Recommendation · MoneyA key challenge is capturing the vocabulary: you have numerical values, categorical values, and information like zip codes, raising the question of whether to encode each zip code as a token. Push significant effort into understanding the vocabulary you need and the vocabulary you want to scale. If your vocabulary is far too big at training time, it becomes messy to train such a model. Invest effort in deciding which information to encode in a token (value-to-token mapping). A too-huge vocabulary makes training a tabular foundation model messy, so significant effort is needed deciding which values to encode as tokens.
AI Engineer · A Bank Trained Its Own Foundation Model to Catch Fraud — Freddy Lecue, Wells Fargo
Recommendation · MoneyWhen a call ends awkwardly with just 'thanks for the time,' respond with: 'This is a great use of time. Thanks again for spending all this with us. I've got a couple of ideas. Based on what you shared, there's a couple of different things we can do to help you. I'd love to give you a tour of our technology... and talk about how this can specifically apply to the things you shared with me today. How does that sound?' Don't give a demo or a 98-slide PowerPoint deck — offer a 'tour of our technology' instead. Make every demo bespoke to what the prospect shared: 'I'm not going to give this same canned crap that I've given 19 times today. I'm going to give you something that's bespoke because I actually listen.'
30 Minutes to President's Club | No-Nonsense Sales · #619: Active Listening to Loosen up Your Discovery Calls and First Dates | Sam McKenna | 30MPC Hall of Fame
Recommendation · MoneyInstead of 'What brought you here today?', open discovery calls with a broad, open-ended question — e.g., 'I could tell you a million things about my company, but I'd love to hear from you first: your team, your challenges, the overall landscape.' This 'cracks their head open': the buyer explains why they showed up in a super professional way rather than narrowly adhering to what the contact form said. Don't fixate on the contact form — acknowledge it, then redirect to broader questions and get to the specific topic later.
30 Minutes to President's Club | No-Nonsense Sales · #619: Active Listening to Loosen up Your Discovery Calls and First Dates | Sam McKenna | 30MPC Hall of Fame
Recommendation · MoneyAfter securing the next meeting, ask: 'Who else would benefit from this in your organization? Do you have peers on other teams or in other lines of business — or pending you seeing this and it being successful, anybody else that you think would need to see this before deciding if we want to move forward?' Framing the ask around who would benefit is less salesy and more customer-centric, making prospects more likely to name two or three people. Expect some prospects to refuse ('I'm the ruler of all things. And you have to go through me first') — it's not a silver bullet, there are no silver bullets in sales, but it's a great start.
30 Minutes to President's Club | No-Nonsense Sales · #619: Active Listening to Loosen up Your Discovery Calls and First Dates | Sam McKenna | 30MPC Hall of Fame
Recommendation · MoneyDon't pepper a prospect with questions for the full 30 minutes — weave in a customer story that mirrors their situation, including specific numbers, then stop and let them react. Structure it as: situation match ('a customer came to us with the same thing'), what you did, how you solved it, and the coolest result — e.g., a final sequence with an 80% open rate and ~7% response rate. After delivering the punchline, pull the rug out and move to the second point — the goal is to make the prospect say 'we want that' repeatedly throughout the call so next steps happen without pushing.
30 Minutes to President's Club | No-Nonsense Sales · #619: Active Listening to Loosen up Your Discovery Calls and First Dates | Sam McKenna | 30MPC Hall of Fame
Recommendation · MoneyChris Dreyer advises niching down so specifically that you have a tailored offer: know how many cases you need to create, what content to create, and which marketing channels your niche congregates in. No one says 'I'm in home services' — they say they're a plumber or a roofer; define your niche that specifically.
Ahrefs · How I Make $32M A Year Dominating This SEO Niche
Method · MoneyGary Vaynerchuk gives a concrete post-production recipe: every live show episode should become a Substack and Beehiiv article and be cut into 19 clips posted on every platform.
Method, not a verified protocol.
GaryVee · You Might Be Making Content Completely Wrong
Recommendation · MoneyRob Walling's first strategic approach is to take a general tool and apply it to a new vertical, such as scheduling for hair salons or accounting for car dealerships. He notes this has been popular since SaaS emerged in the late 2000s, when low distribution costs made small niches worthwhile.
Startups For the Rest of Us · Episode 854 | How to Find Startup Ideas (Sneak Peek Chapter from My New Book)
Method · MoneyAlex lays out a giveaway campaign: run a $2,000 private summer camp giveaway as the 'ballistic' version of the campaign, leading with the $5,000 private summer camp full summer experience as the main hook (anchored by starting with the really expensive thing first). Calculate the total value of the package ($500/week x 10 weeks = $5,000) to anchor the prize, and set second place at $3,000 off the $5,000 value, making the ticket $2,000. Make sure more than one person can win second place to stay legal and compliant — say 'more than one person can win' and announce first and second place prizes explicitly instead of saying 'everyone is going to win,' which removes the excitement. Run the giveaway as a seven to ten day campaign with giveaway ads plus a landing page, a countdown timer at the
Method, not a verified protocol.
Alex Hormozi · Can I Save This Failing Theme Park in 90 Days?
