Recommendation · MoneyShaun Crimmins recommends building two champions: a business champion responsible for the outcome and a technical champion living in the workflow every day. Identify both before entering a pilot. For the technical champion, learn how they do their work today, what metrics they care about, and how you can show tangible value to them in a short period of time. Deliver value to the technical champion to make their life easier so they are less likely to say the team can build the solution themselves. Consider the politics behind each champion: what they have to gain or lose by you coming into the organization.
30 Minutes to President's Club | No-Nonsense Sales · #607 - How to Turn Every Sales Pilot Into a Closed Deal | Shaun Crimmins
Recommendation · MoneyShaun Crimmins recommends agreeing on conversion criteria before the pilot starts: define success upfront and establish that hitting those outcomes should lead to a paid agreement. At the week-zero kickoff, ask the customer: 'If we achieve these agreed-upon success metrics, will you move forward?' If the customer answers 'no', it indicates the metrics don't truly matter, the deal is not a priority, or you are not talking to the right stakeholders. Use this question to surface hidden blockers such as politics, other stakeholders, or competing business priorities early in the pilot.
30 Minutes to President's Club | No-Nonsense Sales · #607 - How to Turn Every Sales Pilot Into a Closed Deal | Shaun Crimmins
Recommendation · MoneyRob Walling advises that if a founder is not willing to go full-time on their own startup, it is a vote of no confidence and the company is unlikely to succeed. As a non-founder employee in such a startup, you should leave—the slow traction is structural, not a product problem. He recommends either starting your own company or getting a job elsewhere. He describes a specific situation where a founder is part-time, has hired a remote CEO while the team is co-located, which he calls a structural disaster.
Startups For the Rest of Us · Episode 849 | Legal Threats, AI as Platform Risk, Building Confidence, and More Listener Questions (Rob Solo)
Report · MoneySimple tools like record-keeping execute automatically when the agent calls them; every tool call that writes data triggers LLM-based verification — fast LLM calls analyzing every single database write.
Latent Space · Agents Prompt People: Using Agents for Long-Horizon Financial Work
Creator perspective · MoneyKumar identifies a big hedge fund problem: an analyst works on an idea for a couple of days, then the idea loses the PM's interest or something else takes precedence, it doesn't come back for months, and the analyst misses a key price window. His response: deploy agents that track all of an analyst's notes against the market — even for ideas worked on for only a day — and when an agent detects a dormant idea has become interesting again, flash it not just to the analyst but also to the PM and the trader, prompting them to return to work they haven't looked at in weeks. He adds that timing is the most important thing when striking at an interesting point in the market, even more than which work item you prioritize, so agents should do more than idea generation: they should think about when,
AI Engineer · Proving Alpha: How a Hedge Fund Measures AI's ROI - Hari Kumar, Contour Asset Management
Principle · MoneyFarza explains that most people scrolling only see the first three seconds of a video, so front-load the hook there. Purposely make the first frame show something your target audience recognizes — for Clicky, the first frame was Xcode because curious developers would be interested — and zoom into the part of the screen where your product is, especially when the product is small on screen.
Y Combinator · This Is How You Should Actually Make Launch Videos
Principle · MoneyThe biggest cost savings in the market right now is deploying a dedicated instance if you know your base workload. Plan deployments around bursty traffic patterns with some base load; limit dedicated capacity and let spikes spill over to the public cloud. Mixing dedicated instances with burst to public cloud gives flexibility.
AI Engineer · The AI Bill Is Too Damn High: Tokenomics 101 — Eugene Cheah, Featherless AI
Creator perspective · MoneyGive realtors a VIP/standard tier structure as the offer to present to their clients. The VIP tier costs about $250 more but feels significantly more premium than discounting $250 or giving $250 back to the realtor. If all movers are already master movers, there is no real cost difference between standard and VIP. Keep pushing the VIP price level up until people say no, since the standard tier is always a backup, and the people who have money will spend more. The word 'upgrade' is preferred over 'white glove,' and the VIP upgrade offer is described as the biggest lever.
Alex Hormozi · Give Me 42 Minutes, I'll Show You How To Sell Like The Top 1% | Scale or Fail Episode 1
Creator perspective · MoneyOffer a free VIP upgrade (or 'free white glove') to anyone a realtor refers, so the realtor's customers think good things about them — the realtor needs to gain from referring you. Arm the referrer with a brag script ('my guy, I've got an amazing moving company, they give all my customers free upgrades') that makes the realtor look great. People go to realtors because realtors are supposed to know the area better and have done it more times — expertise is why the referral relationship exists.
Alex Hormozi · Give Me 42 Minutes, I'll Show You How To Sell Like The Top 1% | Scale or Fail Episode 1
Principle · SocialSexual desires and fantasies can be reached, but only through a calculated buildup: start with non-sexual desires, then biggest turn-offs, then what surprisingly turned her on. Abrupt jumps (e.g., favorite food to favorite sexual position) kill the vibe.
