keynote and I try to do the task of like defining an agent, just, you know, always evergreen content, every content for a keynote.[00:13:14] But I did it in a, in a way that it was like I think like a, what a researcher would do. Like you, you survey what people say and then you sort of categorize and, and go like, okay, this is the, the. What everyone calls agents and here are the groups of DEF definitions. Pick and choose. Right. And then it was very interesting that the week after that OpenAI launched their agents SDK and kind of formalized what they think agents are.[00:13:34] CloudFlare also did the same with us and none of them had memory. Yeah, it's very strange. The, pretty much like the only big lab o obviously there, there's conversation memory, but there's not memory memory like in like a, like a let's store a large across fact about you and like, you know, exceed the, the context length.[00:13:54] And here's the, if you, if you're look, if you look closely enough, there's a really good implementation of memory inside of [00:14:00] MCP when they launched with the initial set of servers. They had a memory server in there, which I, I would recommend as like, that's where you start with memory. But I think like if there was a better, I.[00:14:10] Memory abstraction, then a lot of our agents would be smarter and could learn on, on the job, which is something that we all want. And for some reason we all just like ignored that because it's just convenient to, and, but do you feel like[00:14:24] Jacob: it's being ignored or it's just a really hard problem and like lots of, I feel like lots of people are working on it.[00:14:27] Just feels like it's, it's proven more challenging.[00:14:29] swyx: Yeah. Yeah. Yeah. So, so Harrison has lang me, which I think now he's like, you know, relaunched again. And then we had letter come speak at our mm-hmm. Our conference I don't know, Zep, I think there's a bunch of other memory guys, but like, something like this I think should be normal in the stack.[00:14:44] And basically I think anything stateful should be interesting to VCs 'cause it's databases and, you know, we know how those things make money.[00:14:51] Jacob: I think on the over hype side, the only thing I'd add is like, I'm, I'm still surprised how many net new companies there are training models. I thought we were kind of like past that.[00:14:58] And[00:14:58] swyx: I would say they died end of last year. And now, [00:15:00] now they've resurfaced. Yeah. I mean they, that's one of the questions that you had down there of like, yeah. Sorry. Is there an opportunity for net new model players? I wouldn't say no. I don't know what you guys think.[00:15:08] Alessio: I, I don't have a reason to say no, but I also don't have a reason to say, this is what is missing and you should have a new model company do it.[00:15:15] But again, I'm an add here. Like, all these guys wanna[00:15:17] swyx: pursue a GI, you know, all, they all want to be like, oh, we'll, we'll like hit, you know, soda on all the benchmarks and like, they can't all do it. Yeah.[00:15:25] Jacob: I mean, look, I don't know if Ilia has the secret secret approach up his sleeve of of something beyond test time compute.[00:15:29] Mm-hmm. But it was funny, I, we had Noam Shaer on the podcast last week. I was asking him like, you know, is, is there like some sort of other algorithmic breakthrough? Would he make a Ilia? And he's like, look, I think what he is implicitly said was test time compute gets to the point where these models are doing AI engineering for us.[00:15:43] And so, you know, at that point they'll figure out the next algorithm breakthrough. Yeah. Which I thought was was pretty interesting.[00:15:47] Jordan: I agree with you folks. I think that we're most interested, at least from our side and like, you know, foundation models for specific use cases and more specialized use cases.[00:15:55] Mm-hmm. I guess the broader point is if there is something like that, that these companies can latch onto [00:16:00] and being there sort of. Known for being the best at. Maybe there's a case for that. Largely though I do agree with you that I don't think there should be, at this point, more model companies. I think it's like[00:16:09] Jacob: these[00:16:09] Jordan: unique data[00:16:09] Jacob: sets, right?[00:16:10] I mean, obviously robotics has been an area we've been really interested in. It's entirely different set of data that's required, you know, on top of like a, a good BLM and then, you know, biology, material sciences, more the specific use cases basically. Yeah. But also specific, like specific markets. A lot of these models are super generalizable, but like, you know finding opportunities to, you know, where, you know, for a lot of these bio companies, they have wet labs, like they're like running a ton of experiments or you know, same on the material sciences side.[00:16:31] And so I still feel like there's some, some opportunities there, but the core kind of like LLM agent space is it's tough, tough to compete with the big ones.[00:16:38] Alessio: Yeah. Agree. Yeah. But they're moving more into product. Yeah. So I think that's the question is like, if they could do better vertical models, why not do that instead of trying to do deep research and operator?[00:16:50] And these different things. Mm-hmm. I think that's what I'm, in my mind, it's like the agents coming[00:16:53] swyx: out too.[00:16:54] Alessio: Well. Yeah. In my, in my mind it's like financial pressure. Like they need to monetize in a much shorter timeframe [00:17:00] because the costs are so high. But maybe it's like, it's not that easy to, do[00:17:04] Jacob: you think they would be, that it would be a better business model to like, do a bunch of vertical?[00:17:07] Well, it's more like[00:17:07] Alessio: why wouldn't they, you know, like you make less enemies if you're like a model builder, right? Yeah. Like, like now with deep research and like search, now perplexity like an enemy and like a, you know, Gemini deep research is like more of an enemy. Versus if they were doing a finance model, you know?[00:17:25] Mm-hmm. Or whatever, like they would just enable so many more companies and they always have, like they had as one of the customer case studies for GBT search, but they're not building a finance based model for them. So is it because it's super hard and somebody should do it? Or is it because the new models.[00:17:41] Are gonna be so much better that like the vertical models are useless anyways. Like this is better lesson. Exactly.[00:17:46] Jacob: It still seems to be a somewhat outstanding question. I, I'd say like, all the signs of the last few years seem to be like a general purpose model is like the way to go. And, you know, you know, like training a hyper-specific model in this, in, in a domain is like, you know, maybe it's cheaper and faster, but it's not gonna be like higher quality.[00:17:59] But [00:18:00] also like, I think it's still an, I mean, we were talking to, to no and Jack Ray from Google last week, and they were like, yeah, this is still an outstanding, like, we, we check this every time we have a new model. Like whether there's you know, there that still seems to be holding. I remember like a few years ago, it felt like all the rage was like the, it was like the Bloomberg GPT model came out.[00:18:14] Everyone was like, oh, you gotta like, you know, massive data. Yeah. I had[00:18:17] swyx: a GPA, I had DP of AI of Bloomberg present on that. Yeah. That must be a really[00:18:20] Jacob: interesting episode to go back on because I feel like, like very shortly thereafter, the next opening AI model came out and just like beat it on all sorts of[00:18:25] swyx: No, it, it was a talk.[00:18:26] We haven't released it yet, but yeah, I mean it's basically they concluded that the, the closed models were better so they just Yeah. Stopped. Interesting. Exactly. So I feel like that's been the but he's I, I would be. He's very insistent that the work that they did, the team he assembled, the data that he collected is actually useful for more than just the model.[00:18:42] So like, basically everything but the model survived. What are the other things? The data pipeline. Okay. The team that they, they, they assembled for like fine tuning and implementing whatever models they, they ended up picking. Yeah, it seems like they are happy with that. And they're running with that.[00:18:57] He runs like 12, 13 [00:19:00] teams at Bloomberg just working. Jenny, I across the company.[00:19:03] Jacob: I mean, I guess we've, we've all kind of been alluding it to it right now, but I guess because it's a natural transition. You know, the other broad opening I have is just what we're paying most attention to right now. And I think back on this, like, you know, the model company's coming into the product area.[00:19:13] I mean, I think that's gonna be like, I'm fascinated to see how that plays out over the next year and kind of these like frenemy dynamics and it feels like it's gonna first boil up on like cursor anthropic and like the way that plays out over the next six months I think will be. What, what is Cursor?[00:19:26] swyx: Anthropic is, you mean Cursor versus anthropic or, yeah. And I[00:19:29] Jacob: assume, you know, over time Anthropic wants to get more into the application side of coding Uhhuh. And you know, I assume over time Cursor will wanna diversify off of, you know, just using the Anthropic model.[00:19:39] swyx: It's interesting that now Cursor is now worth like 10 billion, nine, nine, 10 billion.[00:19:43] Yeah. And like they've made themselves hard to acquire, like I would've said, like, you should just get yourself to five, 6 billion and join OpenAI. And like all the training data goes through OpenAI and that's how they train their coding model. Now it's not as complicated. Now they need to be an independent company.