daily

By Dan Walsh

The National Pesticides and Drinking Water Action Group (NPDWAG) is urging all users of pesticides in Wexford to remain vigilant as the spraying window ends.

Communities are again reminded that it only takes one drop to impact a drinking water source. While the need and opportunities for spraying declines towards year end, the risk to drinking water sources remains.

The NPDWAG is reminding all pesticide users in Wexford that the actions they take now can help protect drinking water supplies for the communities that depend on them.

Dr Aidan Moody, Department of Agriculture, Food and the Marine (DAFM) and Chair of NPDWAG, said; “We have seen excellent work by farmers and land managers in recent years to reduce pesticide use and to follow correct application methods. We urge everyone to continue the great work and always consider whether a pesticide is needed at all and, where it is, to make sure that best practices are followed. This approach not only protects our drinking water but also supports biodiversity and healthy ecosystems.”

Dr Patrick O’Sullivan of Uisce Éireann added; “Experience shows that pesticide exceedances can still occur outside the main spraying season, particularly during the autumn months. These detections reinforce a simple message: it only takes one drop of pesticide to impact a water source. By following best practice and taking extra care near watercourses, pesticide users can help protect drinking water and build on the significant progress achieved in recent years.”

Pesticide users are reminded that proper storage and disposal of pesticides and their containers remain important throughout the year. Users should always follow the product label, maintain buffer zones near watercourses, avoid spills and take note of any relevant weather forecasts – especially if rain is due within the next 48 hours.

Pesticide users should also note that a closed spray period is specified on the label of some products, during which product should not be used.

Daniel Blum is a product manager at Melio, a B2B payments company, and one of the most systematic thinkers I’ve had on the show when it comes to personal AI infrastructure. He’s spent the past year building a Claude- and Cowork-based productivity system that manages his Notion board, processes his Slack and email, and runs self-improvement loops every week without needing to be prompted. Beyond his own workflow, Daniel built and scaled a “Workstation” onboarding plugin that gets any Melio employee up and running with a personalized Claude setup in about 15 minutes.

What you’ll learn:

1. Why Daniel says the two rules that make any AI system powerful aren’t about the tool you pick

2. How his weekly prep automation fills an entire Notion board from scratch every Sunday, without his touching it

3. The morning brief feature that teaches Claude new internal terms on its own, so company jargon never slows it down

4. Why he describes Notion as “read-only” now, and what that says about how PM workflows are changing

5. The self-improvement loop that watches Daniel’s edits, spots recurring friction, and suggests new skills to build

6. How he uses a skill called “Improve” to filter the endless flood of AI tips without drowning in them

7. What he built to scale his personal system to every PM at Melio, and the UX lesson he learned the hard way

8. The capability gap that’s still keeping him from running 100% of his work through Claude

Brought to you by:

Optimizely—Your AI agent orchestration platform for marketing and digital teams

Jira AI SDLC—Get your tokens’ worth with Jira

In this episode, we cover:

(00:00) Daniel’s background and the PM overhead problem he needed to solve

(03:30) His AI stack at Melio

(05:00) The two rules that make any AI system genuinely powerful

(06:00) The Notion board Cowork built for him (and manages on his behalf)

(07:30) How he contextualizes Claude with voice memos, links, and recurring updates

(09:00) His weekly prep automation

(11:00) His morning brief

(15:00) How Claude flags unknown internal terms and saves them to context

(17:30) Running 70% to 80% of his workday through Cowork

(19:00) Chrome connector vs. MCPs for tools without integrations

(20:00) The real ROI question: why the early weeks feel slow, and why you push through anyway

(25:00) Scaling the system to the team with the Workstation plugin

(26:30) The self-improvement loop

(31:00) How the Improve skill separates actually useful AI tips from the hype

(32:00) The Workstation onboarding flow, and the UX lesson from distributing “Spectacular”

(38:00) The 20% Claude still can’t do, and what changes when it can

(41:00) What Daniel spends his reclaimed time on

(42:30) Claude rage

Tools referenced:

• Claude: https://claude.ai

• Notion: https://notion.so

Other references:

• From a $6.90 newsletter to $3M API: How a non-coder built Memelord | Jason Levin: https://www.lennysnewsletter.com/p/from-a-690-newsletter-to-3m-api-how?utm_source=publication-search

• How the founder of Morning Brew built a Claude content machine that never runs out of ideas and never sounds like slop | Alex Lieberman: https://www.lennysnewsletter.com/p/how-the-founder-of-morning-brew-built?utm_source=publication-search

Where to find Daniel Blum:

LinkedIn: https://www.linkedin.com/in/blumd/

Website: https://www.imdanielblum.com

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

By Dan Walsh

Four Rivers presents Jenny Instead, a new play by Wexford playwright, poet and screenwriter Eoghan Rua Finn, at Wexford Arts Centre this Thursday, Friday and Saturday.

