Reviewing Progress Regularly

Peer review at this journal took 38 working days. One change cut it to a fraction of that, and the reviews got better. Not because of AI. Not because of some clever algorithm. Because someone finally treated reviewers like professionals doing skilled work. Our colleagues at The journal Biology Open (Daniel Gorelick, Alejandra Clark) just published results from scaling up something they call "Fast & Fair" peer review. The idea is almost embarrassingly simple: → Contract reviewers in advance → Ask them to respond to an invite within 1 working day → Pay them per manuscript, but only if they deliver on time AND the review is actually useful That's it. No payment for just saying yes. No payment for a late or lazy report. Compensation tied to performance, the way it works in basically every other expert profession. The results, comparing paid review against their conventional process: 📉 Time to first decision: 37.7 days → 5.5 days ✅ Invitations accepted: 23% → 67% 🔕 Reviewers who ghosted: 39% → 13% 📝 Completion once accepted: 87% → 98% Now here's the part that should end the debate. The usual counter-argument is that paying reviewers, and rushing them, produces sloppy science. It didn't. Editors rated the paid reviews slightly higher in quality, with fewer useless reports. Acceptance rates barely moved (59% vs 61%), so the bar didn't drop either. Faster. Higher quality. Same editorial rigor. We have spent years pretending that the slowness of peer review is some noble feature of careful science. It isn't. Most of the delay has nothing to do with the thinking. It's the months spent chasing people who never reply. Researchers donate billions of pounds in unpaid labor to a publishing system that turns around and charges them to read it. Then we act surprised when nobody answers the review invite. You get the behavior you pay for. Or in this case, the behavior you've refused to pay for. Pay reviewers. Set deadlines. Hold the quality bar. It works. Link to article: https://lnkd.in/etyPgXPY

With AI coding, Code review is now even more critical in software engineering. I think if we don't treat it that way, we're going to ship a lot of code nobody actually understands. There's a real risk right now of AI-generated PRs getting thrown over the fence. A junior prompts an agent, a full pull request lands, and the question is: who reviews it? A senior? Another agent? At this moment in model and harness quality, you really want that to be a senior. Models are good. They're not yet good enough to carry the weight of your team's history. The "why we decided this two years ago" context. The utility function three directories over that already solves the problem. The architectural decision that looks weird until you know what it's protecting against. A few things I think need to change about how we review: Code review becomes a teaching forum, not a rubber stamp. Walk juniors through why the model chose its approach. What are the implications? What does this touch downstream? PR size becomes a first-class signal. There's growing evidence that AI-generated PRs are trending much larger, sometimes touching many more files than needed and skipping utilities that already exist in the monorepo. That's a review problem before it's a model problem. Critical thinking gets louder, not quieter. It's easy to get lazy when an agent can do so much for you. The teams that resist that gravity are going to pull ahead. One habit I've picked up: when my agent proposes a solution, I ask it, "tell me why this is the best way to do it." You'd be surprised how often it comes back with "now that you mention it, actually...". Eventually, I do think we'll be able to focus more on evaluating quality through an outcome vs. just pure code lens, but we're not there yet for existing codebases imo. Reading code has always been the skill. It's about to be the skill. Clip from my discussion with Erik Rasmussen at JSNation #ai #programming #softwareengineering

Want a daily board that actually improves performance? Keep it simple, make problems obvious, and turn every red into an action. The goal is simple: See problems early and act fast. This is not a reporting tool. It is a problem-solving tool. It tracks SQDCP, which stands for: Safety, Quality, Delivery, Cost, People. It shows target vs actual clearly. Gaps become visible to everyone. Here is how the board works: Safety first → Review safety before everything else. → A stable workplace comes before performance. → No result is worth unsafe work. Simple daily priorities → Track the same few measures every day. → Keep focus on what matters most. → Balance the process, not one metric only. Clear status → Use green, yellow, and red. → Green means normal. → Yellow warns. → Red means act now. Trend visibility → Show more than today’s result. → Track several days in one view. → Patterns reveal deeper problems. Action ownership → Every red needs an owner. → Every action needs a due date. → That is how gaps get closed. Why this matters: Better visibility → Problems surface faster. → Teams see the same facts. → Leaders can manage by exception. Better response → A red is not failure. → It is the system exposing a problem. → That is how Jidoka works in practice. Better improvement → Teams discuss issues in the huddle. → They assign actions before problems grow. → Daily action builds kaizen rhythm. The best boards are simple, current, and team-owned. They do not just display numbers. They trigger countermeasures. They support escalation when needed. Fix it today. Or escalate it tomorrow with cause. This is not just a board. It is a daily habit for seeing problems, assigning action, and closing gaps. *** 🔖 Save this post for later. ♻️ Share to help others learn the power of SQDCP. ➕ Follow Sergio D’Amico for more on continuous improvement. PS: The board does not improve performance. The daily discipline to act on problems does.