[00:19:57] Jacob: Increasingly, it's seems to the model companies want to get into the [00:20:00] product layer. And so seeing over the next six, 12 months does having the best model, you know let you kind of start from a cold start on the product side and, and get something in market. Or are the, you know, companies with the best products, even if they eventually have to switch to a somewhat worse, tiny bit worse model, does it not, you know, where do the developers ultimately choose to go?[00:20:16] I think that'll be super interesting. Yeah.[00:20:18] Alessio: Don't you think that Devon is more in trouble than cursor? I, I feel like on Tropic, if anything wants to move more towards, I don't think they wanna build the ID like if I think about coding, it's like kind of like, you know, you look at it like a cube, it's like the ID is like one way to get the code and then the agent is like the other side.[00:20:33] Yeah. I feel like on Tropic wants more be on the agent side and then hand you off the cursor when you want to go in depth versus like trying to build the claw. IDEI think that's not, I would say, I don't know how you think the[00:20:46] swyx: existence, a cloud code doesn't show, doesn't support what you say. Like maybe they would, but[00:20:52] Jacob: assume, like I assume both just converge eventually where you want have where will you be able to do both?[00:20:57] So,[00:20:57] swyx: so in order to be so we're, we're talking [00:21:00] about coding agents, whether it's sort of what is it? Inner loop versus auto loop, right? Like inner loop is inside cursor, inside your ID between inside of a GI commit and auto loop is between GI commits on, on the cloud. And I think like to be an outer loop coding agent, you have to be more of a, like, we will integrate with your code base, we'll sign your whatever.[00:21:17] You know, security thing that you need to sign. Yeah. That kinda schlep. I don't think the model ads wanna do that schlep, they just want to provide models. So that, that, that's, that would be my argument against like why cognition should still have, have, have some moat against anthropic just simply because they cognition would do the schlep and the biz dev and the infra that philanthropic doesn't really care about.[00:21:39] Jacob: I know the schlep is pretty sticky though. Once you do it,[00:21:41] swyx: it's very sticky. Yeah. Yeah. I mean it's, it's, it's interesting. Like, I, I think the natural winner of that should be sourcegraph. But there's another[00:21:47] Jacob: unprompted point portfolio. Nice. We, I mean they, they're[00:21:51] swyx: big supporters like very friendly with both Quinn and B and they've they've done a lot of work with Cody, but like, no, not much work on the outer [00:22:00] loop stuff yet.[00:22:01] But like any company where like they have already had, like, we've been around for 10 years, we, we like have all the enterprise contracts that you already trust us with your code base. Why would you go trust like factory or cognition as like, you know, 2-year-old startups who like just came outta MIT Like, I don't know.[00:22:17] Product Market Fit in AI[00:22:17] Jacob: I guess switching gears to the to the application side I'm curious for both of you, like how do you kind of characterize what has genuine product market fit in AI today? And I guess less, you more and your side of the investing side, like more interesting to invest in that category of the stuff that works today or kind of where the capabilities are going long term.[00:22:35] Alessio: That's hard. I was asking you to do my job for you, like, man, that's a easy, that's a layout. Tell us all your investing[00:22:40] pieces. Yeah, yeah, yeah. I, I, I would say we, well we only really do mostly seed investing, so it's hard to invest in things that already work. Yeah. That fair. Are really late. So we try to, but, but we try to be at the cusp of like, you know, usually the investments we like to make, there's like really not that much market risk.[00:22:57] It's like if this works. Obviously people are gonna [00:23:00] use it, but like it's unclear whether or not it's gonna work. So that's kind of more what we skew towards. We try not to chase as many trends and I don't know, I, you know, I was a founder myself and sometimes I feel like it's easy to just jump in and do the thing that is hot, but like becoming a founder to do something that is like underappreciated or like doesn't yet work shows some level of like dread and self, like you, you actually really believe in the thing.[00:23:25] So that alone for me is like, kind of makes me skew more towards that. And you do a lot of angel investing too, so I'm curious how,[00:23:31] swyx: Yeah, but I don't regard, I don't have, I don't use, put, put that in my mental framework of things like I come at this much more as a content creator or market analyst of like, yeah, it, it really does matter to me what has part of market fit because.[00:23:45] People, I have to answer the question of what is working now When, when people ask me,[00:23:50] Jacob: do you feel like relative to the, the obviously the hype and discourse out there, like, you know, do you feel like there's a lot of things that have product market fit or like a few things, like where a few things? Yeah.[00:23:58] swyx: I was gonna say this, so I have a list [00:24:00] of like two years ago we, I wrote the Anatomy of autonomy posts where it was like the, the first, like what's going on in agents and, and and, and, and what is actually making money. Because I think there's a lot of gen I skeptics out there. They're all like, these, these things are toys.[00:24:13] They're, they're not unreliable. And you know, why, why, why you dedicating your life to these things. And I think for me, the party market fit bar at the time was a hundred million dollars, right? Like what use cases can reasonably fit a hundred million dollars. And at the time it was like co-pilot it was Jasper.[00:24:30] No longer, but mm-hmm. You know, in that category of like help you write. Yeah. Which I think, I think was, was helpful. And then and the cursor I think was on there as, as a, as, as, as like a coding agent. Plus plus. I think that list will just grow over time of like the form factors that we know to work, and then we can just adapt the form factors to a bunch of other things.[00:24:47] So like the, the one that's the most recently added to this is deep research.[00:24:52] misc: Yeah.[00:24:52] swyx: Right. Where anything that looks like a deep research whether it's a grok version, Gemini version, perplexity version, whatever. He has an investment [00:25:00] that that he likes called Brightwave that is basically deep research for finance.[00:25:02] Yeah. And anything where like all it is like long-term agent, agent reporting and it's starting to take more and more of the job away from you and, and just give you much more reason to report. I think it's going to work. And that has some PMFI think obviously has PMF like I, I would say. It's I, I went to this exercise of trying to handicap how much money open AI made from launching open ai deep research.[00:25:25] I think it's billions. Like the, the, the mo the the she upgrade from like $20 to 200. It has to be billions in the R off. Maybe not all them will stick around, but like that is some amount of PMF that is didn't they have to immediately drop it down[00:25:38] Jacob: to the $20 tier?[00:25:39] swyx: They expanded access. I don't, I wouldn't say, which I thought was[00:25:42] Jacob: really telling of the market.[00:25:43] Right. It's like where you have a you know, I think it's gonna be so interesting to see what they're actually able to get in that 200 or $2,000 tier, which we all think is, is, you know, has a ton of potential. But I thought it was fascinating. I don't know whether it was just to get more people exposure to it or the fact that like Google had a similar product obviously, and, and other folks did too.[00:25:59] But [00:26:00] it was really interesting how quickly they dropped it down.[00:26:02] swyx: I don't, I think that's just a more general policy of no matter what they have at the top tier, they always want to have smaller versions of that in the, in the lower tiers. Yeah. And just get people exposure to it. Just, yeah, just get exposure.[00:26:12] The brand of being first to market and, and like the default choice Yeah. Is paramount to open ai[00:26:18] Jacob: though. I thought that whole thing was fascinating 'cause Google had the first product, right? Yeah. And no, like, you know, I, we[00:26:24] swyx: interviewed them. I, I, I, straight up to their faces, I was like, opening, I mocked you.[00:26:28] And they were like, yeah, well, actually curious, what's[00:26:30] Jacob: it, this is totally off topic, but whatever. Like, what is it going to take for go? Google just released some great models like a, a few weeks ago. Like I feel like it's happening. The stuff they're shipping is really cool. It's happening. Yeah, but I, I, I also, I feel like at least in the, you know, broader discourse, it's still like a drop in the bucket relative to[00:26:45] swyx: Yeah.[00:26:45] I mean, I, I can riff on, on this. I, I, but I, I think it's happening. I think it takes some time, but I am, like my Gemini usage is up. Like, I, I use, I use it a lot more for anything from like summarizing YouTube videos to the [00:27:00] native image generation Yeah. That they just launched to like flash thinking.[00:27:02] So yeah, multi-mobile stuff's great. Yeah. I run you know, and I run like a daily sort of news recap called AI news that is, 99% generated by models, and I do a bake off between all the frontier models every day. And it's every day. Like does it switch? I manual? Yes, it does switch. And I, man, I manually do it.