Eoghan Rua Finn will be known to Four Rivers audiences for his Civil War drama, Amongst Men which was staged by the company in 2023. 

Jenny Instead is set in present-day Dublin. Paddy, a recently returned emigrant, and Maria, a reclusive artist. The plan is simple- temporarily escape themselves. But when their guards come down and unexpected sparks fly their time together becomes more real than either was prepared for.

Can they face each other and themselves on a night neither will forget? And in the face of human complexity is there ever such a thing as a simple plan? Jenny Instead is an intimate examination of difficulty of connection and authenticity in the modern world.

The play is directed by Emma Finegan who has just finished a stint as an associate director at The Gate Theatre. It will be designed by Liam Doona (A Handful of Stars and My Real Life) and lit by Ferdy Emmet. Costumes will be by Wexford’s Jeni Roddy.

The play will feature award winning actress Lauren O Leary (Stage Debut Award for Little Gem off Broadway) and Kyle Hixon (Wednesday- Netflix and Ridley Scott’s The Last Jewel – Fox Searchlight)

Four Rivers Artistic Director Ben Barnes told WexfordLocal.com; “We are delighted to be staging Eoghan’s new play, Jenny Instead with a strong creative team led by Emma Finegan and two fine young actors. This will be the sixth new work from the South East that we have staged over the past four years and underlines our commitment to give voice to the stories and concerns of our audiences and writers” 

Performances take place at Wexford Arts Centre from Thursday September 3^rd and Friday, September 4^th, at 8pm with a Matinee Special: Play & a Pizza on Saturday September 5^th at 2.30pm. Running time: 75 minutes approx.

For further Information contact: www.wexfordartscentre.ie

Dwarf Fortress is getting the mother of all magic updates, extending to "the fundamental cosmological makeup of the universe" "Pursue magical research that really feels like discovery" Infamously simulation-heavy colony builder Dwarf Fortress is getting a Myth and Magic update that, at the possible risk of being maybe a touch hyperbolic, threatens to make all other fantasy game spellcraft look like a sleepy bout of Got Your Nose. It's summarised by Bay12 co-founder Tarn Adams as a set of procedural systems "that go beyond combining spell effects... straight to the fundamental cosmological makeup of the universe", allowing for "magical situations that you cannot get any other way." So many dwarves are going to die, aren't they, Tarn? And in such exotic and unexpected ways. Here's a brief video announcing the update, which is coming later this year. If I'm reading the tea leaves correctly, the update will generate a variety of approaches to sorcery in the course of regular world generation. Distinct species of wizardry and witchcraft will arise with tectonic abandon in the course of laying down rivers and mountains, and charting the fates of creatures, populations and settlements. It certainly sounds like a big bounce beyond the existing relatively threadbare magic system. As Adams goes on, this will allow "your fortresses to pursue magical research that really feels like discovery", encompassing "magic materials, enchantments, rituals, and ruins" together with spells that just "blow things up". You can see a few examples in the video, including a goblin-shredding hex that doubles as a means of shifting stone. All of it tied into "how that particular universe works down to its bones", Adams promises. They've been working on the feature for many years. I probably don't need to remind you Rock Paper Magma Shotgunners that Dwarf Fortress is pretty intense and elaborate even without any procgen thaumaturgy. If you do need reminding, here's Nate's old Basement of Curiosity series. Please bear in mind that the first entry was written in 2019, long before the launch of the Steam edition with its more approachable artstyle – the game has grown horrifyingly since then. In 2023, Sin also had thoughts on why none of Dwarf Fortress's many imitators or fellow travellers have managed to eclipse it.

Apple's unusually timed announcement of new Mac mini and Mac Studio models this week was driven by unexpectedly strong enterprise appetite for AI hardware, according to The Information. Apple normally releases new Mac models in the autumn, closer to October or November, making this week's announcement unusually early, falling just before the anticipated arrival of new iPhone models. The Information says that the AI-driven boom in Mac Studio and Mac mini sales is behind the early launch. Apple noticeably promoted the ability to link multiple Mac Studios together into a single, more capable system for running large frontier AI models, a feature aimed at business and developer customers rather than everyday consumers. Apple highlighted the Mac mini and Mac Studio's shift toward business buyers in June, with a "Business at the Park" event involving executives from major companies Ford, Disney, and Anthropic. The Mac mini was said to be the "darling" of the event. Even so, enterprise's rush toward powerful desktop Macs more broadly took Apple by surprise. The company reportedly did not possess an engineering team dedicated to business customers or staff focused on developer relations, and lacked an enterprise AI strategy. Businesses that approached Apple asking to buy access to the company's Private Cloud Compute infrastructure were reportedly turned down. Apple is instead leaning on partners such as WebAI and Mount Thor, which provide AI tools and execution environments built on Apple hardware. A surge in demand for Mac hardware to run AI models has coincided with the global memory shortage, leaving many Mac mini and Mac Studio configurations out of stock for months. Some enterprise customers are reportedly turning to other hardware such as Nvidia's DGX Spark, a compact AI desktop launched late last year in a form factor similar to the Mac mini's, as Apple's own high end configurations remain difficult to get hold of.