Recommendation · MoneyStart collecting all the ground truth you can evaluate your agent against — from historical data, production, or samples run with your domain experts. If you're in a regulated space, define your hard limits (things that definitely shouldn't happen, e.g., in financial services the agent should never give investment advice) and ingrain them in your evaluation set. Ideally this ensures they never happen; at least you will know about it when it does.
AI Engineer · Evals for High-Stakes AI Agents — Doneyli De Jesus & Annabell Schäfer, Langfuse
Recommendation · MoneyDoneyli De Jesus advises verifying that an LLM judge catches what you intended by manually judging a representative sample yourself and optimizing the judge for coherence with human raters. Without calibration against human-labeled ground truth, the judge will not judge the way a human would and may miss what you wanted to catch.
AI Engineer · Evals for High-Stakes AI Agents — Doneyli De Jesus & Annabell Schäfer, Langfuse
Recommendation · MoneyFor customer-facing or regulated-industry use cases, don't risk the agent doing something it shouldn't: build ground truth datasets before production. Curate them with domain experts within the company, include expected outputs (sample replies, expected behavior, keywords), and validate them with customers. Ground truth is also the foundation for auto-improvement.
AI Engineer · Evals for High-Stakes AI Agents — Doneyli De Jesus & Annabell Schäfer, Langfuse
Recommendation · MoneyTo ensure LLM-as-a-judge consistency (inter-rater reliability), judge a representative sample yourself, then run your LLM judge and optimize for coherence with what your human raters do. Academically you'd have a few human raters; practically, one human labels some data and you optimize the judge against that ground truth. Check the judge over time to make sure it stays representative. When running on production data, start with a few too many false positives — catch a little more than necessary but don't miss anything — then tune it down over time.
AI Engineer · Evals for High-Stakes AI Agents — Doneyli De Jesus & Annabell Schäfer, Langfuse
Recommendation · MoneyDefine quality gates for your agent and verify they are being enforced and scored on every interaction. Scores are automatically calculated whenever a new interaction or trace is captured by the system. Score whether information given to the customer is compliant with banking scope (e.g., a weather question is not compliant), detect failure modes and guardrails blocking answers, and use a score to flag customer intent (e.g., investment advice) so you can easily filter for those cases in traces.
AI Engineer · Evals for High-Stakes AI Agents — Doneyli De Jesus & Annabell Schäfer, Langfuse
RecommendationPamela Fox recommends forcing the model to associate each piece of information in its answer with a source, so it realizes when information wasn't in the sources, and adding explicit prompt instructions like 'if the answer for a bit of info is not in sources, say no source provided' and 'do not make up an answer' if a model answers from its weights in RAG. For RAG, instruct the model to answer based on the sources and cite the sources.
AI Engineer · The Model Swap Workshop: GPT-5.5 vs Kimi vs DeepSeek vs Mistral — Pamela Fox, Microsoft
RecommendationPamela Fox recommends using DSPy to declare your program's constraints and let it generate the prompt that adheres to those constraints. You check in your spec and let DSPy write the prompt based on evaluations, set up your spec and then set up checks/tests to see if the output satisfies the constraint, and give DSPy the student model and the reflection model, then it runs the optimizer to find the best prompt.
AI Engineer · The Model Swap Workshop: GPT-5.5 vs Kimi vs DeepSeek vs Mistral — Pamela Fox, Microsoft
RecommendationPamela Fox recommends designing RAG test questions that include information NOT in the dataset to verify the model admits what it doesn't know, e.g., ask about honeybees when the dataset only has carpenter bee info. The RAG test question is: 'What are the key differences between how honeybees and carpenter bees build their nests?' against a carpenter-bee-only dataset.
AI Engineer · The Model Swap Workshop: GPT-5.5 vs Kimi vs DeepSeek vs Mistral — Pamela Fox, Microsoft
Recommendation · MoneyAsk the buyer for a standard MSA and their non-negotiables (payment terms, litigation jurisdiction), then run everything through your own legal, procurement, rev ops, and sales ops in advance — because whatever the buyer wants, you ultimately won't agree to without internal review. Get on your own legal and procurement team's calendar early, before everyone else is rushing to do the same.
30 Minutes to President's Club | No-Nonsense Sales · #613: Master Parallel Selling Strategies to Speed Up Every Deal | Sam Mckenna | 30MPC Hall of Fame
Recommendation · MoneyTo multi-thread without being salesy, ask your contact specific questions they can't answer — questions only the decision-maker could answer — and they'll volunteer to bring that person in. Use decision-maker-level questions like: What are the priorities for this year? What are you forecasting? What's the growth? What's the roadmap? How are you gonna get there?
30 Minutes to President's Club | No-Nonsense Sales · #613: Master Parallel Selling Strategies to Speed Up Every Deal | Sam Mckenna | 30MPC Hall of Fame
Recommendation · MoneyWhen a deal is blocked waiting on a board presentation, schedule the procurement meeting directly after that presentation date. There's no harm in getting the meeting on the calendar early — it gets you on their calendar before everybody else tries to book time.
30 Minutes to President's Club | No-Nonsense Sales · #613: Master Parallel Selling Strategies to Speed Up Every Deal | Sam Mckenna | 30MPC Hall of Fame
