Functional Executives

With so many AI tools hitting the market, which ones are actually worth using?

In this episode of the Functional Executives Podcast, Jim Boswell and Veer Hossain share their top five AI tools and productivity solutions they personally use to save time, streamline workflows, and deliver measurable business value.

From Claude and ChatGPT Codex to AI meeting recorders, voice dictation, and personal knowledge systems, Jim and Veer discuss what's working, what's changing, and which tools they've stopped using.

In this episode, we explore:

✔️ Claude in Excel and how AI is changing financial workflows

✔️ Claude Cowork and ChatGPT Codex for everyday productivity

✔️ Plaud and the value of capturing meeting conversations and decisions

✔️ Building an AI-powered "second brain" that keeps your knowledge accessible

✔️ Why voice dictation could dramatically change how you work

✔️ GitHub, Manus, and other tools that extend AI's capabilities

✔️ Why some once-popular tools are disappearing from their daily workflows

Whether you're a CEO, CFO, business owner, or executive exploring AI, this conversation offers practical ways to start putting AI to work without getting overwhelmed by all the options.

The takeaway? You don't need every AI tool. You need the right tools working together to help you get more done.

Subscribe to the Functional Executives Podcast for conversations about AI, business strategy, operational efficiency, and creating measurable business value.

🌐 https://www.functionalexecutives.com

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AI is no longer just answering questions. It's doing the work 🤖

What happens when artificial intelligence moves beyond chatbots and starts making decisions, managing workflows, and delivering real business results?

In this episode of Functional Executives, hosts Jim Boswell and Veer Hossain sit down with Justin Rae, Founder & CEO of Cinch, to explore how AI is transforming the way businesses operate—and why the biggest opportunities may still be ahead.

Justin shares firsthand experiences implementing AI across his organization, from Claude Code and intelligent agents to the exciting concept of "self-driving marketing."

In this episode, we explore:

- Why AI adoption isn't necessarily about fear—and what really holds employees back

- How AI agents are transforming productivity, sales, and customer service

- The game-changing capabilities of Claude Code and other AI tools

- Why giving employees room to experiment with AI matters

- How businesses can use AI without losing human oversight

- The potential of self-driving marketing and autonomous AI systems

- What executives should be doing now to prepare for what's next

💡 The big takeaway: AI isn't simply another technology investment. It's changing how work gets done, how teams operate, and what's possible for businesses of every size.

If you're a CEO, CFO, entrepreneur, or business leader looking to move beyond AI hype and understand what's actually working, this conversation is for you.

🌐 Explore more episodes and insights: https://www.functionalexecutives.com

Subscribe to Functional Executives for practical conversations on leadership, technology, business strategy, and operational excellence.

In this episode of Functional Executives, hosts Jim Boswell and Veer Hossain sit down with Evan Moser, CTO of iClassPro, to explore how AI is changing software development inside a real business.

Evan shares how his team used AI to accelerate a major modernization project while keeping experienced developers involved in the process.

We discuss:

+ How AI can dramatically speed up development

+ Why human oversight still matters

+ QA bottlenecks, security risks, and technical debt

+ Claude Code, AI agents, and developer productivity

+ The cost of scaling AI inside an organization

If you’re a CEO, CFO, CIO, CTO, private equity leader, or executive trying to understand how AI can create real business value without sacrificing quality or security, this episode offers a practical look at what’s working now.

AI isn’t just changing how finance and accounting teams work. It’s beginning to change what companies expect from the executives leading them.

In this episode of Functional Executives, Jim Boswell and Veer Hossain sit down with Ken Philbrick, Partner and Founder of Adam James International, an executive search firm that recruits CEOs, CFOs, and other senior leaders for private equity-backed middle-market companies.

Ken shares what he is seeing firsthand as AI begins reshaping finance, accounting, executive recruiting, and the talent market. The conversation explores automation of repeatable accounting functions, the growing connection between finance and technology, and why AI fluency and intellectual curiosity are becoming increasingly important for CFOs and other executives.

They also discuss what AI still can’t replace: judgment, relationships, behavioral insight, and the human nuance required when hiring and leading at the executive level.

And for executives preparing for their next opportunity, Ken offers an important insight: companies are already beginning to include AI capabilities in executive scorecards and expectations. For CEO and CFO candidates, demonstrating how AI fits into a 90-day plan may increasingly become part of the conversation.

In this episode:

• How AI is changing finance and accounting organizations

• What executive recruiters are seeing from CEOs and CFOs

• Why finance and technology are becoming more interconnected

• Where AI can automate work and where human judgment still matters

• AI fluency as an emerging executive leadership competency

• How companies can encourage adoption while managing risk

• What AI could mean for the future talent pipeline

• Why curiosity and adaptability may matter more than ever

If you’re a CFO, CEO, finance leader, private equity professional, or executive navigating how AI is changing your organization and your career, this conversation offers a practical look at what’s already happening in the market.