[00:27:18] And flash is, flash wins most days. So, so like, I think it's happening. I think I was thinking, I was thinking about tracking myself like number of opens of tragedy, g Bt versus Gemini. And at some point it will cross. I think that Gemini will be my main and, and it, it, I I like that will slowly happen for a bunch of people.[00:27:37] And, and, and then that will, that'll shift. I, I think that's, that's a really interesting for developers, this is a different question. Yeah. It's Google getting over itself of having Google Cloud versus Vertex versus AI studio, all these like five different brands, slowly consolidating it. It'll happen just slowly, I guess.[00:27:53] Alessio: Yeah.[00:27:54] Yeah. I, I mean, another good example is like you cannot use the thinking models in cursor. Yeah. And I know [00:28:00] Logan killed Patrick's that they're working on it, but I, I think there's all these small things where like if I cannot easily use it, I'm really not gonna go out of my way to do it. But I do agree that when you do use them, their models are, are great.[00:28:12] So yeah. They just need better, better bridges.[00:28:15] swyx: You had one of the questions in the prep.[00:28:16] Debating Public Companies: Google vs. Apple[00:28:16] swyx: What public company are you long and short and minus Google versus, versus Apple, like, long, short. That was also my[00:28:23] Jacob: combo. I, I feel like, yeah, I mean, it does feel like Google's really cooking right now.[00:28:26] swyx: Yeah. So okay, coming back to what has product market fit[00:28:29] Jacob: now,[00:28:29] swyx: now that we come[00:28:30] Jacob: back to my complete total sidetrack,[00:28:33] Customer Support and AI's Role[00:28:33] swyx: there's also customer support.[00:28:35] We were talking on, on the car about Decagon and Sierra, obviously Brett, Brett Taylor is founder of Sierra. And yeah, it seems like there's just this, these layers of agents that'll like, I think you just look at like the income statement or like the, the org chart of any large scaled company and you start picking them off one by one.[00:28:51] What like is interesting knowledge work? And they would just kind of eat. Things slowly from the outside in. Yeah, that makes sense.[00:28:57] Alessio: I, I mean, the episode with the, [00:29:00] with Brett, he's so passionate about developer tools and Yeah. He did not do a developer tools. We spent like two hours talking about developer tools and like, all, all of that stuff.[00:29:10] And it's like, I, they a customer support company, I'm like, man, that says something. You know what I mean? Yeah. It's like when you have somebody like him who can like, raise any amount of money from anybody to do anything. Yeah. To pick customer support as the market to go after while also being the chairman of OpenAI, like that shows you that like, these things have moats and have longstanding, like they're gonna stick around, you know?[00:29:32] Otherwise he's smarter than that. So yeah, that's a, that's a space where maybe initially, you know, I would've said, I don't know, it's like the most exciting thing to, to jump into, but then if you really look at the shape of like, how the workforce are structured and like how the cost centers of like the business really end up, especially for more consumer facing businesses, like a lot of it goes into customer support.[00:29:54] AI's Impact on Business Growth[00:29:54] Alessio: All the AI story of the last two years has been cost cutting. Yeah. I think now we're gonna switch more towards growth revenue. [00:30:00] Totally. You know, like you've seen Jensen, like last year, GTC was saying the more you buy, the more you save this year is that the more you buy, the more you make. So we're hot off the[00:30:08] Jacob: press.[00:30:10] We were there. We were there. Yeah. I do think that's one of the most interesting things about the, this first wave of apps where it's like almost the easiest thing that you could you could get real traction with was stuff that, you know, for lack of a better way to frame it, like so that people had already been comfortable outsourcing the BPOs or something and kind of implicitly said like, Hey, this is a cost center.[00:30:24] Like we are willing to take some performance cut for cost in the past. You know, the, the irony of that, or what I'm really curious to see how it plays out is, you know, you, you could imagine that is the area where price competition is going to be most fierce because it's already stuff that you know, that people have said, Hey, we don't need the like a hundred percent best version of that.[00:30:42] And I wonder, you know, this next wave of apps. May prove actually even more defensible as you get these capabilities that actually are, you know, increased top line or whatnot where you're like, you take ai, go to market, for example. Like you're, you'd pay like twice as much for something that brought, like, 'cause there's just a kind of very clean ROI story to it.[00:30:59] And so [00:31:00] I wonder ultimately whether the, like this next set of apps actually ends up being more interesting than the, than the first wave.[00:31:05] Alessio: Yeah,[00:31:05] Voice AI and Scheduling Solutions[00:31:05] Jordan: I think a lot of the voice AI ones are interesting too, because you don't need a hundred percent precision recall to actually, you know, have a great product.[00:31:12] And so for example, we looked into a bunch of you know, scheduling intake companies, for example, like home services, right? For electricians and stuff like that. Today they miss 50% of their calls. So even if the AI is only effective, say 75% of the time, yeah, it's crazy, right? So if it's effective 75% of the time, that's totally fine because that's still a ton of increased revenue for the customer, right?[00:31:32] And so you don't need that a hundred percent accuracy. Yeah. And so as the models. And the reliability of these agents are getting better is totally fine, because you're still getting a ton of value in the meantime.[00:31:41] swyx: Yeah. One, this is, I don't know how related this is, but I, one of my favorite meetings at it is related one of my favorite meetings at AI Engineer Summit, it is like, like I do these, this is our first one in New York, and I it is like met the different crew than, than you meet here.[00:31:55] Like everyone here is loves developer tools, loves infra over there. They're actually more interested in [00:32:00] applications. It's kind of cool. I met this like bootstrap team that, like, they're only doing appointment scheduling for vets. They, they, yeah. And like, they're like, this is a, this is an anomaly. We don't usually come to engineering summits 'cause we usually go to vet summits and like talk to the, they're, they're like, you know, they, they're, they're literally, I'm sure it's a[00:32:16] Jordan: massive pain point.[00:32:17] They're willing to pay a lot of money.[00:32:20] Alessio: Yeah. But, but, but this is like my point about saving versus making more, it's like if an electrician takes two x more calls, do they have the bandwidth? To actually do two X more in-house and they get higher. Well, yeah, exactly. That's the thing is like, I don't think today most businesses are like structured to just like overnight two, three x the band, you know?[00:32:38] I think that's like a startup thing. Like mo most businesses then you make an[00:32:42] swyx: electrician agent. Well, no, totally. That's how do you, how do you recruiting agent for electrician, for like[00:32:49] Alessio: electrician. Great. That's a good point. How do you do lambda school for electrician? I, it's hilarious.[00:32:53] Jacob: Whack-a-mole for the bottlenecks in these businesses.[00:32:55] Like as, oh, now we have a ton of demand. Like, cool. Like where do we go?[00:32:58] swyx: Yeah.[00:32:59] Exploring AI Applications in Various Fields[00:32:59] swyx: So just to [00:33:00] round out the, the this PMF thing I think this is relevant in a certain sense of, like, it's pretty obvious that the killer agents are coding agents, support agents, deep research, right? Roughly, right. We've covered all those three already.[00:33:10] Then, then, then you have to sort of be, turn to offense and go like, okay, what's next? And like, what, what about, I[00:33:16] Jacob: mean, I also just like summarization of, of voice and conversation, right? Yep. Absolutely. We actually had that on there. I[00:33:21] swyx: just, I didn't put it as agent. Because seems less agentic, you know? But yes, still, still a good AI use case.[00:33:26] That one I, I've seen I would mention granola and what's the other one? Monterey, I think a bridge was one wanted to mention. I was say bridge. Yeah, bridge. Okay. So I'll just, I'll call out what I had on my slides. Yeah. For, for the agent engineering thing. So it was screen sharing, which I think is actually kind of, kind of underrated.[00:33:42] Like people, like an AI watching you as you do your work and just like offering assistance outbound sales. So instead of support, just being more outbound hiring, you say[00:33:51] Jacob: outbound sales has brought a market fit?[00:33:53] swyx: No, it, it, it will, it's come out. Oh, on the comp. Yeah. I was totally agree with that. Yeah. Hiring like the recruiting side education, like the, [00:34:00] the sort of like personalized teaching, I think.[00:34:02] I'm kind of shocked we haven't seen more there. Yeah. Yeah. I don't know if that's like, like it's like Duolingo is the thing. Amigo.[00:34:08] Jacob: Yeah. I mean, speak in some of these like, you know,[00:34:10] swyx: speak, practice, yeah. Interesting. And then finance, I, there's, there's a ton of finance cases that we can talk about that and then personal ai, which we also had a little bit of that, but I think personal AI is a harder to monetize, but I, I think those would be like, what I would say is up and coming in terms of like, that's what I'm currently focusing on.