How I turned Claude into a self-improving PM assistant | Daniel Blum (PM, Melio)

Brought to you by:

• Optimizely—Your AI agent orchestration platform for marketing and digital teams

• Jira AI SDLC—Get your tokens’ worth with Jira

Daniel Blum is a product manager at Melio who has built a self-improving AI system that now handles 70% to 80% of his workday. In this episode, he breaks down how Claude and Cowork manage his Notion board, prepare him for the week, scan Slack and email for important context, and learn from his edits without waiting for explicit feedback. He explains how he turned the system into a 15-minute onboarding experience for other Melio employees, why the first few weeks of building with AI can feel painfully slow, and how the payoff eventually helped him accomplish a week’s worth of PM work in a single day.

Biggest takeaways:

1. The architecture matters more than the AI tool itself. Daniel believes a system becomes genuinely powerful when it can update its own core files and connect to the tools someone already uses. Once those pieces are in place, the system can improve and become more useful over time, whether it is built in Cowork, Codex, ChatGPT, or something else. He created a transformative setup using the tools Melio had already licensed, proving that the underlying architecture matters more than choosing the perfect platform.

2. Context isn’t something you set up once; it requires an ongoing system. Daniel spent months giving Claude voice memos, links, decks, and verbal brain dumps to build detailed context files for every area of his work. He then created recurring updates that refresh those files every few weeks. This keeps the gap between what Claude knows and what is actually happening inside the company as small as possible.

3. The most impressive part of Daniel’s morning brief is that it identifies what it does not know. Each day, Claude reviews his Slack, email, and notes for unfamiliar terms, projects, or goals that do not appear in its context files. It then asks Daniel targeted questions to fill those gaps. When it encountered the phrase “settlement cap,” for example, it had already read the relevant thread and understood the general idea. It only needed Daniel to confirm the meaning before saving it.

4. The value of a personalized AI system builds slowly, then becomes enormous. Daniel is candid about how frustrating the first few weeks can feel. The system does not know enough yet, its work is slightly off, and nearly everything requires a second look. But once someone pushes through the work of centralizing information and building context, the payoff can be difficult to overstate. He can now accomplish in one focused day what previously took him an entire week.

5. Self-improvement loops learn from the difference between what the AI drafted and what the person actually sent. Daniel built a weekly skill that compares Claude’s original drafts with his final versions, then uses those differences to improve future work. It resembles Alex Lieberman’s “write like me” loop, but it relies less on explicit feedback. Instead, it observes Daniel’s actual behavior and learns from the small edits he makes instinctively.

6. Feedback telemetry turns personal AI workflows into products that can improve themselves. Every one of Daniel’s skills captures moments of friction. If he says something is not working or requests a correction during a session, the system logs that signal. Once a week, his improvement loop identifies the most common problems and recommends updates. It is essentially analytics for his internal tools, and it gives him a structured way to refine the system based on how it performs in real life.

7. The Workstation plugin addresses one of the biggest barriers to adopting AI inside a company: personalization. Daniel watched several product managers struggle with Spectacular, his spec-writing gem, because it had been designed entirely around his own working style. He responded by building an onboarding flow that connects each employee’s tools, maps their colleagues, and learns their voice in about 15 minutes. Instead of starting from scratch with a generic system, every Melio employee now begins with a strong shared foundation personalized to their needs.

8. The biggest remaining limitation of today’s AI systems is persistence, not intelligence. Daniel estimates that Claude already handles 70% to 80% of his workday. What it still cannot reliably do is continue working in the cloud while his computer is off. He is already preparing for that future by teaching Claude how to recognize the “closed state” of different tasks. If a drafted Slack message is no longer saved, for example, the system can infer that it was probably sent. When truly autonomous operation becomes available, Daniel’s system will already understand what completion looks like.

If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.

Catch you next week,
Lenny

P.S. Want every new episode delivered the moment it drops? Hit “Follow” on your favorite podcast app.