STOP asking ChatGPT to "make it better". Here's how to better prompt it instead: ☑ Clearly Identify the Issue Rather than a vague “make it better,” specify the exact element that needs change. For example: "Rewrite the second paragraph so it includes three concrete examples of our product’s benefits. The tone must be formal and persuasive. Remove any informal language or redundant phrases." ☑ Divide the Task into Discrete Steps Break the overall revision into a sequence of manageable tasks. For example: "Go through my instructions, step by step. – Step 1: Summarize it in one sentence. – Step 2: Identify two specific weaknesses. – Step 3: Rewrite the text to address these weaknesses, incorporating specific data or examples." ☑ Specify the Format and Level of Detail Define exactly how the final output should look. For example: "Provide the final revised text as a numbered list where each item contains 2–3 sentences. Each item must include at least one statistical fact or concrete example, and the overall response should not exceed 250 words." ☑ Request a Chain-of-Thought Explanation Ask the model to detail its reasoning process before giving the final output. For example: "Before providing the final revised text, explain your reasoning step-by-step. Identify which parts need improvement and how your changes will enhance clarity and professionalism. Then, present the final revised version." ☑ Conditional Instructions to Enforce Compliance Add if/then conditions to ensure all requirements are met. For example: "If the revised text does not include at least two concrete examples, then add a sentence with a real-world statistic. Otherwise, finalize the response as is." ☑ Consolidate All Instructions into One Prompt Integrate all the detailed instructions into a single, comprehensive prompt. For example: "First, identify the section of the text that needs improvement and explain why it is lacking. Next, summarize the current text in one sentence and list two specific weaknesses. Then, rewrite the text to address these weaknesses, ensuring the revised version includes three concrete examples, uses a formal and persuasive tone, and is structured as a numbered list with each item containing 2–3 sentences. Each list item must include at least one statistical fact or example, and the overall response must be no longer than 250 words. Before providing the final text, explain your reasoning step-by-step. If the revised text does not include at least two concrete examples, add an additional sentence with a real-world statistic." ___ Why This Works People never give enough context. And once ChatGPT answers, they never correct it enough. Think about it like an intern. Deep prompting is all about precision: give clear instructions, context & the right corrections. PS: Don't forget to use the new o3-mini model. It's crushing any other one. Yes – even DeepSeek.

I never thought something this simple would make such a difference in how I work and manage my time. This 15-minute weekly habit changed everything for me: The weekly review. This is one of the most simple yet powerful practices I've built over the years. It helps me reflect on what’s working, what’s not, and what needs adjusting. The concept, introduced by David Allen in “Getting Things Done”, emphasises the importance of closing open loops and staying on top of commitments before they pile up. Over time, it’s become a cornerstone of my productivity system. Here’s what my weekly review looks like: - Review the past week – I list the dates from the past week and, using my calendar and notes, jot down key events and tasks. - Reflect on achievements and challenges – Take a moment to celebrate what went well and spot areas for improvement. - Plan for the upcoming week – Adjust goals and priorities to make sure I’m focusing on what really matters. It’s a small investment of time, but the impact is huge. Every week, those 15 minutes give me clarity, keeps me on track, and make decision-making easier. Instead of constantly chasing the next thing, it gives me a chance to pause, take stock, and plan with intention. Do you have a system for reflecting on your week, or is this something you’d want to try?