[00:34:27] Jacob: I feel like this question's been asked a few different ways but I'm, I'm curious what you guys think it's like, is it like, if we just froze model capabilities today, like is there, you know, trillions of dollars of application value to be unlocked? Like, like AI education? Like if we just stopped today all model development, like with this current generation of models, we could probably build some pretty amazing education apps.[00:34:44] Or like, how much of this, how much of, of all this is like contingent upon just like, okay, people have had two years with GBT four and like, you know, I don't know, six months with the reasoning models, like how much is contingent upon it just being more time with these things versus like the models actually have to get better?[00:34:58] I dunno, it's a hard question, so I'm gonna just throw it [00:35:00] to you.[00:35:00] Alessio: Yeah. Well I think the societal thing, it's maybe harder, especially in education. You know, like, can you basically like Doge. The education system. Probably you should, but like, can you, I I think it's more of a human,[00:35:14] Jacob: but people pay for all sorts of like, get ahead things outside of class and you know, certainly in other countries there's a ton of consumer spend and education.[00:35:21] It feels like the market opportunity is there.[00:35:23] swyx: Yeah. And, and private education, I think yeah, public Public is a very different, yeah. One of my most interesting quests from last year was kind of reforming Singapore's education system to be more sort of AI native, just what you were doing on the side while you were Yes.[00:35:38] That's a great, that's a great side quest. My stated goal is for Singapore to be the first country that has Python as a first language, as a, as a national language. Anyway, so, but the, the, the, the defense, the pushback I got from Ministry of Education was that the teachers would be unprepared to do it.[00:35:53] So it's like, it was like the def the, like, the it was really interesting, like immediate pushback. Was that the defacto teachers union being like, [00:36:00] resistant to change and like, okay. It's that that's par for the course. Anyway, so not, not to, not to dwell too much on that, but like yeah, I mean, like, I, I think like education is one of those things that pe everyone, like has strong opinions on.[00:36:11] 'cause they all have kids, all be the education system. But like, I think it's gonna be like the, the domain specific, like, like speak like such a amazing example of like top down. Like, we will go through the idea maze and we'll go to Korea and teach them English. Like, it's like, what the hell? And I would love to see more examples of that.[00:36:29] Like, just like really focus, like no one tried to solve everything. Just, just do your thing really, really well[00:36:34] Defensibility in AI Applications[00:36:34] Jacob: on this trend of of, of difficult questions that come up. I'm gonna just ask you the one that my partners like to ask me every single Monday, which is how do you think about defensibility at the at the app layer?[00:36:41] Alessio: Oh[00:36:41] Jacob: yeah, that's great. Just gimme an answer. I can copy paste and just like, you know, have network effects. Auto, auto response.[00:36:47] swyx: Honestly like network effects. I think people don't prioritize those enough because they're trying to make the single player experience good. But then, then they neglect the [00:37:00] multiplayer experience.[00:37:00] I think one of the I always think about like load-bearing episodes, like, you know, as, as park that you do one a week and like, you know, some of those you don't really talk about ever again. And others you keep mentioning every single podcast. And one of the, this is obviously gonna be the last one. I think the recap episodes for us are pretty load-bearing.[00:37:15] Like we, we refer to them every three months or so. And like one of them I think for us is Chai for me is chai research, even though that wasn't like a super popular one among the broader community outside of Chai, the chai community, for those who don't know, chai Research is basically a character AI competitor.[00:37:32] Right. They were bootstraps, they were founded at the same time and they have out outlasted character of de facto. Right. It's funny, like I, I would love to ask Mil a bit more about like the whole character thing, but good luck getting past the Google copy. But like, so he, like, he, like he doesn't have his own models, basically he has his own network of people submitting models to be run.[00:37:54] And I think like. That is like short term going to be hurting him because he doesn't have [00:38:00] proprietary ip. But long term he has the network network effect to make him robust to any changes in the future. And I think, like I wanna see more of that where like he's basically looking himself as kind of a marketplace and he's identified the choke point, which is will be app or the, the sort of protocol layer that interfaces between the users and the model providers.[00:38:18] And then make sure that the money kind of flows through and that works. I, I wish that more AI builders or AI founders emphasize network effects. 'cause that that's the only thing that you're gonna have with the end of the day. Yeah. And like brand deeds into network effects you.[00:38:34] Jacob: Yeah, I guess you know, harder in, in the enterprise context.[00:38:36] Right. But I mean, I feel, it's funny, we do this exercise and I feel like we talk a lot about like, you know, obviously there's, you know kind of the velocity and the breadth you're able to kind of build of product surface area. There's just like the ability to become a brand in a space. Like, I'm shocked that even in like six, nine months, how an individual company can become synonymous with like an entire category.[00:38:52] And like, then they're in every room for customers and like all the other startups are like clawing their way to try and get in like one, you know, 20th of those rooms.[00:38:59] Jordan: There's a [00:39:00] bunch of categories where we talk about an IC and it's like, oh, pricing compression's gonna happen, not as defensible. And so ACVs are gonna go down over time.[00:39:08] In actuality, some of these, the ACVs have doubled, we've seen, and the reason for that is just, you know, people go to them and pay for that premium of being that brand.[00:39:16] Jacob: Yeah. I mean, one thing I'm struck by is there's been, there was such a head fake in the early days of, of AI apps where people were like, we want this amazing defensibility story, and then what's the easiest defensibility story?[00:39:24] It's like, oh, like. Totally unique data set or like train your own model or something. And I feel like that was just like a total head fake where I don't think that's actually useful at all. It's the much less, you sound much less articulate when you're like, well the defensibility here is like the thousand small things that this company does to make like the user experience design everything just like delightful and just like the speed at which they move to kind of both create a really broad product, but then also every three, six months when a new model comes out, it's kind of an existential event for like any company.[00:39:49] 'cause if you're not the first to like figure out how to use it, someone else will. Yeah. And so velocity really matters there. And it's funny in in, in kinda our internal discussions, we've been like, man, that sounds pretty similar to like how we thought about like application SaaS [00:40:00] companies. That there isn't some like revolutionary reason you don't sound like a genius when you're like, here's applications why application SaaS company A is so much better than B.[00:40:07] But it's like a lot of little things that compound over time.[00:40:10] Infrastructure and AI: Current Trends[00:40:10] Jacob: What about the infrastructure space, guys? Like I'm curious you know. What, how do you guys think about where the interesting categories are here today and you know, like where, where, where do you wanna see more startups or, or where do you think there are too many?[00:40:21] Alessio: Yeah. Yeah, we call it kind of the L-L-M-O-S. But I would say[00:40:24] swyx: not we, I mean Andre, Andre calls it LMOS[00:40:27] Alessio: Well, but yeah, we, well everyone else just copies whatever two. And Andre, the three of you call it the LMO. Well, we have just like four words of ai framework Yeah. Yeah. That we use. And LM Os is one of them, but yeah, I mean, code execution is one.[00:40:39] We've been banging the drum, everybody now knows where investors in E two B. Mm-hmm. Memory, you know, is one that we kind of touched on before. Super interesting search we talked about. I, I think those are more not traditional infra, not like the bare metal infra. It's more like the infra around the tools for agents model, you know?[00:40:57] Which I think is where a lot of the value is gonna [00:41:00] be. The security[00:41:00] swyx: ones. Yeah.[00:41:01] Alessio: Yeah. And cyber security. I mean there's so much to be done there. And it's more like basically any area where. AI is being used by the offense. AI needs to be applied on the defense side, like email security, you know, identity, like all these different things.[00:41:16] So we've been doing a lot there as well as, you know, how do you rethink things that used to be costly, like red teaming and maybe used to be a checkbox in the past Today they can be actually helpful. Yeah. To make you secure your app. And there's this whole idea of like, semantics, right? That not the models can be good at.