Coach Kyle · What Women Actually Want to Talk About (TIER LIST)
Creator perspective · MoneyTo create search-agent training data, use a deterministic algorithm to create seed data — run a seed collection algorithm repeatedly over Wikidata to generate many different hops, then insert those hops into the prompt as seed entities and ask the model to create a question using any or all of them. Design search riddle questions the model cannot readily answer from the internet. Execute the searches via a search tool — Tavily (Exa is an alternative provider, or you can write your own search tool). Tavily returns URLs with titles and content for each result.
AI Engineer · Teaching Agents to Search with NVIDIA Data Designer — Dhruv Nathawani, NVIDIA
Report · MoneyThe presenters demonstrate asking the coding agent to use the Langfuse skill to find issues in traces; the agent accesses live traces to look at what questions are asked, what scores exist, and where all-caps frustration or user disagreement occurs, and also checks for issues beyond the configured evaluators — such as latency problems and tool call failures — to find where the system is silently failing in production.
AI Engineer · Continuously Improving Agents with Langfuse — Annabell Schäfer & Lotte Verheyden, ClickHouse
ReportSelect frames and use the 'Send to Figma Make' option under prototype mode; a finished prototype with interactions can be taken into Figma Make; when sending, it takes the interaction there plus whatever is prompted; a prompt like 'Make this interaction into a section of a website. Use the intro animation and keep things as is. Honor the transitions.' was used, along with instructing it to make no mistakes; a prototype can also be converted to a working site with a prompt like 'make this prototype into a working site include to build an animation in the first frame'.
Figma · Figma for Edu: Prototyping with animations in Figma
Report · MoneyWhen Signal finds a problem, its report lets you add the failing trace to a dataset so you can run evals on it, or create an evaluator based on the problem. It creates a GitHub issue completely describing the problem — which trace went wrong, how to find it, and where to fix it. Connected to your repo, Signal can open PRs directly with suggested fixes; instead of manually reading traces or evals, you review a queue of auto-generated PRs and approve or reject them.
AI Engineer · From Vibes to Production: Evaluating and Shipping AI Agents That Work 201 — Laurie Voss, Arize AI
Report · MoneyTo close the loop from observability to automatic fixing, the speaker asked the agent to fix the specific identified problem. When the agent asked for broad permissions, hitting yes-to-all would upset his head of security, so the agent's proposed actions were reviewed before approval.
AI Engineer · From Vibes to Production: Evaluating and Shipping AI Agents That Work 201 — Laurie Voss, Arize AI
Report · MoneyDORA change failure rate impact is volatile. AI has changed the amplitude of this volatility, with some companies seeing up to a 2% increase (potentially 50% more defects). This volatility exists without AI but is amplified by it, influenced by release pipelines and testing.
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AI Engineer · The State of AI in Software Development: Data from 400+ Orgs — Justin Reock, DX
Recommendation · MoneyKarri Saarinen recommends maintaining a shared, accessible place where customer context, product thinking, and learning live — important for both people and AI agents, who can query it to answer questions. He discourages skipping it: without it, 'What do we have about this?' has no answer. The space can also cover learning about anything else you're doing, not just customers and product.
Lenny's Podcast · Context is now the product: Product leadership when software can build itself | Karri Saarinen
Recommendation · MoneyRyan Cooke advises that output metrics — percentage of PRs, number of PRs, or amount of code generated into production — can disguise how well AI coding systems are actually working, since a rising PR count may belie an overall increase in PRs and make it hard to tell whether AI output is driving outcomes. Instead, measure outcome metrics such as whether the factory is accelerating the ability to deliver features, and think first about how the investment's success will be measured and whether it drives value for the engineering organization.
AI Engineer · No, That's Not a Software Factory — Ryan Cooke, WorkOS
Recommendation · MoneyWorkOS created their own MCP gateway early in the development of their factory, which they call their context engine — it connects into all of their internal systems and builds system prompts and context around how to navigate the tools and when to use them. In the MCP server's tool description, provide the agent a list of the tables, the content they contain, and guidance like: if you're trying to answer questions about this type of content, write a query for these tables. The MCP server gives the agent orientation to understand how the organization uses its tools, how Linear and Snowflake are organized, and guidance on where to find information. If you're just getting started thinking about a software factory, it is well worth your time to invest in an internal MCP gateway server that is
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AI Engineer · No, That's Not a Software Factory — Ryan Cooke, WorkOS
Recommendation · MoneyRyan Cooke recommends investing in an internal MCP gateway server that connects all internal systems, with descriptions telling the agent how to use those tools and how information is organized in them. It will be useful in many other use cases.
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AI Engineer · No, That's Not a Software Factory — Ryan Cooke, WorkOS