Veer and Jim get honest about what it actually takes to prepare a mid-market company's data for AI — and why "getting your data ready" means a lot more than your operational data warehouse. They dig into the maintenance burden nobody talks about, why shortcutting the learning curve costs you the nuance that makes AI valuable, and how to think through the build-versus-buy decision when you're evaluating your own "second brain" for the business.

What we cover

It's not your database data. The AI-readiness conversation is really about the messy, unstructured stuff — SharePoint files, conversations, one-off projects — not the operational data warehouse you've had for 20 years.

Categorization is the real bottleneck. Before anything else works, you have to decide how to model and bucket your data, and make sure those buckets connect. Most teams get stuck right here.

Not everything in your files is authoritative. That folder your summer intern filled isn't a source of truth just because it's in SharePoint.

You can't shortcut the learning curve. Veer and Jim talk about why "getting the reps in" matters — skip the hands-on iteration and you lose the nuance that makes these tools actually useful.

Build or buy your "second brain"? The two dig into what it means to build (or buy) an AI system for a company — ownership, champions, "pioneers" inside the org, and why the right call depends heavily on where you are in your maturity curve and how close you are to an exit.

The maintenance nobody budgets for. Whichever path you choose, the system needs ongoing care — security, infrastructure, search tooling — as your data and scale grow.

A preview of what's next. Jim teases an upcoming deep dive on the AI maturity curve and power users, plus mentions of new guest interviews and more on "OpenBrain" in future episodes.

Notable moments

1:18 — Jim: "They're not talking about your operational data warehouse that you've been using for 20 years. They're talking about all the other stuff that adds the color to that financial or operational data."

2:45 — Jim on the real issue with data modeling: "You've got to really decide how to categorize all of this data... those buckets all have to be connected with a pipe."

3:45 — Veer: "The files that are in SharePoint that your summer intern uploaded are not necessarily authoritative documents, right?"

10:08 — Jim frames the core question: "If you were going to build a second brain... for your company... do you build this or do you go find [a vendor]?"

15:41 — Veer: "There's a durability with buy that you don't get with build, especially if it's not your competency."

18:33 — Jim's takeaway: as your data and scale grow, you'll have to keep rethinking both your maintenance and your search tooling.

Timestamps

0:00 — Categorizing and modeling data
4:00 — Reflecting on lessons learned
7:20 — Importance of hands-on experience
10:46 — Aligning investments with company goals (build vs. buy)
15:59 — Teaser: the AI maturity curve
18:33 — Scaling and data management, key takeaway

We'd love your feedback — what should we go deeper on? What could we cut? Drop a comment and let us know.

Welcome to Functional Executives, where Jim Boswell and Veer Hossain peel back the glossy pitch deck to give a ground-level field report on building personal AI "Open Brain" systems. If you're a leader thinking AI will magically 10x your productivity (spoiler: it won’t), or just want to know what actually happens after the hype, this one’s for you.

• The Reality Behind the Brochure: Jim Boswell and Veer Hossain share why their Open Brain prototypes—meant to be the digital second brains—work well… until they really don’t.
• The Raccoons Analogy: Turns out, today’s AI tools often feel like "three raccoons in a trench coat." Yes, it sounds ridiculous—but so is believing one click solves enterprise search and data nightmares.
• Personal Use Cases & Real Revenue: Veer Hossain discusses how his system actually saved time, made money, and pulled context for consulting proposals faster than a caffeine jolt.
• CRM Heartbeating: Jim Boswell’s OpenBrain combs through emails, preps his daily top 5 messages, and ensures no client thread is dropped—though, as always, human review is a must.
• Data Problems Don’t Magically Disappear: Still using that 1997 spreadsheet? So is your AI. Veer Hossain explains why bad data makes for bad answers, no matter how shiny the LLM.
• Surprise, You’re in IT: From rotating API keys to ongoing database maintenance, personal AIs generate their own tech debt. It’s not a “set and forget” world—welcome to your new hobby.
• Scaling Lessons for Enterprises: Every pain Jim Boswell and Veer Hossain felt building solo gets multiplied (and much more critical) at organizational scale. AI changes work dynamics, but not the laws of data and common sense.

• If you’re thinking AI will just “figure it out,” expect a lot of digital trash pandas rifling through fifteen copies of Final_Version_V2.xlsx.
• Maintenance, data curation, and being explicit about what you want are the new table stakes.
• LLMs are powerful, but they’re not mind readers—and handing off your work without review is still a career-limiting move.
• Building your own tools forces you to learn fast what “good” actually looks like—often by failing first.