Want your team to perform better this year? Express genuine positivity, early. Researchers published in Organization Science studied 9,968 consultants across 20 months. The result? Consultants who received positive feedback early in the year performed significantly better—regardless of past performance. When leaders express positive emotions early on… Employees feel seen. They feel respected. And they’re driven to maintain that respect all year long. It creates a motivational anchor. Athletes show the same pattern. Another study tracked 245 NCAA athletes and 86 coaches. Those who received early-season praise from their coaches performed better even after controlling for playtime or past stats. But here’s the twist: Teams performed BEST when leaders paired early praise… with a little constructive feedback at the midpoint. Not harsh. Just honest. It’s the classic tough-love combo, with the love first. Why it works: Midpoint critique signals, “You can do better and I believe you will.” It gives people a chance to re-earn the respect they value. And that challenge? It boosts motivation and focus. So, what should you do? Start projects with specific, heartfelt praise. Avoid constant negativity, it backfires. Use midpoints to give clear, constructive feedback. Sequence matters more than style. The bottom line: You don’t have to choose between kindness and candor. Lead with warmth. Course-correct with honesty. The right emotional timing doesn’t just feel better it delivers results.

🎓 Earlier this week in my Harvard Business School course, Demystifying the Family Enterprise, we studied a case I wrote that focused on the importance of estate planning — "Ken Talbot: A Life Well Lived." Ken Talbot built a remarkable business and had a deep commitment to giving back. But when he passed unexpectedly, his estate plan hadn’t kept up with his success or his intentions. What followed was a decade of legal battles, fractured relationships, and a legacy delayed. ➡️ The lesson is simple — and it applies to everyone, not just those with extraordinary wealth. No matter your age or financial situation, you need a will. Estate planning isn’t about predicting the future — it’s about protecting the people you love from uncertainty. It’s about clarity, not control. And it’s one of the most meaningful acts of stewardship we can offer. From the case and my broader research, a few principles stand out: ✅ Have a will — even a simple one is better than none. ✅ Keep it current as life, family, and finances evolve. ✅ Communicate your intentions early and openly — silence creates confusion. ✅ Choose your trustees and executors with care — expertise matters more than familiarity. Having these conversations may feel uncomfortable, but the hardest discussions are often the most loving ones. ❓ If tomorrow came sooner than expected, would your loved ones know your wishes? #EstatePlanning #Legacy #FamilyEnterprise #Stewardship #WealthWithPurpose

Last week’s post about Dominion Energy’s update on data center contracts generated a lot of discussion. Today we take a slightly deeper look at the nature of the new contracts, as well as metrics on capacity and demand. The headline number was that Dominion’s total contracted capacity surged to 40.2 gigawatts (GWs), an 88% gain from the 21.4 GWs in July 2024. Looking deeper into the numbers, Dominion currently has 14 gigawatts of contracts either under construction (CLOA) or under a service contract (ESA). There was a massive jump in contracts for engineering studies for power lines and substations to support potential future data center builds. It's worth taking a moment to understand the three categories of contracts seeking capacity. - Electric Service Agreements (ESA) are contracts for electrical service, where a meter is set and electricity begins flowing. Dominion ESAs increased slightly from 8.0 GWs to 8.8 GWs. - Construction Letter of Authority (CLOA) is a contract to commence construction of substations and other facilities needed to deliver power. The customer is responsible for costs (which could be $25 million for a substation plus any transmission connection cost ) if the project is abandoned. CLOAs at Dominion decreased from 5.8 GWs to 5.2 GWs in the June-December period. This signals that projects are being completed and moving to ESAs. - Substation Engineering Letter of Authority (SELOA) is a contract to perform detailed early-stage engineering studies that may not always lead to new data centers. The customer pays for the study, which study outlines the cost to provide a connection, and then the customer decides whether to proceed. Dominion’s SELOA contracts have increased to 26.2 GWs of capacity, up from 7.6 GWs in July. As I noted last week, the surge in SELOA applications is driven by two items, a procedural change at Dominion, which effectively incentivized developers seeking power to get in line now, and increased developer interest in projects. How much of the new SELOA capacity is likely to convert into construction and service delivery? And when? That’s the big question facing the market, and Virginia is not alone. Similar trends have boosted requests for engineering studies in other major markets, which is one reason that “headline numbers” from utilities may vary from models based on models for historic power demand. Last week I noted differences between the Dominion contract totals and data from PJM and the JLARC report. Folks in the utility industry have noted that this is an apples vs. oranges comparison, as Dominion contract values are for capacity, while the PJM forecast requires a metered demand forecast. I think it’s useful to track all these projections, but do so in context. Some of those Dominion SELOAs may eventually show up in the PJM numbers, but many others may not go forward.