[00:41:32] You know, in the past everything is about syntax. It's kind of like very basic, you know, constraint rules. I think now you can start to infer semantics from things that are beyond just like simple recognition to like understanding why certain things are happening a certain way. So in the security space, we're seeing that with binary inspection, for example.[00:41:51] Like there's kinda like the syntax, but then there are like semantics of like understanding what is the scope overall really trying to do. Even though this [00:42:00] individual syntax, it's like seeing something specific. Not to get too technical, but yeah, I, I think infra overall, it's like a super interesting place if you're making use of the model, if you're just, I'm less bullish.[00:42:13] Not, not that it's not a great business, but I think it's a very capital intensive business, which is like serving the models. Mm-hmm. Yeah. I think that infra is like, great people will make money, but yeah. I, I, I don't think there's as much of a interest from, from us at[00:42:25] Jordan: least. Yeah. How, how do you guys think about what OpenAI and the big research labs will encompass as part of the developer and infra category?[00:42:31] Yeah.[00:42:31] Alessio: That, that's why I, I would say I search is the first example of one of the things we used to mention on, you know, we had X on the podcast and perplexity obviously as a, as an API. The basic idea[00:42:44] swyx: is if you go into like the chat GBT custom GPT builder, like what are the check boxes? Each of them is a startup.[00:42:50] Alessio: Yeah. And, and now they're also APIs. So now search is also an a p, we will see what the adoption is. There's the, you know, in traditional infra, like everybody wants to be [00:43:00] multi-cloud, so maybe we'll see the same Where change GPD search or open AI search. API is like, great with the open AI models because you get it all bundled in, but their price is very high.[00:43:11] If you compare it to like, you know, XI think is like five times the, the price for the same amount of research, which makes sense if you have a big open AI contract. But maybe if you're just like pick and best in breed, you wanna compare different ones. Yeah. Yeah, they don't have a code execution one.[00:43:26] I'm sure they'll release one soon. So they wanna own that too, but yeah. Same question we were talking about before, right? Did they wanna be an API company or a product company? Do you make more money building Tri g BT search or selling search? API?[00:43:38] swyx: Yeah. The, the broader lesson, instead of like going, we did applications just now.[00:43:42] And then what do you think is interesting infrastructure? Like it's not 50 50, it's not like equal weighted, like it, it's just very clearly the application layer has like. Been way more interesting. Like yes, there, there's interesting in infrastructure plays and I even want to like push back on like the, the, the whole GPU serving thing because like together [00:44:00] AI is doing well, fireworks, I mean I was, that worked.[00:44:02] Alessio: It's like data[00:44:02] Jacob: centers[00:44:03] Alessio: and inference[00:44:03] Jacob: providers,[00:44:04] Alessio: the,[00:44:04] swyx: you know,[00:44:04] Alessio: I think it's not like the capital[00:44:06] swyx: Oh, I see.[00:44:07] Alessio: I for, for again, capital efficiency. Yeah. Much larger funds. So you, I'm sure you have GPU clouds. Yeah.[00:44:13] swyx: Yeah. So that's, that's, that is one thing I have been learning in, in that you know, I think I have historically had dev tools and infra bias and so has he, and we've had to learn that applications actually are very interesting and also maybe kind of the killer application of models in a sense that you can charge for utility and not for cost.[00:44:33] Right? Which, where like most infrastructure reduces to cost plus. Yeah. Right. So, and like, that's not where you wanna be for ai. So that's, that's interesting for, for me I thought it would be interesting for me to be the only non VC in the room to be saying what is not investible. 'cause like then I then, you know, you can I, I won't be canceled for saying like, your, your whole category is, we have a great thing where like, this thing's[00:44:54] Jacob: not investible and then like three months later we're desperately chasing.[00:44:56] Exactly. Exactly. So you don't wanna be on a record space changes so [00:45:00] fast. It's like you gotta, every opinion you hold, you have to like, hold it quite loosely. Yeah.[00:45:02] swyx: I'm happy to be wrong in public, you know, I think that's how you learn the most, right? Yeah. So like, fine tuning companys is something I struggled with and still, like, I don't see how this becomes a big thing.[00:45:12] Like you kind of have to wrap it up in a broader, ser broader enterprise AI company, like services company, like a writer, AI where like they will find you and it's part of the overall offering. Mm-hmm. But like, that's not where you spike. Yeah, it's kind of interesting. And then I, I'll, I'll just kind of AI DevOps and like, there's a lot of AI SRE out there seems like.[00:45:32] There's a lot of data out there that that should be able to be plugged into your code base or, or, or your app to it's self-heal or whatever. It's just, I don't know if that's like, been a thing yet. And you guys can correct me if you're, if I'm wrong. And then the, the last thing I'll mention is voice realtime infra again, like very interesting, very, very hot.[00:45:49] But again, how big is it? Those are the, the main three that I'm thinking about for things I'm struggling with.[00:45:54] Jordan: Yeah. I guess a couple comments on the A-I-S-R-E side. I actually disagree with that one. Yeah. I think that the [00:46:00] reason they haven't sort of taken off yet is because the tech is just not there quite yet.[00:46:04] And so it goes back to the earlier question, do we think about investing towards where the companies will be when the models improve versus now? I think that's going to be, in short term we'll get there, but it's just not there just yet. But I think it's an interesting opportunity overall.[00:46:18] swyx: Yeah. It's my pushback to you is, well it's monitoring a lot of logs, right?[00:46:22] Yeah. And it's basically anomaly detection rather than. Like there's, there's a whole bunch of like stuff that can happen after you detect the anomaly, but it's really just an anomaly detection. And we've always had that, you know, like it's, this is like not a Transformers LLM use case. This is just regular anomaly detection.[00:46:38] Jordan: It's more in terms of like, it's not going to be an autonomous SRE for a while. Yeah. And so the question is how, how much can the latest sort of AI advancements increase the efficacy of going, bringing your MTTR
Sid Victor is the Senior Vice President and Head of Support Services at Movate. He is based in Frisco, Texas, USA. Sid has published his opinion around BPO flexibility on LinkedIn several times. He has made it clear that he feels the future is not human agents OR AI OR any other solution - it is a blend of all the best options and BPOs should be able to offer this blended solution. For example, should BPOs be capable of offering traditional BPO, Gig CX, and AI all under one roof? This is what Sid has been talking about for some time. The future for successful BPOs will need to be about more than just offering an automation service or a contact center. They need to offer a flexible mix of everything - building a CX solution using all these ingredients. Mark Hillary called Sid to find out more... https://www.linkedin.com/in/sid-victor-3355b73/ https://www.movate.com/
Hey CX Nation,In this week's CXWeekly Update we walk through some ideas, goals & CTAs to begin leveraging boutique BPOs as your business grows. Its very common for most Founders or executives to want to hire more full-time staff or add to the team during peak seasons when customer communications, tickets & orders are on the rise. Use this CXWeekly update as a starting point for building out your company's goals around how can begin leveraging BPOs to improve your customer & employee experience.Don't worry we have a ton of amazing guest interviews coming down the pipeline over the next couple of weeks as we start to get crank things up on the content front here at CXC in 2025.Part of our goal for this year is to create more customer focused business leader content, including more short episodes like these ones that are digestible, actionable & most importantly entertaining & valuable for all of you.If you enjoy The CXChronicles Podcast, stop by your favorite podcast player and leave us a review today.You know what would be even better?Go tell one of your friends or teammates about CXC's content, CX/CS/RevOps services, our customer & employee focused community & invite them to join the CX Nation!Are you looking to learn more about the world of Customer Experience, Customer Success & Revenue Operations?Click here to grab a copy of my book "The Four CX Pillars To Grow Your Business Now" available on Amazon or the CXC website.For you non-readers, go check out the CXChronicles Youtube channel to see our customer & employee focused video content & short-reel CTAs to improve your CX/CS/RevOps performance today (politely go smash that subscribe button).Contact us anytime to learn more about CXC at INFO@cxchronicles.com and ask us about how we can help your business & team make customer happiness a habit now!Reach Out To CXC Today!Support the showContact CXChronicles Today Tweet us @cxchronicles Check out our Instagram @cxchronicles Click here to checkout the CXC website Email us at info@cxchronicles.com Remember To Make Happiness A Habit!!