Join Jim Boswell and Veer Hossain for this dry-witted, reality-check episode—ideal for digital execs, AI-curious leaders, and anyone tired of tech evangelists promising too much, too soon.

Subscribe for more no-nonsense talk on building practical, functional digital tools—minus the hype.

This week, Veer and Jim Boswell spiral into the sensory details of cultural comfort food, childhood culinary trauma, and the battle for olfactory dominance in the American home. From stone-ground spices to Swanson’s TV dinners hotter than fresh magma, it’s a nostalgic, scent-heavy tour through food memories and the way they shape our lives (and the air quality in our kitchens).

• Veer shares stories of his mom's two-inch thick stone tablet, used to hand-grind spices into paste — a process that leaves both flavor and unforgettable scents wafting for days
• Jim Boswell confesses his fascination with "spice kitchens" — heavily ventilated mini-kitchens designed to contain the glorious chaos of toasting spices
• The delicate art of cooking outside to keep the house from becoming an aromatic time capsule

• A home divided: Veer recounts his family's allergy to flowery scents and the ever-present Glade plug-in migraine
• Jim Boswell waxes poetic about the dark amber notes of Pura fragrances — not everyone’s cup of sandalwood tea

• From Indian curries to the best hummus in Toledo, Veer and Jim Boswell dissect how moving around the U.S. is really just a culinary adventure with a side of new friends
• The existential crisis of kids preferring sodium-bomb Salisbury steak to homemade cuisine

• A love/hate manifesto on pot roast, microwave mashed potatoes, and the dubious joys of apple cobbler that could probably power a small reactor
• Food shapes nostalgia — and sometimes, weirdly, adulthood brings you right back around.

• A whistle-stop tour of American food geography: Mediterranean cravings in Toledo, Lechón Asado in South Florida, and the holy grail of Nashville hot chicken

• "Veer's here! I smell curry!"
• "A carrot that tastes like a cow is the best kind of carrot."
• "The apple cobbler was like magma. You had to wait 2 hours to eat it or you burned everything."

• Missing comfort food? Try a slow-cooked pot roast and get back to your roots

• What scents immediately bring you back to childhood?
• Does your family have any “cultural kitchen hacks” to keep the peace (or the smell) in check?
• TV dinner nostalgia: Is it real, or does it evaporate once you taste a real meal?

The conversation focused on the widening gap between AI hype and actionable adoption in mid-market companies. A key theme that emerged was the persistent focus on the latest AI models and industry arms races, while overlooking the pragmatic ways AI can transform less glamorous—but critically important—business workflows. The discussion explored why the typical headlines about “game-changing” models miss the real concerns of most companies and how functional leaders should reframe their approach.

• Several points were raised, including the tendency for media to spotlight either mega-corporations burning mountains of cash or trendy micro-startups, while the economic engine—the midmarket operators—gets ignored

• One concept discussed was the difference between talking about technology and extracting real business value from it.
• Instead of asking, “What’s the latest model?” a more valuable question is, “How does this help my team operate faster, with less grind, and more accuracy?”

• There was a breakdown of "quantization," which basically means compressing large language models to run on smaller, local devices—trading off some precision for speed and privacy
• The group compared this to giving street-by-street directions instead of a pinpoint GPS—less accurate, but often good enough

• Small models keep things private, but if only one analyst can use it, we’re right back where we started with locked-up spreadsheets. A key theme that emerged was the need for good architecture: how will your company balance privacy, collaboration, and resilience?

• The discussion explored real-world examples, like automating a 13-week cash flow forecast or report generation. The focus was on freeing up smart humans to actually interpret and act on the data—not grind through compiling it
• Using AI to build durable, repeatable scripts (think of it as your own private IT team without the ticketing system) was highlighted as a difference-maker

• Despite the buzz, adoption remains sluggish among even tech-savvy organizations—a surprising revelation for all involved
• The bottom-line advice: Stop waiting for the “perfect” model. Pick a use case, get reps, and build momentum. Budget a few bucks for professional development—skip the overpriced conference and just play with the tools already

• Which workflows have you quietly revolutionized? How is AI actually showing up in your organization—beyond the hype? The team wants your feedback!
  • Drop a comment or shoot a message on LinkedIn.

Next time: Expect more hands-on stories, and maybe a few guests who’ve stopped talking and started doing. Until then—close the newsletter tab and start building.

In this episode, Veer Hossain and Jim Boswell are joined by Justin Rae, CEO of Cinch, to geek out about AI agent orchestration, local inference on SparkBoxes, and the future of "self-driving" marketing. The crew dig into what’s actually working at scale (spoiler: tinkering leads to full-blown ops), how to cut the fat from marketing workflows, and why handing the mundane off to bots is your new superpower.