How do the best product teams ship better and faster without things breaking? They embed quality into every step of the development process. Here’s how you can do the same: — 𝗙𝗶𝘃𝗲 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗖𝗵𝗲𝗰𝗸𝗽𝗼𝗶𝗻𝘁𝘀 𝗢𝗡𝗘 - 𝗕𝗲𝗳𝗼𝗿𝗲 𝗙𝗶𝗻𝗮𝗹𝗶𝘇𝗶𝗻𝗴 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 → When: Right after you’ve done your research and before locking down specs. → Why it matters: This is your chance to clarify any confusion, resolve technical risks, and ensure alignment before things snowball. → Win: Fewer mid-sprint surprises and last-minute changes. — 𝗧𝗪𝗢 - 𝗗𝘂𝗿𝗶𝗻𝗴 𝗘𝗮𝗿𝗹𝘆 𝗗𝗲𝘀𝗶𝗴𝗻 𝗥𝗲𝘃𝗶𝗲𝘄𝘀 → When: As soon as wireframes or low-fidelity prototypes start taking shape. → Why it matters: You can catch complexity, edge cases, and UX blind spots before they become costly problems. → Win: Fewer redesigns, smoother testing, and faster handoffs to development. — 𝗧𝗛𝗥𝗘𝗘 - 𝗕𝗲𝗳𝗼𝗿𝗲 𝗕𝗲𝗴𝗶𝗻𝗻𝗶𝗻𝗴 𝗙𝘂𝗹𝗹 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 → When: After design has stabilized but before full-scale coding kicks off. → Why it matters: Confirm the technical feasibility, refine strategies, and estimate accurately so nothing derails you down the line. → Win: Fewer slowdowns and more predictable delivery timelines. — 𝗙𝗢𝗨𝗥 - 𝗣𝗿𝗲-𝗟𝗮𝘂𝗻𝗰𝗵 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 & 𝗗𝗿𝘆 𝗥𝘂𝗻𝘀 → When: Right before launch, after QA rounds and beta testing are complete. → Why it matters: This is your dress rehearsal—simulate real-world conditions, verify stability, and make sure everything works under pressure. → Win: A smooth, stable launch with fewer emergency fixes. — 𝗙𝗜𝗩𝗘 - 𝗣𝗼𝘀𝘁-𝗟𝗮𝘂𝗻𝗰𝗵 𝗘𝗮𝗿𝗹𝘆 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 → When: Immediately after go-live, during the first few hours and days. → Why it matters: Keep a close watch on user behavior, unexpected errors, and drop-offs so you can act fast. → Win: Faster issue resolution, stronger retention, and happier users. — The big lesson? Most problems don’t appear out of nowhere. They’re born in earlier stages and snowball when left unchecked. By building these 5 checkpoints into your product process, you: → Catch issues before users notice. → Save time, money, and your team’s sanity. → Deliver a product you’re proud of. — Deep dive is available in the comments. 👇

Warren Buffett’s recent announcement about a new round of charitable giving offers insights into his thoughtful approach to estate planning—wisdom we can all learn from. He highlights two key principles that resonate deeply: 👉 Involve your heirs early on. Transparent conversations about your estate create clarity and build understanding among family members. 👉 Continuously revisit your plan. Family dynamics and priorities evolve; your plan should, too, to reflect those changes. At Primus Wealth, we see firsthand how adopting these practices can make a world of difference. Estate planning is about more than distributing assets—it’s about creating a meaningful legacy that aligns with your values and goals. By involving your heirs early and revisiting your plan regularly, you help them understand your intentions, reduce confusion, and minimize conflicts. This proactive approach not only preserves wealth but also supports stronger family relationships, ensuring your legacy is carried forward with clarity and harmony. #EstatePlanning #LegacyBuilding #WealthManagement #FamilyOffice