Episode SummaryIn this episode of the Player Driven Podcast, host Greg interviews Łukasz Cieślak, Senior Operations Manager at 5CA. Łukasz shares his journey from support agent to senior operations manager and provides deep insights into the role of BPOs (Business Process Outsourcing) in the gaming industry. He explains how companies like 5CA help gaming studios scale their player support, the essential KPIs that drive player satisfaction, and the growing role of AI in modern support operations. The episode also highlights career advice for those looking to grow from support agent to management roles and explores emerging trends like VIP support and hybrid AI-human models.This conversation offers valuable lessons for gaming studios, support professionals, and anyone curious about the future of player support.Key Takeaways for Indie Developers from the Podcast with Łukasz CieślakOutsourcing Player Support with BPOs BPOs like 5CA allow indie devs to scale support without hiring in-house teams. Outsourcing lets devs focus on core tasks like game development while ensuring players get timely support.Essential Player Support KPIs to Track Track key metrics like service level, quality assurance, and player satisfaction (CSAT or NPS). Consistent support responses are crucial since players share their experiences on platforms like Discord and social media.The Role of AI in Player Support AI tools can handle repetitive inquiries, freeing agents (or indie devs) to focus on complex issues. Hybrid models (AI + human support) are the future, offering faster, more efficient player support.Career Growth and Leadership Lessons Łukasz's journey from agent to senior manager shows the value of proactivity and continuous learning. Indie devs can apply this approach by taking initiative, helping teammates, and being curious about better ways to operate.Emerging Trends in Player Support VIP support is growing in popularity, offering white-glove treatment for high-value players. Personalization and proactive support can build community loyalty, especially for indie devs running Discords or Kickstarter campaigns.These takeaways offer actionable insights on support outsourcing, key metrics, AI, career growth, and player experience trends.Notable Quotes"The companies that will be most successful will have a hybrid model, where agents are equipped with super-advanced AI tools to help them be more productive." – Łukasz Cieślak"If you're a support agent and want to grow, focus on helping others — help your boss, help your colleagues, and stay curious about how things work." – Łukasz Cieślak"Players are vocal on social media and Discord, so if one agent gives one answer and another gives a different answer, it's going to cause issues." – Łukasz Cieślak"AI is more than chatbots. It's everything from data analytics to moderation to making workforce management more efficient." – Łukasz Cieślak"BPOs give game studios the ability to focus on their core competency, like building great games, while outsourcing the complexity of player support." – Greg
Neville Samuels is the CEO of Virtual Staff 365. He is based in Melbourne, Australia. Virtual Staff 365 offers a virtual staffing service that includes CX. In this discussion with Peter Ryan, Neville explores how virtual staffing can help to create a flexible CX environment that can work for in-house teams or BPOs. https://www.linkedin.com/in/outsourcingexperts/ https://www.virtualstaff365.com.au/
Katrin Langley is a CX expert with experience throughout her career at several major BPO companies. She is based in Tampa, Florida. Peter Ryan called Katrin to talk about first-time outsourcing. Most companies still handle their customer service processes in-house, even as it has become more and more complex in recent years. Why do companies still want to retain these processes and what approach can BPOs take to convince them that outsourcing is a positive strategy? https://www.linkedin.com/in/katrinlangley/
Ted Nardin is the VP of Customer Success & Value Add at Teleperformance Jamaica. Ted has spent years researching CX. He recently joined Teleperformance and Mark saw a LinkedIn update with this new job title focusing on customer success and value add. Mark called Ted to discuss this idea. How can BPOs put business success on the table and talk to clients about how to add value in the customer relationship - rather than the usual focus on the cost to serve customers? What more can companies get from all those customer interactions? https://www.linkedin.com/in/tnardin/ https://teleperformance.com/
Vidya Ravichandran is the CEO of UnifyCX. She is based in Louisville, Kentucky, USA. In this conversation with Peter Ryan, Vidya talks about the evolution of GlowTouch Technologies into UnifyCX, how technology is changing the BPO industry, and how CX and BPO is evolving as technology solutions become more integral to customer interactions. As customers demand more complex solutions the BPO community is adopting or building different tech solutions - using AI in particular. But should BPOs buy off-the-shelf tools or create their own and attempt to lead their sector? In this conversation Vidya talks about how BPO is evolving and how the new brand wants to be seen as a CX leader. https://www.linkedin.com/in/vidya-ravichandran-53423b2/ https://www.unifycx.com/
Almost everyone in the CX environment knows about B2B sales. BPO companies need to sell to clients. CX software companies need to sell to customer service teams or BPOs. Most people in this industry are working for specialist companies selling services to another company. Mark Hillary has just written a book about this - how do B2B companies sell to each other and how has it changed since the Covid pandemic? Mark and Peter talked about the new book. What inspired it and why it matters for people working in CX... The book also features a foreword by Paul O'Hara - a legend from the CX environment with a decade plus experience of using social sales strategies for B2B. https://www.linkedin.com/in/markhillary/ https://www.linkedin.com/in/pauloharateleperformance/ The Social Sales Playbook: Developing a B2B Sales Plan That Drives Results Published October 11, 2024 https://www.amazon.com/Social-Sales-Playbook-Developing-Results/dp/B0DJY3MYD2/
Neal Topf is the founder and President of Callzilla. He is based in Miami, Florida. Callzilla is a CX specialist based in the US, but also with delivery centers in Colombia and South Africa. Peter Ryan called Neal for a conversation about corporate culture - in particular culture inside the BPO environment. Neal recently posted on LinkedIn that a prospective client was impressed with the Callzilla technology and their business proposal, but he wanted to meet the team. Seeing the team at work and learning about their daily on-the-job culture was really important to this company - he wanted to build a rapport with the Callzilla team. Neal has often written that prospective clients today are less interested in contact center metrics and much more interested in how the team can help with both sales and service or how engaged the team is and how this will translate into great CX. Clients today are looking for a BPO to have solutions to business problems - not just AHT statistics. Tune in for the latest CX Files where Neal talks about culture and why it is more important than ever for BPOs to have a positive answer when a prospect suggests visiting their team. https://www.linkedin.com/in/nealtopfcustomerexperience/ https://www.callzilla.cx/
In this episode of Dialed In, host Gadi Shamia engages in an enlightening conversation with Ricky Arriola, CEO of Inktel and former City Commissioner of Miami Beach. Dive into the origins of Inktel, a leader in business process outsourcing (BPO), and explore how they've adapted to the evolving landscape of customer service since 1997. Ricky shares his insights on why companies outsource their customer service, the various BPO models, and how Inktel differentiates itself in the market. He also discusses the impact of AI on BPOs, how AI is transforming contact centers, and his vision for the future of the industry. Learn about the balance between AI and human touch in customer service, client responses to AI, and the evolving role of human agents. Tune in for an engaging discussion on the evolution of customer service, the role of AI, and what the future holds for the industry.