• From At-Bats to Galactic Swings: Justin Rae breaks down why getting reps with AI tools matters more than obsessing over which local model to run.
• SparkBoxes Galore: What workloads actually make sense to run locally? Justin Rae has three (and counting) running monitoring, code analysis, and more.
• Kill the Token Tax: Running continuous AI agents in the cloud is expensive. Local inference saves serious cash…and gives you ultimate control.
• Workflow Fixes, Not Just Flags: It’s not just monitoring—Cinch’s agents actually queue up and propose fixes, with humans as the final gate.
• Human-in-the-Loop Done Right: Build trust in your agents, level up the team, and become the AI orchestrator they’ll fight to hire in three years.
• Self-driving Marketing Roadmap: Like self-driving cars, there are levels. Justin Rae lays out where Cinch sits today and where it’s headed.
• Level Up, Don’t Fear Up: This isn’t about killing jobs—it’s about empowering people to punch above their weight and own the new tools of the trade.

• Events:
  • Pestworld
  • SEMA
  • Apex (November)
  • Various regional shows in home and automotive services throughout the summer
• Website: cinch.io
  Want to put their AI voice agent to the test? Sign up for a demo or check out the self-serve option right from their homepage.

“The future is you managing your own agents. I want you to leave here the most AI-versed marketer anywhere.” – Justin Rae

“Why don’t we have self-driving marketing yet? You’re not going to kill someone if you botch an email, right?” – Justin Rae

For the exec who wants to game harder and manage smarter: get your hands dirty, reap the at-bats, and show your agents who’s boss—before someone else does.

• Subscribe on your favorite podcast platform.
• Give us a shout if you automate something over the weekend instead of mowing the lawn.
• Connect with Justin Rae and Cinch at cinch.io or at any of the events above.

Episode Summary

What happens when you stop seeing AI as just another chatbot and start wielding it like a pneumatic nail gun? In this episode, the team sits down with Justin Rae, CEO of Cinch, to dissect what it really takes to integrate AI into ops, products, and even the back office. From orchestrating multi-agent AI stacks to hacking the digital equivalent of "knowing your customer," this conversation is loaded with dry wit, real-world stumbles, and the relentless pursuit of 10x gains.

Highlights

• AI Isn’t Just a Chatbot Anymore
  • Discussion centered on evolving AI from "just a chatbot" to orchestrating real-world tasks—answering phones, making data-driven decisions, and driving measurable business results.
  • Emphasis on the challenges of building, maintaining, and trusting AI systems. It’s about more than hype: when an AI fails, who fixes it?
• From Data is the New Oil to Actionable Customer Insights
  • "Data is the new oil" still rings true, but the power is now in execution—taking the raw data, matching it to customers, and replicating the kind of relationship the old-school shopkeeper had with regulars, just at digital scale.
  • AI is unlocking hyper-personalized marketing, like tailoring offers and tones in emails based on granular customer habits and preferences.
• Real-World Machine Learning Use Cases
  • At Cinch, the team uses machine learning to segment customers by value and price sensitivity, not just at launch but updated dynamically as habits and markets change.
  • This means customers aren’t treated equally—if a previously valuable client now lags the pack, the system catches it and adapts outreach accordingly.
• Iterate (and Fail) Your Way to Wins
  • The company culture is built around hands-on experimentation with AI, including regular “build something cool with AI” contests—gift cards for the winners, and bragging rights for days.
  • Not everything works: iterative “at-bats” are essential. The key is giving people space for a good first experience, which unlocks imagination and adoption.
• Change Management, Minus the Corporate Spin
  • You want to get knowledge workers, engineers, and everyone from sales to support using AI? Make it about reducing real pain—prioritizing tickets, finding faster answers, masking data for demos on the fly.
  • Incentives and space to experiment beat another round of PowerPoint-driven “AI transformation” meetings every time.

Quick Takeaways

• Try more, judge less. The path to AI ROI is paved with failed experiments and accidental discoveries—just like the training data.
• Make experimentation safe and worthwhile. Incentivize, don’t just assign.
• Hyper-personalization isn’t science fiction. Mapping data to behavior means marketing finally gets truly one-to-one.

Timestamps of Note

• [01:21] AI’s role beyond chatbot basics
• [05:30] Data-driven customer value segmentation
• [09:08] Customizing marketing tones and content
• [14:13] Building internal AI culture with contests
• [19:26] Overcoming mental and procedural barriers
• [24:07] Real examples of AI driving business efficiency
• [29:50] AI as the power tool of modern work

Functional Executives—yes, change is hard, but the 10x upside is real once you evolve past the “it’s just another chatbot” phase.