RCD. What is it, and can you trust it? Numeracle Podcast Series, The biggest issue that we have globally, is a lack of established circles of trust “The biggest issue that we have globally, is a lack of established circles of trust,” Brett Nemeroff, VP of Engineering – Voice at Numeracle. “Just because someone sends you RCD doesn't mean that you'll instantly trust it and send it on to your customer. But really, for RCD to become effective, we need to standardize on a few things, such as methods and procedures for doing KYC, enforcement methodologies, if people do things that they're not supposed to do, what do we do to stop them from doing that, and then inter-carrier and inter-country trust relationships.” “Because of this, it's possible to send cryptographically verifiable end-to-end caller information, which really has never been possible before.” In this podcast we go deeper into RCD, rich call data. “RCD allows the data to be embedded inside of a shaken passport, which means that it's signed by the originating character that is expected to be performing KYC on the customer.” Adds Brett. “Because of this, it's possible to send cryptographically verifiable end-to-end caller information, which really has never been possible before.” We learn how RCD is part of Numeracle's broader vision: “What we're trying to do is we're trying to help restore trust into communications.” In today's recording we learn where RCD being used today, availability domestically and internationally, relevance to STIR/SHAKEN and if it be spoofed? As RCD gains traction, it becomes more central to commerce, communication and more. About Numeracle: Numeracle is an industry pioneer and leader with actionable solutions for legal callers that prioritizes their calling identity as the foundation to restoring trust in the voice channel and to their calls by removing barriers, like improper spam labels, from harming their phone numbers. Numeracle's Entity Identity Management™ (EIM) platform puts enterprise brands, BPOs, and service providers in direct control of their identity, which we vet and verify. Our EIM platform can also be used to manage branded communications, to improve call reputation with blocking and labeling prevention and spam label remediation, and we provide visibility into call display to ensure brand identity is presented as intended, with transparency and consistency. Our KYC-based identity vetting and verification is the cornerstone of the platform; developed in support of evolving federal regulations and telecom standards.
You DON'T need a ton of money to find and fund real estate deals. Despite earning just $15,000 per year, today's guest found the perfect property for him and scrounged the money to close. If you're willing to learn, network, and put yourself out there, you can do the same! Todd Fullerlove Jr. had recently graduated college, gotten married, and welcomed his first child when the reality of starting a family hit him like a ton of bricks. Living paycheck to paycheck, his little family was forced to move in with his mom. Todd knew something had to change and decided to give real estate investing a try. The only problem? He had no money! Fortunately, Todd had learned that you don't need to be sitting on a pile of cash to get started. So, Todd did what every smart investor does—he found the deal first! From there, he built relationships and raised capital. Just by taking action, Todd has completed five deals in five years! In this episode, Todd will show you how to find and fund off-market deals through the power of private money. You'll also get a full breakdown of the short sale process, from working with banks to navigating home appraisals and broker price opinions (BPOs). Stick around until the end to hear about the loan Todd used to buy his first rental property with low money down! In This Episode We Cover How Todd went from making $15,000 per year to landing five real estate deals How to get 100% funding for your deals through the power of private money Short sales explained and why banks are motivated to work with you What you NEED to know before tackling DIY home renovation projects The BIG difference between a home appraisal and a broker price opinion (BPO) Buying rental properties with low money down using USDA loans And So Much More! Check out more resources from this show on BiggerPockets.com and https://www.biggerpockets.com/blog/rookie-423 Interested in learning more about today's sponsors or becoming a BiggerPockets partner yourself? Email advertise@biggerpockets.com. Learn more about your ad choices. Visit megaphone.fm/adchoices
Unveiling Accelerated Business Success by Unlocking AI Potential We welcome Joe Buggy to this week's episode of the Digitally Irresistible podcast. As an innovative executive leader with a rich background in operations, business development, and finance, with specialization in the BPO sector, Joe is renowned for his strategic insights. Growing up as the son of an Air Force family with Irish-Italian heritage, Joe developed a keen eye for detail and a knack for problem solving. His passion for optimizing processes and delivering results, fueled by his experiences working alongside industry-leading professionals, has shaped his career trajectory. Leveraging his deep expertise in trust and safety and content management, Joe has led the charge on multiple transformative endeavors for business process outsourcing (BPO) companies, propelling growth and performance within these customer-centric enterprises. In this episode, we delve into the world of data annotation and labeling and its impact on the business world. Exploring Content Management and Data Annotation To provide context, we first explore the realm of content management—a cornerstone of brand representation and engagement in the digital age. Joe explains how content management encompasses everything from digital presence to product portrayal, emphasizing its pivotal role in shaping brand perception and customer experience. Transitioning to the core of our discussion, Joe breaks down the concepts of data annotation and labeling, which are critical aspects of content management since they ensure a brand's content is accurately described in its systems. He explains that labeling involves assigning simple tags to unstructured data, such as images or text, to facilitate understanding of artificial intelligence (AI) algorithms. Joe gives an example of a cat image, where the label "cat" informs the system about the content, demonstrating that this process extends to all forms of data. Annotation, however, adds layers of context, enabling more nuanced interpretation and data utilization for sentiments, uses, or directions. If we consider four primary data types—numerical/alphanumeric text, images, audio, and video—the complexity and unstructured nature increase as we move from numeric to alphanumeric to image, audio, and video data. This escalation underscores the crucial need for labeling and annotation to provide context for AI models. For example, in image recognition, labeling each image with metadata such as "flower species" enables AI to accurately classify different types of flowers. Similarly, in audio transcription, labeling with timestamps and the speaker identities ensures precise transcription of conversations. In video analysis, annotations like "suspicious behavior" help AI detect and respond to specific events. Overall, labeling and annotation are essential for transforming raw data into structured information that AI can effectively understand and utilize across various applications. The Intersection of Annotation, Industry Applications, and Deliberate Partnerships in AI Development In our deep dive into the realm of AI development, Joe further illuminates the pivotal role of annotation and labeling. He explains how these foundational processes serve as the bedrock for training AI models, elevating their accuracy and contextual understanding to unprecedented levels. Joe underscores the importance of structured data in this process, emphasizing how it enables AI algorithms to glean meaningful insights and make more accurate predictions that drive successful outcomes for brands. As we cross the landscape of data annotation and labeling, Joe provides a panoramic view of their diverse applications spanning numerous sectors. From the dynamic realms of health care, where AI powers telemedicine and aids in drug development, to the bustling domains of retail , where every retailer strives for a seamless omnichannel customer experience (CX) Joe explains how AI-driven solutions create transformative changes. In health care, AI models assist in diagnosing medical problems and understanding drug interactions by relying on meticulously labeled data. Similarly, in retail, AI improves customer experiences by allowing users to virtually try on clothing or eyeglasses tailored to their body style or face shape. These algorithms continuously learn from user preferences, suggesting products that align with individual tastes, akin to the automotive industry's use of AI for autonomous vehicles and predictive maintenance. Across digitally native industries, travel services, consumer products, and gaming, AI's integration optimizes operations, predicts market trends, and fosters brand acceptance through data-driven insights and personalized recommendations. Given the scale and complexity inherent in data annotation, Joe describes the importance of forging partnerships with BPO organizations. Joe highlights how these collaborations empower brands to navigate the intricate landscape of AI development with confidence and agility. By tapping into BPOs' depth of knowledge in annotating and labeling data—whether through bounding box, semantic annotation, video annotation , or cuboids—brands can ensure high-quality data preparation crucial for computer vision, natural language processing, and audio processing applications. BPOs excel by identifying and hiring top talent and training them rigorously in specialized systems and processes. Moreover, these partnerships enable continuous improvement through robust quality monitoring, feedback mechanisms, and coaching to drive new goals and introduce optimized processes. Through strategic collaborations, Joe envisions a future where innovation knows no bounds and the transformative potential of AI is fully unleashed to shape a brighter tomorrow. With support from BPOs, organizations can confidently build and execute their AI strategies with the scalability, quality, and security needed for success. Navigating Security, Privacy, and Brand Considerations in AI Initiatives In our exploration of AI initiatives, Joe delves into the critical aspects of data security and privacy. Addressing pertinent concerns surrounding the handling of consumer and proprietary data, Joe emphasizes the need for robust measures to safeguard sensitive information and the importance of implementing stringent protocols and cutting-edge technologies to ensure compliance with regulatory standards and instill trust among stakeholders. By prioritizing security and privacy in AI-driven initiatives, organizations can mitigate risks and uphold the integrity of their data assets, paving the way for sustainable growth and innovation in the digital landscape . With significant experience in navigating the complexities of AI implementation, Joe's valuable insights highlight key considerations that can shape the success of brands seeking to harness the full potential of AI. He points out the significance of aligning AI strategies with organizational goals and values , ensuring a cohesive approach toward driving business objectives. Identifying gaps in expertise and resources and forming tactical partnerships with trusted providers can help augment a company's capabilities and ensure seamless execution of services. Adopting a holistic approach and leveraging the expertise of external partners enables brands to unlock the full potential of AI technology, driving innovation and sustainable business growth in today's competitive landscape. "Identify where [your brand's] gaps are and if those gaps include meeting the speed, the scale, the different data types, and the security at a level of accuracy and consistency that the organization requires, I would look to partner with a trustworthy organization to address those gaps." - Joe Buggy What Joe Likes to Do for Fun When not working, Joe enjoys outdoor cooking and golf, highlighting the importance of work-life balance and sharing cherished moments with friends and family. To learn more about Joe, connect with him on LinkedIn. Watch the video here. Read the blog post here.
Are you confused about Reverse Mortgages vs. Traditional Notes? This episode and video equips you to evaluate and bid on reverse mortgage deals involving deceased borrowers who leave behind vacant properties.In this episode, Scott Carson dives deep into:Key Differences: Reverse Mortgages vs. Performing/Non-performing NotesEvaluating REO & Fix & Flip Opportunities: When Inheriting Property with a Reverse MortgageBidding Strategies: Analyzing Seller Reserve, BPOs, Inspections & Legal StatusInsider Tips: Accessing Seller Information & Due Diligence Reports (Free Resources!)Unlock Hidden Value: Learn how to identify profitable reverse mortgage deals and craft winning bids in today's market.Bonus: Discover how to obtain Seller Reserve Bids, Property Access & Due Diligence (Free with WCN Crew Membership: Link to Note Umbrella: [HTTP://noteumbrella.com])Watch the original VIDEO HERE!Book a call with Scott HERE!Love the show? Subscribe, rate, review, and share!Here's How »Join the Note Closers Show community today:WeCloseNotes.comThe Note Closers Show FacebookThe Note Closers Show TwitterScott Carson LinkedInThe Note Closers Show YouTubeThe Note Closers Show VimeoThe Note Closers Show InstagramWe Close Notes Pinterest
Registration is now open for the Gartner CFO & Finance Executive Conference, Gartner's flagship CFO event, on 20-21 May 2024 in National Harbor, Maryland. Reserve your space today.Listen to this exclusive preview of the Gartner CFO & Finance Executive Conference, which helps organizations unlock enterprise value by transforming finance's top roles:CFO: Mastering digital transformation. Measuring AI initiative risks and opportunities.Financial planning and analysis (FP&A): Modernizing data architecture. Creating business partnership influences.Controllers: Revamping governance models. Discovering the future of blockchain and accounting.VP of Finance Transformation: Building future organizational models. Evaluating consulting firms and business process outsourcing (BPOs).Episode highlights: The urgency behind the conference's autonomous finance theme (1:25)The CFO role is expanding to AI initiatives and cybersecurity (6:29)FP&A skill sets for modernizing data architecture (9:25)Controllers are under serious pressure with governance models and automation (11:24)VPs of financial transformation must build future organizational models (13:02)Cutting through the AI hype with expert interactions (15:37)
CX Outsourcers Special Edition: For the next two weeks CX Files will be published on both Monday and Thursday giving previews of the talks that will be taking place in Atlanta at the CX Outsourcers conference on May 1/2... --- Paula Kennedy Garcia is an old friend of the CX Files. She has senior experience in several leading BPOs and is know as a leader in CX innovation and new delivery models. Paula is based in Belfast. In this conversation with Mark Hillary she talks about her planned talk on digital CX to the CX Outsourcers conference in Atlanta on May 1/2. Unfortunately, Paula has had to cancel her visit to Atlanta just before the broadcast of this epsiode (Peter and Mark recorded this about a week before broadcast), but it would be a shame to not hear the conversation so we have still published it here. https://www.linkedin.com/in/paula-kennedy-garcia-1b90b81/ https://cxoutsourcers.com/
In this episode, host John Walter talks with Braden Ream, the co-founder and CEO of Voiceflow. They delve into the evolution of conversation design with the advent of large language models. Braden shares insights into the shift from traditional methods to AI-driven approaches and discusses how Voiceflow is pioneering in this space. The discussion also touches upon the emerging trends in outsourcing and BPOs, highlighting the integration of AI in these sectors.Additional Resources:Connect with Braden Ream on LinkedIn: https://www.linkedin.com/in/braden-ream/Learn more about Voiceflow: https://www.voiceflow.com/Connect with John Walter on LinkedIn: https://www.linkedin.com/in/jowalter/
Imagine navigating the rapid changes in the Business Process Outsourcing (BPO) industry with the help of Artificial Intelligence (AI). How do BPOs need to adapt and evolve to stay competitive in this AI-driven landscape? That's what we're discussing in this enlightening episode, drawing insights from a seminar at the Google campus and exploring the potential of technology to revolutionize contact centers.With a focus on enhancing customer experience (CX), we delve into how technology can be a gamechanger. From backfilling headcount to reducing average handle time, we explore how becoming CX partners for clients can transform your business. We also examine how analytics can provide a deeper understanding of customer sentiment and how gamification can add value to the customer journey.Are you ready for the future of BPO technology? We discuss how BPOs need to become proficient in the latest tools to offer value to customers. From leveraging features like auto summarization and Agent Assist to understanding the impact of chat GPT and its new voice capabilities, we cover it all. We also highlight the significance of automated voice services in increasing customer engagement. Tune in, stay updated, and remain competitive in this ever-evolving industry.We're gearing up to launch OttoQA, the game-changing QA automation tailored for smaller contact centers. But here's the twist — we want you in our inner circle before anyone else. Sign up at ottoqa.com with your email, and you'll dive deep into our exclusive Discord, join insightful industry AMAs, and be first in line for beta testing when Otto rolls out. Be part of our pre-launch excitement and help shape the next big thing in QA!Follow Tom: @tlaird_expiviaJoin our Facebook Call Center Community: www.facebook.com/callcentergeekConnect on LinkedIn: https://www.linkedin.com/in/tlairdexpivia/Follow on TikTok: https://www.tiktok.com/@callcenter_geekLinkedin Group: https://www.linkedin.com/groups/9041993/Watch us: Advice from a Call Center Geek Youtube Channel
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